Desiccant Evaporative Cooling

Transcription

1 Desiccant Evaporative Cooling Optimal strategy for cooling in a Dutch climate Date: July 10 Version: Final report

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3 Desiccant Evaporative Cooling Optimal strategy for cooling in a Dutch climate Document title: Program: Author: Desiccant Evaporative Cooling Optimal strategy for cooling in a Dutch climate Eindhoven University of Technology Master program Sustainable Energy technology Specialization: Sustainable Energy in the Built Environment Ralph van Oorschot Student ID: Committee members: prof. ir. P.G.S. Rutten Architecture Building and Planning dr.ir. M.G.L.C. Loomans Architecture Building and Planning dr.ir. A.W.M. van Schijndel Architecture Building and Planning dr.ir. H.P. van Kemenade Mechanical Engineering Graduation company: Eindhoven University of Technology Status: Final report Date: July 10

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5 ABSTRACT The built environment is a large energy consumer, it is estimated to consume -40% of the world s total energy consumption. Cooling represents a large part of this consumption. This energy demand will only increase because of the increased living standards. A possible solution to reduce the energy consumption for cooling could be by using solar thermal cooling systems. Solar thermal energy is hereby used to provide cooling. Desiccant Evaporative Cooling (DEC) is one of those techniques. The cooling effect of a DEC system is based on the adiabatic cooling principle. Moisture in the air is adsorbed by a sorption wheel which is regenerated with solar thermal heat. The dry air is then adiabatically cooled which decreases its temperature. This DEC system consists of several different HVAC components, which can all be controlled separately. The goal of this research is to find the optimal strategy for controlling these components in the Dutch climate. A simulation of the DEC system is made and analyzed. An optimization is made based on these results. A very hot summer month in 1976 is used for optimization of the control strategy. Total electrical and thermal energy consumption in that month is reduced by optimizing this strategy. The reduction in energy demand of this optimization is the difference between the original and improved DEC system, which is shown in Table 1 below. For a reference, a conventional cooling system is also added. Optimizations show that a large reduction in thermal energy consumption could be achieved. This large reduction of thermal energy indicates also that a system without the dehumidification option could provide enough cooling for the most situations. This option, called combined humidification is also improved and added to the comparison. Table 1: Thermal and electrical energy consumption compared to a conventional system Energy consumption Electrical [%] Thermal [%] Conventional system 100 % 0 % Original DEC system 71.8 % 100 % Improved DEC system 63.7 % 6. % Improved combined humidification system 23.8 % 0 % Overheating hours High humidities t >.5 C t > C t > 25.5 C RH>75% RH>70% Conventional system 0,00 0,00 Original DEC system 2,27 0,00 Improved DEC system 0,76 0,00 Improved combined humidification system 0,81 3,37 0,0 0,5 1,0 1,5 2,0 2,5 0,0 1,0 2,0 3,0 4,0 % of occupied time % of occupied time Figure 1: Overheating hours and high humidities for the simulated month in percentages of occupied time - i -

6 The overheating hours and high humidities are shown in Figure 1. The DEC system as well as the combined humidification system provides a comfortable temperature with both less than 1% overheating in the hot summer month. The combined humidification mode looks very promising, but it has also some drawbacks. The ventilation rate is at some short periods 12ACH which requires a well balanced terminal system to prevent unwanted draughts. The combined humidification system is not able to dehumidify the outside air. Therefore there are some periods with humidities over 70%RH, which could be unwanted. If these drawbacks are acceptable the combined humidification would be a good solution, otherwise the DEC system is preferred. But both options consume less energy than the conventional cooling system. - ii -

7 ACKNOWLEDGEMENTS This report is my master degree thesis for the study Sustainable Energy Technology at the Eindhoven University of Technology. I started this master degree program in September 08. As specialization I chose Sustainable energy in the built environment. I had finished my courses in October 09 and at that moment I started with my graduation project. At the start of this project I did not have a subject yet. I have had contact with some companies who had some research proposals, but unfortunately I could not find the right one for me. More than a month had passed and my graduation supervisor prof. ir. PGS Rutten came to me with the idea of solar thermal cooling. I was inspired by that topic and it caught my interest. But also, I was hoping to graduate for a company and get some experience in practical situations. I did not want to waste more time, so I started my graduation project for the TU/e about solar thermal cooling, especially DEC system. This research project didn t go without a hitch. My motivation skills were put to the test more than once. Especially when you re working at home it is very hard to beat the temptation to do other nongraduation related things. The simulation part was a lot more work than expected. The only result I had after a couple of months hard work were some working simulations, but I could not show any result yet. After finishing the simulation phase and having some results I got enthusiastic again. My supervisors told me more than once to speak a little softer when I was too enthusiastic. The whole project was one large learning phase. I learned a lot about Matlab, air handling units, but probably the two most important, using a systematic approach and making a good planning. This leads me to the last thing where I want to thank everyone who supported me during my graduation project. First everyone who helped me at at the TU/e. Especially Paul Rutten for the interesting discussions and the useful feedback, Jos van Schijndel who helped me with the simulations and HAMbase, Marcel Loomans for its feedback and Erik van Kemenade who joined the exam committee at the last moment. Besides the employees of the TU/e, I want to thank DWA for the received documents and information about DEC systems. And finally, I want to thank my friends too. I was in the fortunate situation that 4 of my best friends including my girlfriend were also in their graduation phase. So there was always someone to discuss a problem or a moment to relax and get our mind off things. An extra motivation was the contest I held with my girlfriend about who graduated first. I want to thank her especially for accepting my grumpy moments and my late night work. Ralph van Oorschot July 10 - iii -

8 NOMENCLATURE Symbol Description Unit A Area m 2 C P Specific heat at constant pressure KJ/kg K G Solar irradiation W/m 2 h Specific enthalpy KJ/kg m mass kg p Pressure Pa p ws Saturation pressure Pa q Time rate of energy transfer W Q Total energy transfer kwh T Absolute temperature K t Temperature C v Specific volume m 3 /kg V Total volume m 3 W Humidity ratio of dry air g/kg da ε Effectiveness - μ Efficiency - Indices a da e env m min max th w Abbreviation ACH Comb. Hum. COP DEC HVAC HAMbase PMV PPD PV Regen RH SP Description Ambient Dry air Electric Environment Mean Minimum Maximum Thermal Water Description Air changes per hour Combined humidification operation mode Coefficient of performance Solar powered solid Desiccant Evaporative Cooling Heating Ventilation Air Conditioning Heat Air Moisture transport in multi zone buildings Predicted mean vote Predicted percentage dissatisfied Photovoltaic Regeneration temperature Relative humidity Set point - iv -

9 CONTENTS ABSTRACT... I ACKNOWLEDGEMENTS... III NOMENCLATURE... IV 1 INTRODUCTION Theory Solar thermal cooling Working principle of a DEC system Objectives Research question(s) Methodology MODELING Simulink model Operating mode evaluation System outlet air conditions Energy consumption MODEL ANALYSIS Load Room climate Cooling and Dehumidification potential Climate Required cooling power (HAMbase) External room influences Thermal mass Ventilation Regeneration temperature Solar collector and Buffer Demand and Production Buffer size Verification Results OPTIMIZATION General optimization Humidity Ventilation reduction at unoccupied hours Unit specific optimization DEC-system Combined humidification system Results DISCUSSION, CONCLUSION AND RECOMMENDATIONS Discussion Conclusion Recommendations REFERENCES v -

10 APPENDICES The following appendices are part of this report: Appendix APPENDIX I: APPENDIX II: APPENDIX III: APPENDIX IV: APPENDIX V: APPENDIX VI: APPENDIX VII: APPENDIX VIII: APPENDIX IX: APPENDIX X: APPENDIX XI: APPENDIX XII: APPENDIX XIII: APPENDIX XIV: Contents Theory behind thermal cooling Different solar cooling methods Comparison between different solar cooling systems Choice of modeling software Modeling Available control strategies Fixed parameters for analysis Operating mode evaluation Analysis of the DEC system + load Cooling and Dehumidification potential Climate data HAMbase Solar collector Conventional system - vi -

11 1 INTRODUCTION Energy consumption in the built environment has increased in recent years with the development of the economy worldwide. The energy consumption of the built environment is estimated between - 40% percent of total energy use. Cooling represents a large part of the energy consumption in the built environment. Because of the increased living standards and occupant demands, cooling energy demand will only increase. A strong increase in cooling demand is expected according to Figure 2. Figure 2: Perspective in the EU for cooling energy demand [1] This increased demand for cooling power will most certainly give problems in future if only nonsustainable cooling systems are used. The nominal and peak load on the electricity grid will increase on hot summer days, because of the high electrical load of conventional cooling systems. This could cause blackouts, due to overloads in the electrical grid. Almost all countries in the EU signed the Kyoto protocol and thereby committing that they reduce the production of greenhouse gasses. With an increase in energy demand for cooling, a sustainable solution for cooling could provide a solution. Solar thermal cooling can help alleviate the problem. The fact that peak cooling demand in summer is associated with high solar radiation offers an excellent opportunity to exploit solar thermal cooling technologies. 1.1 THEORY Solid desiccant evaporative cooling (DEC) is one of the systems that uses thermal energy to provide cooling. In this case a solar thermal collector is used to provide the required heat. A DEC system is not the only system available that uses solar thermal energy to provide cooling. In the next chapters an overview of the different available (solar)thermal cooling methods are given and the working principles of the DEC system is described. The working principle of the other cooling methods is described in Appendix II. A table is made for comparison with the other solar cooling techniques and an overview of the different installed systems in Europe is given SOLAR THERMAL COOLING The idea behind solar thermal cooling is graphically represented in Figure

12 dispersed heat Figure 3: General Scheme - Solar thermally driven air conditioning [1] Solar heat is captured with a solar thermal collector. This heat is stored in a buffer or directly used in a thermally driven cooling process, which can be based different technologies. Chilled water or cooled air is transferred to the building and used for cooling. The theory behind this process can be found in Appendix I. The idea of cooling with solar energy is not new, the first world exhibition was in 78 in Paris. Augustin Mouchot produces the first ice block with solar energy using a periodical absorption machine of Edmund Carré Mouchot.[1] From a thermodynamic point of view there are many processes conceivable for the transformation of solar energy into cooling. An overview is given in Figure 5. Figure 4: Sketch of the first solar thermal cooling device in 78 Solar radiation Electric proces (PV) Heat tranformation process Thermo mechanical process Open cycle Closed cycle Liquid sorbent Solid sorbent Liquid sorbent Solid sorbent Liquid desiccant cooling Solid desiccant evaporative cooling Absorption cooling Figure 5: Classification of the different solar powered cooling techniques [2] Adsorption cooling The most promising techniques are in the heat transformation processes, or solar thermal driven processes. There are four different kinds of systems available: Absorption cooling Closed cycle, liquid sorbents. Adsorption cooling Closed cycle, solid sorbents. Solid desiccant evaporative cooling Open cycle, solid sorbents. Liquid desiccant cooling Open cycle, liquid sorbents. Absorption cooling is the most commonly used technique for thermal cooling, most probably because it is the longest available and has the lowest investment costs. Liquid desiccant cooling has - 2 -

13 some advantages and is very promising, but still needs some further development. The solid DEC systems are an average performer. A further comparison between these different systems is given in Appendix III

14 1.1.2 WORKING PRINCIPLE OF A DEC SYSTEM Solid desiccant evaporative cooling is an open loop solid sorbent cooling system. In an open system the refrigerant is discarded from the system after providing the cooling effect and new refrigerant is supplied in its place. Therefore only non toxic liquids such as water and air can be used as refrigerants with direct contact to the surrounding air. An overview of the working principles of other solar cooling systems could be found in Appendix II. The DEC system consists of multiple components, which are all commonly used in HVAC application. The main components are a sorption wheel, heat recovery wheel, two humidifiers (direct and indirect), a heating coil and two fans. The sorption or desiccant wheel consists of a rotating wheel made of silica gel or Lithium-Chloride. It can adsorb moisture at the dehumidification side and desorbs the moisture at the high temperature regeneration side. In this process there is primarily moisture transport between the sides and a minimum of heat transport. The heat recovery wheel is a heat exchanger which transfers thermal energy from one side to the other. The humidifiers spray water to the system that evaporates. The evaporation of this water consumes energy, which results in a lower air temperature with a higher humidity. The complete DEC cooling process as in Figure 6, works which the following steps: 1. Warm and humid outside air enters the system. It is dehumidified and the moist in the air is adsorbed by the sorption wheel. 2. The warm dry air is pre-cooled with a heat recovery wheel that is in counter-flow with the cooled return air from the building. 3. Dry air with a moderate temperature is coming out of the heat recovery wheel, which is connected to a humidifier. The air is humidified and the temperature of the air decreases further through evaporative cooling. 4. Cool air with a moderate humidity is supplied to the room. Temperature and humidity is increased by means of loads in the room. 5. Return air from the building is cooled using evaporative cooling by making use of a humidifier. Humidity level is close to its saturation point. 6. The cool and humid air is pre-heated with a heat recovery wheel that is in counter-flow to the air entering the building. 7. The air is further heated with solar heat by making use of a heating coil. This is connected to a buffer and solar collector. 8. The heated air is used to regenerate the sorption wheel. The water bound in the pores of the desiccant material of the sorption wheel is desorbed by means of the hot air. 9. Heat and humid air leaves the system through the outlet. An example of temperatures and humidity levels according to each step is shown in Figure

15 Humidifiers Load Heat recovery Sorption wheel wheel Figure 6: Graphical representation of a solar desiccant evaporative cooling system [3] Figure 7: Mollier chart for the different steps in a DEC system - 5 -

16 1.2 OBJECTIVES The main objective of this research is to find an optimal use of a solar DEC system for the Dutch climate. Optimal use is based on the operation strategy that consumes the least electrical energy and efficiently uses thermal energy while maintaining indoor comfort level. The main objective can be divided in the following sub objectives: Comparison of different solar driven cooling techniques Understand theory behind the DEC system and existing control strategies Build a simulation model of a DEC system Verify the simulation based on the obtained data from actual components Analyze the behavior of different parameters in the DEC system Optimize the control strategy to minimize primary energy consumption Comparison with a conventional cooling system 1.3 RESEARCH QUESTION(S) What is the optimal use of a solar DEC system for cooling in a predefined utility building, while maintaining a certain comfort level in the Dutch climate? The optimal use is the operation strategy with the least electrical energy consumption and most efficient use of thermal energy while maintaining the indoor comfort level. 1.4 METHODOLOGY The methodology proposed is divided into the following phases: The first phase is the definition phase. This to define and well understand the working principle of the DEC system. A comparison between other solar driven cooling systems is made. Also the available literature about control strategies is evaluated. The second phase is the modeling phase. In this phase a model is built that is able to cope with different control strategies for all the components. This model should be validated with data from real components. The third phase is a model analysis phase. In this phase the behavior of different parameters is analyzed. The fourth phase is an optimization phase. This to optimize the control strategy of the DEC system to minimize primary energy consumption and efficient use of solar energy. The last phase is the comparison phase. The most optimal use of the DEC-system are compared with each other and a conventional cooling system

17 2 MODELING To be able to analyze and improve the DEC system a computer simulation is required. There is not a complete model of the system available. Therefore all the different components have to be modeled to make a simulation. Each component is modeled and verified separately before combining them together to make a complete model. Matlab Simulation is chosen for the simulation, this choice is based on different criteria, which is described in Appendix IV. 2.1 SIMULINK MODEL The same approach is used for the modeling of the required components. A simulation model is made based on a mathematical model, which is verified with data from an actual component from manufacturers. In the Appendix V, models of all the required components are evaluated in the same way: 1. Short introduction of the component and working principle 2. Mathematical model used for simulation 3. Matlab Simulink model 4. Assumptions used for the model 5. Verification of the model These verified models are combined to a single Matlab Simulink file which simulates the complete DEC system including a room. This model can be seen in Figure 8. All the colored blocks are subsystems which simulate the different components of the DEC system, except for the grey, dark green and the pink bock. The grey part is a summation of the energy consumption of the different components and the pink subsystem is an embedded Matlab file used for programming different control strategies. The green subsystem is the simulation of the room with a thermal load. Figure 8: Overview Simulink model used for simulating the DEC system - 7 -

18 2.2 OPERATING MODE EVALUATION Controlling the DEC system can be done in various ways. The system consists of multiple components which can all be switched and controlled separately. By switching some of the components on or off, it is possible to switch between different operating modes. An overview of some articles about control strategies are given in Appendix VI, based on those results the available operating modes are given in Table 2. An x indicates that the component of the system is switched on, otherwise it is switched off. Table 2: Different operation modes for a DEC system Operation mode Fan(s) Direct humidifier Indirect humidifier Heat recovery wheel Desiccant wheel Off Ventilation (free cooling) x Direct humidification x x Indirect humidification x x x Combined humidification x x x x Desiccant Evaporative Cooling (DEC) x x x x x To see the behavior of the DEC system for the different operating modes, simulations are made for a range of inlet air temperatures and humidities for every operating mode SYSTEM OUTLET AIR CONDITIONS A constant internal load is used to determine the return air conditions. If thermal energy is used, it is assumed to be available infinite at a defined temperature. The calculations are done for an average 1m 2 of office floor area. Fixed parameters of Appendix VII are used if not stated otherwise. The results for the outlet air at different operation modes can be found in Appendix VIII. A short summary is given in Table 3 below. Table 3: Summary of results room supply air conditions Operating mode Ventilation mode Direct humidification mode Indirect humidification mode Combined humidification mode DEC mode Summary Room supply air temperature is a bit higher than outside air temperature, due to temperature increase by the fans. Absolute humidity does not change. Return air conditions have no influence on the room supply air conditions. Air is cooled adiabatically, room supply air temperature is dependent on outside humidity. Relative room supply air humidity is equal to setpoint of the direct humidifier. In case of higher relative outlet humidity than setpoint the profile is equal to that in ventilation mode. Return air conditions have no influence on the room supply air conditions. Room supply air temperatures decreases until the point that the cooling effect of the indirect humidifier is smaller than the added heat by the internal load. The temperature decrease is highly dependent on the absolute return air humidity. Absolute humidity does not change. Combination of the direct- and indirect humidification mode effects occur. Outlet temperature is lower than the modes separately. Outlet temperature is highly dependent on absolute outside humidity. Regeneration temperature is of large influence of the room supply air - 8 -

19 conditions. At 40 C regeneration temperature the extra cooling effect can almost be neglected compared to the combined humidification mode ENERGY CONSUMPTION A comparison between energy consumption for the operating modes is made, an example at an outside temperature of C and 10g/kg da can be found in Table 4 and Table 5. Table 4: Energy consumption for 1m 2 floor area at normal internal load and min. ventilation rate (outside C 10 g/kg da ) Electricity consumption [W/m 2 ] Heat consumption [W/m 2 ] COP e [-] Outlet temperature [ C] Relative outlet humidity [%] Ventilation mode 2,23 0,00 10,3,25 36 Direct humidification 2,35 0,00 9,8,43 64 Indirect humidification 2,64 0,00 8,7 21,83 61 Combined humidification 2,64 0,00 8,7 21,31 64 DEC mode regen. at 40 C 2,86, 8,0 21, 64 DEC mode regen. at 60 C 2,95 73,48 7,8,0 64 DEC mode regen. at 80 C 3,03 1,60 7,6 15,1 64 Table 5: Energy consumption for 1m 2 floor area at high internal load and min. ventilation rate (outside C 10 g/kg da ) Electricity consumption [W/m 2 ] Heat consumption [W/m 2 ] COP e [-] Outlet temperature [ C] Relative outlet humidity [%] Ventilation mode 2,23 0,00 17,9,25 36 Direct humidification 2,35 0,00 17,0,43 64 Indirect humidification 2,81 0,00 14,2 23,55 61 Combined humidification 2,79 0,00 14,3 21,97 64 DEC mode regen. at 40 C 3,01 33,19 13,3,69 64 DEC mode regen. at 60 C 3,10 74,56 12,9 19,61 64 DEC mode regen. at 80 C 3,19 117,50 12,6,86 64 The COP for every mode is better at higher internal load compared to the normal internal load. This is obvious, because the provided cooling is larger at the high internal load with equal energy consumption. The COP e of the indirect humidification mode is comparable to the combined humidification mode, but performs worse when looking at the outlet temperature. This mode does not have other advantages compared to combined humidification and is therefore never an optimum situation

20 3 MODEL ANALYSIS The goal of this analysis is to optimize the operation strategy of the DEC system. Components of the DEC system are not changed, only dimensions and the operation strategy. Buffer Solar collector Outside air Electrical energy Return air DEC system Process air Thermal energy Return air Room supply air 1m 2 office Climate 1 Load 2 3 Figure 9: Simplified graphical overview of the stepwise analysis Within the operation modes in Table 2 of chapter 2.2 it is also possible to change operation parameters, such as fan speed, reheating energy, humidification ratio. Therefore finding the optimal operating strategy for different scenarios can be a complex task. A stepwise approach is chosen to find the optimum control strategy and corresponding parameter values: 1. A room with a fixed internal load is connected to the DEC system to see the influence of it and determine the cooling potential per operating mode. 2. A climate is introduced. Outside air conditions, as well as the external load of the room are dependent on that climate. 3. Based on the thermal energy demand the appropriate buffer and collector size is determined This approach is also visualized graphically in Figure 9, where the dotted lines are boundaries of each step. If a line crosses a boundary line assumptions are mode for that variable. If not stated otherwise, the assumptions made in Appendix VII are used. 3.1 LOAD Room air conditions for the different operating modes are evaluated. A mixing system inside the room is assumed and therefore the return air temperature is assumed equal to the in room air conditions. Based on these results the maximum cooling potential for every operating mode is determined. Fixed parameters from Appendix VII are used, except for the maximum allowed setpoint for the direct humidifier. Simulations show that a higher setpoint will still fulfill the comfort level. The setpoint of the direct humidifier increased from 65%RH to a maximum of 85%RH

21 3.1.1 ROOM CLIMATE The result of this analysis can be found in Appendix IX. Some important points can be noticed when comparing the results of the different operating modes with previous results from Appendix VIII The shape of the graphs is roughly the same, but the in room temperature is very dependent on the load and ventilation rate at all operating modes. An increase in ventilation rate increases the allowed load with an equal in room temperature. If the ventilation rate doubles, the energy and moisture removed from the room doubles too. The energy consumption of the DEC system doubles too. Looking at the energy consumptions between modes, the difference between the lowest energy consumption (ventilation mode) and highest (DEC mode) at equal ventilation rates is about %. The cooling effect is much larger when switching between modes than when increasing ventilation rate by %, therefore increasing ventilation rate should be used as a last option. As already determined in chapter 2.2.2, indirect humidification has a higher COP with equal or higher in room temperatures than other modes. This mode is never preferred and shall thus be omitted. Based on the results of chapter 2.2.1, Table 4 and Table 5 an energy optimized operation mode selection can be made. This is shown in Table 6. The mode with the lowest selection priority number should be chosen first, as long as it fulfills the operating range for temperature as well as humidity. The control parameters indicate the set point of the controllable parameters for each of the operating modes. Table 6: Energy optimized operation mode selection. Ventilation mode Direct humidification Indirect humidification Combined humidification Selection Control parameters priority 1 Airflow 2 Airflow SP Direct Humid Airflow SP Direct Humid SP Indirect Humid. DEC mode 4 SP Direct Humid SP Indirect Humid. Regen. Temp. Airflow Lowest allowed value, Highest allowed value, Lowest allowed value that satisfies room air conditions

22 3.1.2 COOLING AND DEHUMIDIFICATION POTENTIAL To optimize the control strategy the operation range and cooling potential for each of the modes should be known. The operating range is the range in which the cooling power and dehumidification of the system is equal or larger than the cooling demand. As determined before, the delivered cooling power and dehumidification is dependent on several different parameters, such as the outside air conditions, operating mode and ventilation rate. The maximum cooling power and moisture removal is determined by assuming a room temperature of 25 C with 60%RH. Simulations for cooling power and moisture removal are made for the different operating modes and outside air conditions, the results can be found in Appendix X. The dehumidification is based on the maximum setpoint of 85%RH for the direct humidifier. If a lower setpoint is used, the dehumidification potential would be larger, but the cooling potential would decrease. The maximum cooling and moisture removal potential is depended on the ventilation rate. It increases as the ventilation rate increases, therefore the results are given for a minimum and maximum ventilation rate. The minimum cooling load is assumed to be 35W/m 2 and the moisture removal is 0.002g/s/m 2, which is equal to the high internal load. Based on the results of Appendix X, the maximum outside air conditions can be found for every mode to provide the required cooling. Based on the operating mode selection in Table 6 the most energy efficient control strategy could be found. In case of an overlap between modes, the most energy efficient operation mode is chosen that could provide at least the required cooling and dehumidification. The result can be found in the figures on the next page. In case of the moisture removal, the ventilation mode is not shown, this because it overlaps a large part of the figure. The ventilation mode can provide the moisture removal of 0.002g/s/m 2 at absolute outside humidities below 8.75g/kg da at minimum ventilation mode and 10.4g/kg da at maximum ventilation mode, independent on the outside temperature

23 Figure 10: Cooling potential in W/m 2 based on operating mode selection of Table 6 that could provide a minimum cooling load of 35W/m 2 at minimum ventilation rate (4 ACH) Figure 11: Cooling potential in W/m 2 based on operating mode selection of Table 6 that could provide a minimum cooling load of 35W/m 2 at maximum ventilation rate (8 ACH) Ventilation mode Direct humidification mode Combined humidification mode DEC mode at 40 C regeneration temp DEC mode at 60 C regeneration temp DEC mode at 80 C regeneration temp

24 Figure 12: Maximum moisture removal potential in g/s/m 2 based on operating mode selection of Table 6 that could provide a minimum dehumidification of 0.002g/s/m 2 at minimum ventilation rate (4ACH) Figure 13: Maximum moisture removal potential in g/s/m 2 based on operating mode selection of Table 6 that could provide a minimum dehumidification of 0.002g/s/m 2 at maximum ventilation rate (8ACH) Direct humidification mode Combined humidification mode DEC mode at 40 C regeneration temp DEC mode at 60 C regeneration temp DEC mode at 80 C regeneration temp

25 Setpoint [-] Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot 3.2 CLIMATE The purpose of these simulations is to see the influence of a varying outside climate. The climate influences the outside temperature but also the external load in the room. The next simulations are based on the climate data at de Bilt (NL), in the period from until Detailed information of this profile is given in Appendix XI. Because of this climate, the simulations are not quasi static anymore and the HAMbase room model is used for simulations, this model also takes the thermal inertia of the room into account. A stepwise approach is used to see the influence of the climate and the influence of a dynamic room: - The in HAMbase simulated room is examined to determine the required cooling power - The DEC-system is connected to HAMbase and the energy consumption of the system is determined. - The effect of differences in thermal mass is simulated. - Ventilation rate is increased to see the influence. - Simulations are done with different regeneration temperatures to see the influence. To start with, a temperature based control strategy is used. An infinite regeneration temperature of 80 C is assumed. To prevent too low night temperatures, the heat regeneration wheel is operated when the room temperature is below 23 C. Max. Direct humidifier Indirect humidifier (+ energy recovery wheel) Regeneration temperature (+ sorption wheel) Air flow speed Min C C.5 C 25.5 C Figure 14: Temperature based control strategy REQUIRED COOLING POWER (HAMBASE) Two different types of rooms are used in the simulation phase. Until now a simple model with a fixed internal sensible and latent energy load is used. This can only be used for the quasi static simulations. The second model is based on a HAMbase model. HAMbase is a simulation model for the heat and vapor flows in a building. With this model, the indoor air humidity and energy consumption for heating and cooling of a multi-zone building can be simulated.[3] A couple of changes are made in HAMbase to make it suitable for implementation it in the simulation. These changes are explained in Appendix XII. A room with the size of x25x2.5 meter is simulated in HAMbase. These dimensions are chosen, to match the ventilation rate with data used for the verification of the sorption and heat exchanger wheel. Four different models are made to check the influence of thermal mass and adiabatic or non adiabatic situation

26 Adiabatic / Climate influence Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot All 4 outer walls, ceiling and floor are assumed adiabatic. Thin outer walls Thermal mass Thick outer walls 3 outer walls, ceiling and floor are assumed adiabatic. One external wall is orientated south with 25x2.5m glazing. Figure 15: Schematic representation of the different room models used in the simulation. The internal (cooling) load is W/m 2 at normal load and 35W/m 2 at high load. The occupation period is from 8:00 until :00, including weekends. At non occupation hours the internal load is estimated to be 5W/m 2. A simple simulation is run to see the properties of the room. The required cooling power, is the energy that has to be removed from the room to keep the internal air temperature at C. This is done for the 2 different internal load profiles (normal and high load), for the adiabatic and non adiabatic situation. - -

27 Required cooling power [W/m 2 ] Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot Normal internal load High internal load Normal internal and external load High internal and external load Time [days] Figure : Required cooling power for different loads The cooling demand is a little lower than the internal load at the adiabatic situation. This could be caused by the thermal mass of the building which spreads out the cooling demand over the whole day. The external load adds an extra 5-15W/m 2 to the required cooling demand EXTERNAL ROOM INFLUENCES The control strategy as in Figure 14 is used in combination with the low thermal mass building, this to see the influence of energy consumption by the DEC system for the different loads. The result is shown in Figure 17. Normal load Adiabatic Normal load External high load Adiabatic High load External 1,67 0,52 1,71 3,15 1,73 1,78 Energy consumption Qe [kwh/m²] Qth [kwh/m²] 4,81 11,5 Overheating hours t >.5 [%] t > [%] t > 25.5 [%] 0,00 0,00 0,00 2, ,0 0,5 1,0 1,5 2,0 2,5 kwh/m² floor area % of occupied time Figure 17: Simulation results for different loads for the simulated month Electrical energy consumption is almost equal for the different loads. The thermal energy consumption increases as the load increases. In case of the high load external there are some overheating hours. From now on the room with external wall shall be used. Water consumptions for the high load room with external influences is 25.1 kg/m 2 floor area for the simulation period of 31 days. With an average price of 1 per m 3 water and 0.25 per kwh, the cost of water can be neglected compared to the energy costs. Water consumption will not be used as a factor to be optimized THERMAL MASS The control strategy as in Figure 14 is used in combination with external load, to see the influence of the thermal mass

28 Normal load Low mass Normal load High mass High load Low mass High load High mass 1,71 3,15 1,7 2,64 1,78 1,77 Energy consumption Qe [kwh/m²] Qth [kwh/m²] 10,25 11, kwh/m² floor area Overheating hours t >.5 [%] t > [%] t > 25.5 [%] 0,00 0,00 0,81 2,27 0,0 0,5 1,0 1,5 2,0 2,5 % of occupied time Figure : Simulation results for the difference in thermal mass for the simulated month The high thermal mass decreases the energy consumption and reduces the overheating hours. Based on these results the high thermal mass building is preferred and shall from now on be used VENTILATION Influence of ventilation increase is simulated. There are three options for a ventilation increase in the step from C: Option 1: Increase of regeneration heat with a minimum ventilation rate (original situation) Option 2: No regeneration heat, but instead ventilation increase as a last option Option 3: Increase of regeneration heat combined with an increase ventilation rate as a last option. These three options are graphically shown in Figure

29 Setpoint [-] Setpoint [-] Setpoint [-] Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot Option 1: Direct humidifier Indirect humidifier (+ energy recovery wheel) Regeneration temperature (+ sorption wheel) Air flow speed Min C C.5 C 25.5 C Option 2: Max. Direct humidifier Indirect humidifier (+ energy recovery wheel) Air flow speed Option 3: Max. Direct humidifier Min C C.5 C 25.5 C Indirect humidifier (+ energy recovery wheel) Air flow speed Regeneration temperature (+ sorption wheel) Min C C.5 C 25.5 C Figure 19: Graphical representation of the different control strategy options The high thermal mass building with external influences is used for this simulation. Normal load Option:1 Normal load Option:2 Normal load Option:3 High load Option:1 High load Option:2 High load Option:3 1,7 2,64 1,73 0 1,74 2,15 1,77 1,85 0 1,88 Energy consumption Qe [kwh/m²] Qth [kwh/m²] 7,39 10,25 Overheating hours t >.5 [%] t > [%] t > 25.5 [%] 0,00 0,00 0,81 0,00 1,21 3, ,0 1,0 2,0 3,0 4,0 kwh/m² floor area % of occupied time Figure : simulation results for differences in ventilation rate for the simulated month

30 In both cases option 3 uses the most electrical energy and has the least overheating hours. The thermal energy consumption is decreased compared to the original situation. Option 2 as well as option 3 has some advantages over the first option REGENERATION TEMPERATURE Simulations for the chosen month are made to determine the thermal energy demand. In this case an infinite thermal energy supply at a fixed temperature is assumed. Calculations are made at a water temperature of 60 and 80 C. The 40 C option is omitted because of the small cooling potential. High internal load with external influences is used to see the maximum cooling potential. The results of these simulations are shown in Figure 21 below. Option 1 at 80 C Option 1 at 60 C Option 3 at 80 C Option 3 at 60 C 1,77 1,77 1,88 1,9 Energy consumption Qe [kwh/m²] Qth [kwh/m²] 6,3 7,39 10,25 9,43 0,81 0,00 0,40 Overheating hours t >.5 t > t > , ,0 2,0 4,0 6,0 8,0 kwh/m² floor area % of occupied time Figure 21: Simulation results for different regeneration temperatures for the simulated month Option 3 has the least overheating hours combined with a thermal energy reduction of -%. Energy consumption is only increased by 6-7%. - -

31 Difference between consumption and production [kwh/m 2 ] Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot 3.3 SOLAR COLLECTOR AND BUFFER The goal of this chapter is to find the optimal dimensions for the solar collector area and buffer size. A stepwise approach is used, which is described below: 1. Calculate the required solar collector size based on the thermal energy demand. 2. Determine difference between production and consumption to calculate the appropriate buffer size. 3. Simulate the system to verify the determined values DEMAND AND PRODUCTION The solar collectors should provide the required thermal energy demand of the DEC system. In this simulation, vacuum tube collectors (Apricus tube collector) are used because of the high efficiency at high temperatures. In Appendix XIII the optimal angle of the collector and the added heat per 1m 2 collector is determined. Based on the energy consumption Figure 21, the solar collector size per 1m 2 floor area can be calculated, which is shown in Table 7. Table 7: Solar collector size required to match the thermal energy consumption at high internal load Q th Consumption per month [kwh/m 2 floor area] Q th Production per month [kwh/m 2 panel] Panel size [m 2 /m 2 floor area] Control option 1 at 80 C Control option 1 at 60 C Control option 3 at 80 C Control option 3 at 60 C BUFFER SIZE To determine the optimum buffer size, the difference between demand and production is calculated. This is done for a regeneration temperature of 60 C and 80 C with the increased ventilation rate (option 3). The results are given in Figure o C average buffer temperature 80 o C average buffer temperature Time [days] Figure : Required buffer capacity per 1m 2 of floor area

32 Top node buffer temperature Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot The maximum difference between consumption and production is around the start of day, which is around 1.kWh at 60 C and 1.38kWh at 80 C regeneration water temperature. Based on a maximum buffer temperature change of ±5 C from the desired regeneration temperature, the buffer size should be 109kg at 60 C and 1kg at 80 C per m 2 floor area. At a maximum change of ±10 C of the desired regeneration temperature, the buffer sizes decrease to 54.5kg at 60 C and 59kg at 80 C per square meter floor area VERIFICATION Simulations are done to verify the calculated values for buffer and collector size. The temperature profile of the top node buffer temperature is given in Figure 23. The differences in overheating hours are shown below in Figure. For these simulations the high internal load profile is used in combination with the increased ventilation (option 3) o C 54.5kg buffer 60 o C 109kg buffer 80 o C 59kg buffer 80 o C 1kg buffer Time [days] Figure 23: Top node temperature profile for different buffer sizes - -

33 Thermal energy Consumption [kwh/m²] Production [kwh/m²] 80 C Buffer infinite 80 C Buffer 1kg 80 C Buffer 59kg 60 C Buffer infinite 60 C Buffer 109kg 60 C Buffer 54.5kg 6,3 6,3 6,38 6,59 6,29 6,61 7,39 7,39 7,6 7,8 7,6 7,84 Overheating hours t >.5 [%] t > [%] t > 25.5 [%] 0,00 0,00 0,00 0,40 0,40 0, ,0 0,2 0,4 0,6 0,8 kwh/m² floor area % of occupied time Figure : Simulation results for different buffer sizes and regeneration temperatures for the simulated month Energy production by the solar collector is a bit higher than calculated. This difference occurs most probably because of the buffer temperature drop around day. Because of this temperature decrease, the efficiency of the solar collector increases. The energy consumption is a bit higher, most probably the result of the peak production in first 10 days. Because of this peak, the DEC system uses water of a higher temperature which allows higher energy transfer with the regeneration air. One exception is the 60 C with the 54.5kg buffer. In this case the water temperature is too low to provide enough cooling. Therefore the overheating hours are also increased. At the regeneration temperature of 80 C the buffer of 59kg could fulfill the cooling demand. At 60 C a buffer size of 109kg is required with this control strategy. 3.4 RESULTS HAMbase is used for the simulations of the room. The cooling load consists of an internal as well as an external load. At high load, the internal load is 35W/m 2 in occupied periods and the external load fluctuates between 5-15W/ m 2, depending on the climate. The room with high thermal mass shows lower cooling energy consumption and is therefore used in further simulations. An increase in ventilation rate as well as a higher regeneration temperature increases the cooling potential. Both options consume a lot extra energy and should be used wisely. The two following candidates have a large cooling potential with the least energy consumption: DEC system: DEC system with a high regeneration temperature combined with ventilation increase as last option. Combined humidification system: DEC system without using the sorption wheel and any regeneration heat. In this case, combined humidification with ventilation increase as last option is used for maximum cooling. The buffer size and solar collector area for the DEC system is also determined. At an average regeneration temperature of 60 C a panel size of m 2 per 1m 2 floor area is required and a

34 buffer size of 109kg/m 2. At an average regeneration temperature of 80 C a panel size of m 2 per 1m 2 floor area is required and a buffer size of 59kg/m

35 4 OPTIMIZATION Based on the model analysis in chapter 3, there are two candidates which have the most potential: DEC system: DEC system with a high regeneration temperature combined with ventilation increase as last option. Combined humidification system: DEC system without using the sorption wheel and any regeneration heat. In this case, combined humidification with ventilation increase as last option is used for maximum cooling. The operation strategy of both candidates will be further optimized in this chapter. The components of the DEC system are not changed. In chapter 4.1 some generation optimizations are done which can be applied to both candidates. In chapter 4.2 some specific optimizations are made. 4.1 GENERAL OPTIMIZATION In this chapter two general optimizations are done which are applied to both candidates HUMIDITY In previous simulation, only overheating hours are used to determine the comfort level. Humidity was not controlled, but it is also of importance for the perceived comfort level. The direct humidifier is now disabled when room humidity exceeds 65-70%RH. A lower maximum humidity would give a small potential for adiabatic cooling, which results in more overheating hours. DEC mode DEC mode Max. 70%RH Combined humid. Combined humid. Max. 70%RH Combined humid. Max. 65%RH Energy consumption Qe [kwh/m²] 1,9 1,9 1,85 0 1,85 0 1,85 0 6,38 6,39 Qth [kwh/m²] Overheating hours t >.5 t > t > ,40 0,40 3,69 3,69 4,11 High humidities RH>75% RH>70% 0,00 0,00 2,48 2,38 2, ,0 2,0 4,0 6,0 0,0 1,0 2,0 3,0 kwh/m² floor area % of occupied time % of occupied time Figure 25: Simulation results for different maximum room humidity levels for the simulated month In case of the DEC system, the humidity is always below the 70%RH. This optimization has no positive or negative effect on the results. Changes in thermal as well as electrical energy consumption are so small that they can be neglected. For the combined humidification system, there are some hours in which the relative humidity exceeds 70%RH. This optimization improves humidity level a little. When a setpoint of 65%RH is used, the reduction in high humidities are small compared to the increase in overheating hours, therefore is chosen to use a maximum room setpoint of 70%RH VENTILATION REDUCTION AT UNOCCUPIED HOURS The fans inside the DEC system consume the most electrical energy compared to all the other components

36 To reduce this energy consumption, the ventilation rate is decreased at unoccupied hours. This is done when the room temperature is below C. A 1/ of the minimum ventilation rate is reached at 23 C in unoccupied situations. Shutting down the system completely at unoccupied situations and starting up a few hours before the occupation period has a negative effect to overheating hours, most probably because of the high relative humidities at the morning periods and the high thermal inertia of the room The following parameters are used for the different candidates: DEC mode: 60 C regeneration temperature with 109kg/m 2 buffer and an options for ventilation increase Combined humidification mode: Maximum humidity of 70%RH Energy consumption Qe [kwh/m²] Qth [kwh/m²] Overheating hours t >.5 t > t > 25.5 High humidities RH>75% RH>70% DEC mode DEC mode Optimized 1,9 1,62 6,39 6,51 0,40 0,40 0,00 0,00 Comb. Humid. Comb. Humid. Optimized 1,84 0 1,57 0 3,69 3,72 2,38 2, ,0 2,0 4,0 0,0 1,0 2,0 3,0 kwh/m² floor area % of occupied time % of occupied time Figure : Simulation results for ventilation reduction at unoccupied hours for the simulated month The ventilation reduction at unoccupied hours has a positive effect on the electrical energy consumption for both candidates. An average electricity consumption reduction of more than 14% is achieved. There is only a minimum increase in overheating hours. The thermal energy consumption is slightly increased, this increase is small compared to the reduction in electrical energy. 4.2 UNIT SPECIFIC OPTIMIZATION Some optimizations cannot be applied to both candidates. In the next sub-chapters, both options are optimized separately DEC-SYSTEM The DEC system provides fewer overheating hours compared to the combined humidification system, but is consumes more electrical and thermal energy than the combined humidification system. The main aim of this optimization is to reduce the energy consumptions of this system. Two new operating modes are used for the different optimization, which are also given in Figure 27: Option 4: Minimizing electrical energy consumption Option 5: Minimizing thermal energy consumption The result of those approaches is shown in Figure. - -

37 Setpoint [-] Setpoint [-] Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot Max. Option 4: Direct humidifier Indirect humidifier (+ energy recovery wheel) Regeneration temperature (+ sorption wheel) Air flow speed Min C C.5 C 25 C 25.5 C Option 5: Max. Direct humidifier Indirect humidifier (+ energy recovery wheel) Air flow speed Regeneration temperature (+ sorption wheel) Min C C.5 C 25 C 25.5 C Figure 27: Graphical representation two control strategies used Original Option 4 at 60 C Option 4 at 80 C Option 5 at 60 C 1,62 1,51 1,49 1,58 0,72 Energy consumption Qe [kwh/m²] Qth [kwh/m²] 6, ,58 0,13 Overheating hours t >.5 t > t > ,40 0,80 0, ,0 0,2 0,4 0,6 0,8 1,0 kwh/m² floor area % of occupied time Figure : Simulation results for the DEC system optimization for the simulated month Reducing electrical energy consumption results in a large increase in thermal energy consumption (53%), it reduces the electrical energy consumption only 6%. This is not considered to be the optimal control strategy. In case of the thermal energy reduction (option 5), a reduction of 93% is achieved and electrical energy is also reduced by 2%, compared to the original situation. The reduction in electrical energy consumption is most probably the result of the sorption wheel that has to run less hours. In the original situation the sorption wheel starts at the same moment the ventilation rate is increased. (.5 C) This operation strategy is very close to the combined humidification and is considered to be the optimal control strategy. To provide the required thermal energy a solar collector area of 7.9e-3m 2 panel/ m 2 floor area is required

38 The buffer size should relatively be larger compared to the solar collector size. This is because there is only a peak use at some moments. A buffer size of 12kg/m 2 floor area has enough buffer capacity COMBINED HUMIDIFICATION SYSTEM The combined humidification system has some large advantages over the DEC-system. It consumes less energy and fewer components are required, which results in a lower investment. The main disadvantages are the overheating hours and high humidities, which are more than in the case of the DEC-system. In previous simulations the sorption wheel and heat exchanger for the solar thermal energy are still in the system, those components are obsolete when used in this set-up. When both components are removed, the pressure drop over the system is reduced, and also the energy consumptions of the fans. This effect could a large, because the sorption wheel has a large pressure drop. One option to reduce those overheating hours is to switch to the highest ventilation rate a lower room temperature. Another option is to increase the maximum ventilation rate in the case of overheating. Energy consumption Overheating hours High humidities Qe [kwh/m²] Qth [kwh/m²] t >.5 t > t > 25.5 RH>75% RH>70% Original Extra components removed Early switch to max. ventilation Max. 12ACH (Max. 70%RH) Max. 12ACH Max. 67.5%RH Max. 12ACH Max. 65%RH 0 0,58 0 0,58 0 0,59 0 0,59 0 0,59 0 1,57 0,81 1,62 1,66 3,72 3,45 3,38 2,40 2,43 2,83 3,37 2,84 2, ,0 2,0 4,0 0,0 2,0 4,0 kwh/m² floor area % of occupied time % of occupied time Figure 29: Simulation results for the combined humidification system optimization for the simulated month Removing the sorption wheel and the heat exchanger reduces the energy consumption by more than 60%. It has also a positive effect on the overheating hours which are reduced a little. This could be a result from the fan which adds less heat to system. An early switch to maximum ventilation rate at 25 C has almost no effect to the reduction of overheating hours. An increase in ventilation rate also increases the cooling potential. To reduce overheating hours, the maximum ventilation could be increased above the maximum 8ACH to 12ACH for the short periods of overheating hours. This reduces the overheating hours by more than a factor 4. The increase in maximum flow rate does reduce the overheating hours, but increases the maximum humidity a little. The high humidities have an effect both on the perception of the comfort and the growth of micro-organism. According to the ISO 77 norm [4]: The influence of humidity on thermal sensation is small at moderate temperatures close to comfort and may usually be - -

39 Temperature Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot disregarded when determining the PMV value, therefore can be assumed that the effect of humidity in perception of comfort is small. There is an increase growth of Bacteria, viruses and Fungi at a relative humidity above 60-70RH%.[5] These high humidities only occur for a very small periods of time, therefore the increased airflow is considered as the most optimal control strategy in combined humidification mode. 4.3 RESULTS Based on the model analysis and optimization phase, the two most promising options are compared with each other. To be able to make a good comparison, a conventional cooling system is also used for the simulation of the same room. Specifications of this system and simulations can be found in Appendix XIV. The results below are based on providing the required cooling power for the room with the high thermal mass, high internal load and one external wall orientated south. The best control strategy for each option is compared with the conventional system. The results can be found in Figure below. Energy consumption Qe [kwh/m²] Qth [kwh/m²] Conventional Combined humidification DEC 0,59 0 0,72 1,58 2,48 Overheating hours t >.5 t > t > ,00 0,81 0,76 0,00 0,00 High humidities RH>75% RH>70% 3, ,0 0,5 1,0 kwh/m² floor area % of occupied time Figure : Comparison of the optimization simulation results for the simulated month 0,0 2,0 4,0 % of occupied time Both systems have large energy reduction compared with the conventional system. There is a little overheating, most of it occurs at the same time for both options. At that moment, the outside air has a high temperature combined with a very high absolute humidity Combined humidification system DEC system Conventional system Time [days] Figure 31: Overheating at the most extreme day

40 Predicted percentage dissatisfied [%] Relative humidity [%] Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot Combined humidification system DEC system Conventional system Time [days] Figure : High humidities at the most extreme day To provide information about the perception of the thermal comfort of the different systems the predicted percentage dissatisfied people is calculated based on the predicted mean vote (PMV) value for an activity level of 1.2 met, 0.75 clo and 0.02m/s air velocity.[4] The result is shown in Figure 33. The predicted percentage dissatisfied (PPD) value is in almost all days between the 5% an 10%, except for the extreme situation in day Conventional system DEC system Combined humidification system Time [days] Figure 33: Predicted percentage dissatisfied for the simulated month Based on energy consumption, the combined humidification option is preferred. Looking at the overheating hours and high humidities, the DEC system would be a better option. If high requirements are set for the indoor climate, the DEC system is best option. Otherwise the combined humidification option is better option. The electrical energy consumed by the systems could also be supplied by photovoltaic (PV) panels. A simple simulation is made to calculate the total energy production per square meter solar panel. The total production for the simulated month with PV panels with 15% efficiency is.15kwh/m 2. Based on these values a comparison for total required panel size could be made. - -

41 Table 8: Calculation of total required collector/panel size Collector/ m 2 floor PV/m 2 floor Total area for the 500m 2 building Conventional system m 2 Combined humidification system m 2 DEC system 7.9e m 2 The DEC system as well as the combined humidification system consumes water. The consumption for the 31 days period is 27.1 kg/m 2 for the DEC-system and 25.8 kg/m 2 for the combined humidification system

42 5 DISCUSSION, CONCLUSION AND RECOMMENDATIONS This chapter starts with the description of the comments with regard to the used methodology. The second paragraph describes the conclusions of this thesis. In the last chapter some recommendations that can be used for improvement and further research are given. 5.1 DISCUSSION This thesis described the numerical modeling and control optimization of a DEC system that is used for cooling a modeled room. The model is used to perform simulations and the results are used to draw conclusions. Some aspects in this process have not been taken into account. The realized model of the DEC system is based on static models of the components. This system is connected to a room simulation in HAMbase, which is a dynamic model. The effect of this interaction is not taken into account. The simulation time step used for the simulations is 1 minute. Because of the absence of the dynamics inside the models, it is assumed that have a faster reaction time than the simulation step size. The connection between the HAMbase room and the DEC system is not validated. An assumption is made that there is a perfect mixing inside the room and that the energy and humidity added or extracted is the difference between the room supply air and the in room air conditions. This ideal situation would not occur in reality. Therefore, the simulation results could differ from the real situation. Only temperature and relative humidity are taken into account to determine the discomfort. PMV and PPD values are calculated based on assumption of air flow speed, clothing level and metabolism. Especially air flow speed could have a large influence on the perception of comfort. Simulations are only done for one month. This hot month is chosen because it consists of multiple extreme situations. Other extreme situations that did not occur in this specific month are not simulated and therefore not taken into account. The DEC system is only optimized to provide cooling, it cannot provide heating in a winter situation. This research is focused on providing the required cooling demand with a DEC system. Combinations of a conventional cooling system with a DEC system are not considered. A possible option could be that the base load is provided by the DEC system and at high cooling demand a conventional system assists and it provides the extra cooling. In case of the combined humidification system, the air flow rate is very high (12ACH) for some short periods of time, this could decrease the comfort level. It is assumed that this is allowed for a short period of time. The decrease of comfort level due to high air flow rates is not taken into account. Extra pressure loss in the DEC system because of longer air ducts, terminal systems and filters are not taken into account. This extra pressure loss will increase the energy consumption of the fans. Total energy consumption will be a bit higher in reality then simulated. But since both systems have equal losses, they are still comparable with each other. - -

43 In the air ducts after the direct humidifier, the relative humidity is 85%RH for large periods of time. At these humidities there is an increased risk of growth of Bacteria, viruses and Fungi. This will add extra costs for cleaning and preventing growth inside these air ducts. 5.2 CONCLUSION The goal of this research is to find the optimal use for cooling with a solar DEC system in a Dutch climate. A systematic approach is used to see the influence of each parameter. An optimization is made based on the results found. The most important result at the analysis phase is that the cooling potential is much more related to outside humidity than outside temperature, especially at combined humidification mode. Thermal energy for dehumidification is most required at high outside humidities. The idea that there is a high thermal energy demand at high temperatures/solar irradiation is thus not valid. Therefore production and consumption of thermal energy do not have the same profile. The importance of the ventilation rate could be seen at the introduction of a room with load. A double in ventilation rate doubles the allowed internal load with the same room temperature. The energy consumption of the DEC system doubles too, so it should be used wisely. A very hot summer month in 1976 is used for analysis and optimization of the operation strategy. The cooling load consists of an internal as well as an external load. At high load, the internal load is 35W/m 2 at occupied hours and the external load fluctuates between 5-15W/ m 2, depending on the climate. Optimizations show that a large reduction in thermal energy consumption could be achieved. This large reduction of thermal energy indicates also that a system without the dehumidification option could provide enough cooling in the most situations. There are two options that could provide the required cooling: DEC system: DEC system with a high regeneration temperature combined with ventilation increase as last option. Combined humidification system: DEC system without using the sorption wheel and any regeneration heat. In this case, combined humidification with ventilation increase as last option is used for maximum cooling. Total electrical and thermal energy consumption in that month is further reduced by optimizing the operation strategy. The optimized control strategy for both options is shown in Figure. In case of the DEC system a maximum air flow rate of 8ACH is allowed and for the combined humidification system the maximum is 12ACH for short periods of time. To reduce energy consumption, the air flow rate is gradually decreased in unoccupied hours to 1/ of the minimum ventilation rate at 23 C

44 Setpoint [-] Setpoint [-] Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot DEC system Max. Direct humidifier Indirect humidifier (+ energy recovery wheel) Air flow speed Regeneration temperature (+ sorption wheel) Min C C.5 C 25 C 25.5 C Combined humidification system Max. Direct humidifier Indirect humidifier (+ energy recovery wheel) Air flow speed Min C C.5 C 25.5 C Figure : Graphical representation two operation strategies used The reduction in energy demand of this optimization is the difference between the original and improved DEC system, which is shown in Table 9. The overheating hours and high humidities are shown in Figure 35. For a reference, a conventional cooling system is also added. Table 9: Thermal and electrical energy consumption compared to a conventional system Energy consumption Electrical [%] Thermal [%] Conventional system 100 % 0 % Original DEC system 71.8 % 100 % Improved DEC system 63.7 % 6. % Improved combined humidification system 23.8 % 0 % Overheating hours t >.5 C t > C t > 25.5 C High humidities RH>75% RH>70% Conventional system 0,00 0,00 Original DEC system 2,27 0,00 Improved DEC system 0,76 0,00 Improved combined humidification system 0,81 3,37 0,0 0,5 1,0 1,5 2,0 2,5 0,0 1,0 2,0 3,0 4,0 % of occupied time % of occupied time Figure 35: Overheating hours and high humidities for the simulated month in percentages of occupied time - -

45 The DEC system as well as the combined humidification system provides a comfortable temperature with both less than 1% overheating is the hot summer month. The combined humidification mode looks very promising, but it has also some drawbacks. The ventilation rate is at some short periods 12ACH which requires a well balanced terminal system to prevent unwanted draughts. The system is also not able to dehumidify outside air. Therefore there are some periods with humidity s over 70%RH, which could be unwanted in some cases. If these drawbacks are acceptable, the combined humidification would be a good solution, otherwise the DEC system is preferred. But both options consume less energy than the conventional cooling system. 5.3 RECOMMENDATIONS For both improvement of the results and further research, the following aspects are recommended: Total life cycle cost analysis for the different systems should be done to give information on the financial aspect. This research is only focused on the cooling of a utility building. Simulations of a year are required for a complete analysis. The DEC system could have some advantages over the combined humidification system if the thermal heat from the solar collectors could also be used for heating in winter. The components of the model are verified individually. A verification of the complete DEC system with all the components could add some strength to the validity of the simulation. To make the cooling of the building 100% sustainable, the water used in the system should also be provided by a sustainable source. One option could be to store rain water for the use in the system. The air velocity inside the building is not specifically simulated, it is just assumed ideal mixed. The comfort level is also based on factors such as the air velocity. An appropriate terminal system should be chosen to stay in the comfort range with the combined humidification system. The difference in energy consumption between the DEC-system and the combined humidification is being mainly caused by the pressure drop over the sorption wheel. An improvement could be to bypass the sorption wheel in the DEC system except when it is required for dehumidification

46 6 REFERENCES [1] Dr. Tomas Núñez, "Solar Cooling and Air-Conditioning," in SOLATERM Expert Mission, Tunis, 08. [2] S. and Bansal, PK Jain, "Performance analysis of liquid desiccant dehumidification systems," International Journal of Refrigeration, vol., no. 5, pp , 07. [3] A.W.M. van Schijndel, "Integrated heat air and moisture modeling and simulation," Eindhoven: Technische Universiteit, Eindhoven, 07. [4] "NEN-EN-ISO 77: Ergonomics of the thermal environment Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria," ISO 05, Geneve, 05. [5] C. Cox M. Loomans, "Grenzen voor de lelatieve vochtigheid van het binnenklimaat. een beoordeling op basis van een literatuurstudie," TNO bouw, pp. 1-11, Apr. 02. [6] H.M. Henning, "Solar assisted air conditioning of buildings-an overview," Applied Thermal Engineering, vol. 27, no. 10, pp [7] RZ and Ge, TS and Chen, CJ and Ma, Q. and Xiong, ZQ Wang, "Solar sorption cooling systems for residential applications: Options and guidelines," International Journal of Refrigeration, vol., no. 5, pp , 09. [8] C.A. and Grossman, G. and Henning, H.M. and INFANTE FERREIRA, C.A. and Podesser, E. and Wang, L. and Wiemken, E. Balaras, "Solar air conditioning in Europe-: an overview," Renewable & sustainable energy review, vol. 11, no. 2, pp , 07. [9] W. and Napolitano, A. and Melograno, P. Sparber, "Overview on world wide installed solar cooling systems," in 2nd International Conference Solar Air-Conditioning, Tarragona, 07. [10] J.Y. and Li, S. and Hu, Y.F. Wu, "Study on cyclic characteristics of the solar-powered adsorption cooling system," Science in China Series E: Technological Sciences, vol. 52, no. 6, pp , 09. [11] Márton Varga, "Internal Heat Loads," Austrian Energy Agency, Vienna,. [12] TESS library for TRNSYS, "TESS libraries Proforma documentation," Thermal Energy Systems Special, Madison, Wisconsinists,. [13] P. and Marchio, D. Stabat, "Heat-and-mass transfers modelled for rotary desiccant dehumidifiers," Applied Energy, vol. 85, no. 2-3, pp , 08. [14] SRCC. (09, Sep.) Solar collector certification and rating. [Online]. [15] SenterNovem, "Cijfers en tabellen 07," SenterNovem, 07. [] dr. ir. A.W.M. van Schijndel. Sustainable building and systems modelling 7Y700. [Online]. [17] Rudi Santbergen, "Optinal model for solar cells and annual yield model for PVT system," WET [] TS and Chen, CJ and Ma, Q. and Xiong, ZQ Wang RZ and Ge, "Solar sorption cooling systems for residential applications: Options and guidelines," International Journal of Refrigeration, vol., no. 5, pp , 09. [19] Jeroen Rietkerk, "Energiebesparkende installatiecomponenten in de praktijk," Technische Universiteit Eindhoven, Eindhoven, 07. [] ASHRAE 08 chapter 25 AIR-TO-AIR ENERGY RECOVERY,. [21] ASHRAE 09 chapter 1 psychrometrics,. [] R. and Seals, R. and Ineichen, P. and Stewart, R. and Menicucci, D. Perez, "A new simplified

47 version of the Perez diffuse irradiance model for tilted surfaces," Solar Energy, vol. 39, no. 3, pp , [23] P.E. Arthur A. Bell jr., HVAC equations data and rules of thumb, 2nd ed., McGraw-Hill professional, Ed., 07. [] S. and Hu, Y.F. Wu J.Y. and Li, "Study on cyclic characteristics of the solar-powered adsorption cooling system," Science in China Series E: Technological Sciences, vol. 52, no. 6, pp , 09. [25] DWA Installatie- en energieadvies, "Meet- en evaluatierapport energiesysteem met zonnecollectoren ten behoeve van DEC-systeem en ruimteverwarming," DWA Installatie- en energieadvies, Bodegraven, 00. [] G. and Henning, H.M. and INFANTE FERREIRA, C.A. and Podesser, E. and Wang, L. and Wiemken, E. Balaras C.A. and Grossman, "Solar air conditioning in Europe-: an overview," Renewable & sustainable energy review, vol. 11, no. 2, pp , 07. [27] CHAPTER 25 AIR-TO-AIR ENERGY RECOVERY 08 ashrea,. [] ASHRAE, "Psychrometrics," in ASHRAE Handbook Fundamentals., 09, p. Chapter 1. [29] ASHRAE, "Fans," in ASHRAE Handbook HVAC Systems and Equipment., 08, p. Chapter. [] S. Alizadeh, "Performance of a solar liquid desiccant air conditioner--an experimental and theoretical approach," Solar Energy, vol. 82, no. 6, pp , 08. [31] TESS library for TRNSYS type 642,. [] "Objective methodology for simple calculation of the energy delivery of (small) Solar Thermal systems," European Solar Thermal Industry Federation,

48 Desiccant Evaporative Cooling Optimal strategy for cooling in a Dutch climate - Appendices - Date: July 10 Version: Final report

49

50 Desiccant Evaporative Cooling Optimal strategy for cooling in a Dutch climate - Appendices - Document title: Program: Author: Desiccant Evaporative Cooling Optimal strategy for cooling in a Dutch climate Eindhoven University of Technology Master program Sustainable Energy technology Specialization: Sustainable Energy in the Built Environment Ralph van Oorschot Student ID: Committee members: prof. ir. P.G.S. Rutten Architecture Building and Planning dr.ir. M.G.L.C. Loomans Architecture Building and Planning dr.ir. A.W.M. van Schijndel Architecture Building and Planning dr.ir. H.P. van Kemenade Mechanical Engineering Graduation company: Eindhoven University of Technology Status: Final report Date: July 10

51

52 CONTENTS APPENDIX I: Theory behind thermal cooling... 3 APPENDIX II: Different solar cooling methods... 5 APPENDIX III: Comparison between different solar cooling systems... 9 APPENDIX IV: Choice of modeling software APPENDIX V: Modeling APPENDIX VI: Available control strategies... APPENDIX VII: Fixed parameters for analysis APPENDIX VIII: Operating mode evaluation APPENDIX IX: Analysis of the DEC system + load APPENDIX X: Cooling and Dehumidification potential APPENDIX XI: Climate data APPENDIX XII: HAMbase APPENDIX XIII: Solar collector APPENDIX XIV: Conventional system Appendix - Page 1

53 Appendix - Page 2

54 APPENDIX I: THEORY BEHIND THERMAL COOLING In this appendix, the basic theory behind thermal cooling will be described. Thermal cooling system can be simplified to the energy flows as in Figure 1. The different thermal cooling systems may all be characterized by three temperature levels: T H High temperature level, at which the driving temperature of the process is provided. T C Cold temperature level, at which the cooling process is operated. T M Medium temperature level, which is the temperature of the heat rejected from the chilling process and the driving heat. In the basic process, Q cold is the heat absorbed, or the useful cooling in the air-conditioning system. Q heat is the heat to drive the process, in this case from the solar collector or storage buffer. Q reject is the sum of Q cold and Q heat which has to be removed at a medium temperature level. Figure 1: Simplified view of a thermal cooling system The efficiency of thermal driven cooling is given in Coefficient of Performance (COP), defined as the fraction of the heat rejected from the cold side and the required driving heat. The COP ide al for a heating and cooling process can be calculated as in ( 1 ) and ( 2 ). COP ideal Heating = Q H = T H ( 1 ) Q H Q C T H T C COP ideal Cooling = Q C = T C ( 2 ) Q H Q C T H T C Assuming that the ideal cooling process a combination is of COP ideal Heating from T H T M and the COP ideal Cooling from T C T M, the theoretical maximum efficiency can be can be calculated as in ( 3 ). [1] COP ideal = T H T H T M T C T M T C = T C T H T H T M T M T C ( 3 ) In a real case scenario the COP can be calculated by dividing the cooling power over the driving energy. This is the absorbed solar energy in case of a solar cooler. COP = Q C Q H ( 4 ) The losses of the solar collector is not taken into account in this calcution. The solar collectors cannot absorb all the radiation on the panel. Generally only -40% is absorbed. In most cases the COP is calculated without taking these losses into account. Another performance indicator for solar thermal collectors is the ratio of electric energy used in relation to the provided cooling power. The formula to calculate this ratio is given in ( 5 ). COP e = Q c Q e ( 5 ) Appendix - Page 3

55 W electric can be defined in two ways: Electrical energy that is put into the system. Total energy that is used to generate the electrical energy, including all losses such as transport. Appendix - Page 4

56 APPENDIX II: DIFFERENT SOLAR COOLING METHODS There are four different kinds of heat transformation processes available: Absorption cooling Closed cycle, liquid sorbents. Adsorption cooling Closed cycle, solid sorbents. Solid desiccant evaporative cooling Open cycle, solid sorbents. Liquid desiccant cooling Open cycle, liquid sorbents. The principle behind these cooling techniques can be found in the next chapters, except for the Solid desiccant evaporative cooling system which can be found in main report. Compression cooling powered by PV panels is also added to be able to make a better comparison. 1.1 ABSORPTION COOLING Absorption cooling systems are a closed loop, liquid sorbent type. There are two different types of absorption systems commercially available, the water / lithium-bromide (H 2 O/LiBr) and ammonia / water (NH 3 /H 2 O) systems. The principle is the same, they only use different liquids as refrigerants and absorber. The LiBr/H2O system uses lithium bromide as the absorber and water as the refrigerant. The ammonia-water system uses water as the absorber and ammonia as the refrigerant. Both are built up as in Figure 2, with the following components: A generator, condenser, evaporator and absorber. 3 4 High pressure Low pressure 2 1 Figure 2: Graphical representation of an absorption cooler The system is connected to three in- or outputs. Driving heat Hot water warmed up through a solar collector, which is the driving force of the process. Cooling water This is heated water used to disperse the heat from the complete process. A wet cooling tower is commonly used to transfer that energy to the surroundings Chilled water Cooled water that can be used for cooling. The cooling process can be divided in four steps: 1) The cooling is based on the evaporation of the refrigerant in the evaporator at a low pressure. The evaporation of the refrigerant consumes energy which provides the cooling. 2) The vaporized refrigerant is absorbed by the absorber liquid. This process is cooled to make it more efficient. 3) The solution of refrigerant and absorber is pumped at high pressure to the generator. By applying driving heat, the solution is regenerated to a refrigerant as a vapour and absorber as a liquid. The absorber circulates through an expansion valve back into the absorber. 4) The refrigerant leaving the generator condenses in the condenser through the application of cooling water. It circulated through an expansion valve again into the evaporator. The absorption system can be built up as single or double cycle. In the double cycle, there are two generators and condensers, one at a low and one at a high temperature level. The COP can be Appendix - Page 5

57 improved by making use of these two steps. However, the driving temperatures are also higher which makes it less suitable for use in combination with solar thermal energy. An example of the different COP values for these systems at different driving temperatures is shown in Figure 3. Figure 3: COP as function of the heat supply temperature [1] 1.2 ADSORPTION COOLING Adsorption cooling systems are a closed loop, solid sorbent type. There are two different types of systems which make of use this process: Water / silica gel (or Zeolith) and ammonia / salt systems. The water / silica gel type is most used commercially, but both systems work generally with the same principle. 3 The system consists of four chambers: two adsorber / desorber chambers, an evaporator and a condenser. All four chambers are operated at nearly a full vacuum. The system is connected to three in- or 4 outputs. Driving heat Hot water warmed up through a solar collector Cooling water Heated water used to disperse the heat from the complete process. A wet cooling tower is commonly used to transfer that energy to the surroundings. Chilled water Cooled water that can be used for cooling. Figure 4: Graphical representation of an adsorption cooler The system cycles the chamber 1 and 2 between adsorbing and desorbing. In case of Figure 4, chamber 1 is desorbing and chamber 2 is adsorbing. Due to the low pressure, the refrigerant (water) in the evaporator is transferred into the gas phase by taking up the heat from the chilled water, which generates the cooling effect. The sorption material in chamber 2 is adsorbing the refrigerant vapour. Appendix - Page 6

58 At the same time chamber 1 is regenerated. The refrigerant vapour is being heated and desorbed from the sorbent and being condensated by cooling water in the condenser. The condensated refrigerant is recycled to the bottom of the machine where it is reused. When the sorption material in chamber 2 saturated and the sorption material in chamber 1 is dry, the machine automatically reverses the function of the two rooms. The positions of the valves are changed and the cooling water and hot water are reversed in chamber 1 and LIQUID DESICCANT COOLING Liquid desiccant cooling is an open system with a liquid sorbent type. The cooling principle is the same as the DEC system. The dehumidification is based on the desiccant s liquid strong affinity to water. The most commonly used desiccant liquids are aqueous solutions of lithium chloride. The system is connected to four in- or outputs. Driving heat Hot water warmed up with a solar collector, connected to the heater. Cooling air The warmed room air can used to disperse the heat and regenerate the liquid desiccant. This heated air is blown to the surroundings. Cooling water - Heated water used to disperse the heat from the complete process. A wet cooling tower can be used to transfer that energy to the surroundings Chilled air Cool, dry air is blown from this system into the room. Process air is dehumidified by the concentrated liquid desiccant solution in the absorber, this is done by blowing the process air through the liquid desiccant. The strong desiccant solution absorbs the water in the air and becomes diluted. This is shown at the left side of Figure 5. To improve this process, it can be cooled with cooling water. Extra cooling can be provided by adding a direct evaporation step afterwards. At the right side the diluted solution is heated using solar heat and fed into the regenerator. The air blown through the regenerator absorbs the water in the diluted solution. Figure 5: Graphical representation of a liquid desiccant system [2] An advantage of this system is that the regenerated solution can be stored in a reservoir for times when extra cooling power is required. Appendix - Page 7

59 1.4 COMPRESSION COOLING POWERED BY PHOTOVOLTAIC SOLAR PANELS Although the conversion of electricity by photovoltaic panels to drive a classical vapour compression cycle is a feasible concept, it will most likely not be used in practice. The reason is that developed countries have a well-developed electricity grid and the maximum efficiency of these panels is achieved by feeding the produced electricity into the grid. In the following calculation is assumed that there is no local electricity storage, the produced energy is directly fed into the grid and when bought back for the same price when required. The COP of the vapour compression cooling is dependent on the size of the system, the COP of large centrifugal compressors can reach up 8, but small reciprocating compressors have a COP about 2 to 4. Table 1: Assumptions made for compressor cooling powered by PV panels Parameter Value Yearly irradiation in NL 1150 [kwh/m 2 ] Peak irradiation in NL 1000 [W/m 2 ] Efficiency PV panels 15 [%] Price PV (+inverters) 500 [ /m 2 ] COP compressor cooler 3 [-] Price compressor cooler 500 [ /kw] 1 kw cooling requires 333W, assuming that the cooling period is 3 months for 8 hours a day, the energy required per year is 3 monts 4 weeks 7 days 8 ours 333 W = 2kW. In that case 1.5m 2 of solar panels are required to provide 1kW cooling. Therefore the total costs are 1250 [ /kw] cooling power. Appendix - Page 8

60 APPENDIX III: COMPARISON BETWEEN DIFFERENT SOLAR COOLING SYSTEMS The four different types of solar cooling systems have their specific advantages and disadvantages. The systems are compared with a state of the art PV powered compression cooling. In the last sub-chapter an overview of the installed systems in Europe is given with their specifications is. 1.1 COMPARISON In Table 2, a comparison between literature data of the most important specifications of solar cooling systems is made. Cooling capacity [kw] Invalid source specified. Driving temperature [⁰C] [1] Invalid source specified. Table 2: Overview different specifications of solar cooling systems compressor cooling powered by PV panels Absorption Cooling (single cycle) Few <100 Many >100 Adsorption Cooling Solid Desiccant Evaporative Cooling (Air flow: m 3 /h) Liquid Desiccant Cooling 0 (Air flow: m 3 /h) COP 1 [-] [1] Electrical COP 2 [-]Invalid source specified. Invalid source specified. Invalid source specified Collector area [m 2 /kw] [1] Initial Cost [ /kw] Invalid source specified. Collector technology Single or multi crystalline PV panels. Flat place, Evacuated tubes, Optical concentration Flat plate, Evacuated tubes Flat plate collectors, Evacuated subes, Solar air collectors In Table 3, the most important advantages and disadvantages of the different systems are given. Flat plate collectors, Solar air collectors 1 COP based on total energy consumption, thermal energy as well as electrical energy. 2 COP based only on electrical energy consumption. Appendix - Page 9

61 Table 3: Advantages and disadvantages of the different systems [1][3][4][5][6] Advantages Disadvantages Compressor High efficiency cooler Uses chemical refrigerant cooler Proven technology Not likely to make a large price drop Absorption Cheap to produce Contains toxic materials cooling Low COP at low thermal energy temperatures Adsporption cooling Long life expectancy (no crystallization or corrosion) Low conductivity of silica gel, which results in large volume of Low maintenance the chiller Cooling water tower required Solid DEC No cooling water tower required Performance is very dependent Dehumidification possible on the climate (humidity) Low maintenance Runs at atmospheric pressure Liquid DEC Regenerated liquid can be used as a buffer Performance is very dependent on the climate (humidity) Dehumidification possible Runs as atmospheric pressure 1.2 INSTALLED SYSTEMS IN EUROPE In 06 there are about 70 solar cooling systems installed in Europe. Most of them were realized in Germany and Spain, see Figure 6. Figure 6: Overview of the installed systems in Europe 06 [1] The total installed cooling power is about 6.3 MW, with a total collector size of 17500m 2. As shown in Figure 7, most installed systems are absorption chillers. The least installed systems are the liquid desiccant systems, probably because this technology is still the least developed. When looking at cooling capacity and collector area the distribution looks somewhat different, because the installed adsorption systems generally have a large cooling capacity. Appendix - Page 10

62 Figure 7: Distribution of systems in terms of number of systems, cooling capacity and installed collector area [1] The type of solar collectors used in these systems is given in Table 4 below. Table 4: Number of installations with a certain type of solar collector Invalid source specified. Absorption Adsorption Solid DEC Liquid DEC Flat plate collectors Evacuated thermal collectors Optical concentrated collectors Solar air collectors The COP value for the different realized systems is given in Figure 8. A trend can be found, the COP increases with higher driving temperatures. Figure 8: COP as function of the driving heat [5] Appendix - Page 11

63 1.3 CONCLUSION Solar thermal cooling is already successfully used for cooling in buildings, especially in countries with a climate that requires a high cooling potential. Absorption cooling is the most commonly used technique for thermal cooling, most probably because it is the longest available and has the lowest investment costs. Liquid desiccant cooling has some advantages and is very promising, but still needs some further development. The solid DEC systems are an average performer. Appendix - Page 12

64 APPENDIX IV: CHOICE OF MODELING SOFTWARE The simulation of a solar DEC system is a complex task, because of the many different components and changing conditions. It is close to impossible to make those calculations by hand, therefore a simulation software tool is required. There is a large variety of different simulation software, with all their specific advantages and disadvantages. A set of requirements is made, to find the optimal simulation software for this task, based on these requirements a simulation software tool is chosen. The following points are essential for the simulation: Free available or licensed at the TU/e Easy to adapt / flexible Implementation of control strategy Able to simulate the following: o Solar irradiation o Solar thermal panels o Thermal water storage buffer o Desiccant wheel o Heat recovery wheel o Humidifier o Fan o Standard office room Many simulation software packages do not agree with the first point. By looking at the licensed software of the TU/e and simulation software used in DEC simulation articles the following simulation software packages qualify: TRNSYS (licensed at the TU/e) Matlab/Simulink (licensed at the TU/e) ESP-r (Free available and open source) SimSPARK (Free available and open source) TRNSYS and Matlab Simulink suit the requirements the best. The TESS library for TRNSYS is commonly used in articles and has all the required components. Matlab Simulink is chosen as simulation software because of there is more knowledge and experience available at the TU/e. TRNSYS could be used as an alternative. Appendix - Page 13

65 APPENDIX V: MODELING To be able to analyze and improve the DEC system a computer simulation is required. There is not a complete simulation model of this system available. The DEC system consists of a couple different air handling units, which all have to be modeled to make a simulation. Each component is modeled and verified separately before combining then together to make a complete model. In the next sub-chapters, models of all the required components are evaluated in the same way: 1. Short introduction of the component and working principle 2. Mathematical model used for simulation 3. Matlab Simulink model 4. Assumptions used for the model 5. Verification of the model To be able to connect the different models in the complete simulation, a standard for defining inand outlet state should be made. Four variables are chosen, in which all conditions of the air flow are fixed and in such a way that conversions to other units are the least required and are not processor intensive. The variables used are given in Table 5, these four variables are multiplexed in Simulink to a single connection. Because of this standard definition, conversions between units are necessary. The most common used conversions are given in chapter 1.8. Table 5: Air flow in- and outlet conditions Variable Description Unit t Dry air temperature [ C] W Humidity ratio [g water /kg air ] m Mass flow of dry air per second [kg da /s] p Pressure [Pa] Appendix - Page 14

66 W [kg/kg] Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot 1.1 SORPTION_WHEEL.MDL The sorption wheel(or desiccant dehumidification wheel) is a component that removes moisture from the air. A common method for removing moisture is by cooling air below its dew point. A sorption wheel uses a different method. It relies on the ability of hygroscopic materials (such as Silica gel or Zeolith) to adsorb water onto their surfaces. The water from the (moist) process air adsorbs onto the surface of the sorption wheel. The sorption material rotates slowly and when saturated it is rotated to another section where the desiccant material is being regenerated. This is done by the air flow of the regeneration air. A graphical representation of the sorption wheel including the air flows is shown in Figure Process air inlet 2. Process air outlet 3. Regeneration air inlet 4. Regeneration air outlet Figure 9: Graphical representation of a sorption wheel Mathematical model In an ideal situation the sorption wheel dries the process air and adds the moisture to the regeneration air stream isenthalpically. In reality, the sorption and desorption in processes are not isenthalpic i.e. because moisture, temperature and enthalpy travels in waves through the sorption material. Howe and Jurinak developed a theory to calculate outlet states. [7] F1 R 4 F1 D 0.02 F1 P F2 P F2 D 2 2* F2 R T [K] Figure 10: Potential functions in a psychometric chart for the determination of the state of outlet process air The process paths within the sorption wheel can be seen in Figure 10. The numbers at the intersections of the blue lines indicate entrance and exit conditions in the dehumidifier. Temperature and humidity ratio is known at point 1, by using formula ( 6 ), the constant F1 P can be computed and the blue line connecting 1-2 is fixed. This can also be done for line 3-4, because point 3 is fixed, and therefore F1 R can be computed. The other two lines, connecting 2-3 (F2 P ) and 1-4 (F2 R ) can be calculated in the same way with formula ( 7 ). Appendix - Page 15

67 F1 P/R = 65 T W0.86 ( 6 ) F2 P/R = T W ( 7 ) Because of non-idealities in the system the outlet state 2 can in reality not be achieved, it will shift to point 2*. Two effectiveness values (ε1 and ε1) are used to calculate the actual outlet state (2*). The dashed red lines can be calculated based on a new F1 D and F2 D value which can be determined by formula ( 8 ) and ( 9 ). ε F1 = F1 D F1 P F1 R F1 P ( 8 ) ε F2 = F2 D F2 P F2 R F2 P ( 9 ) The intersection of the two lines indicates the actual outlet condition at the process side. The outlet conditions at the regeneration side can easily be calculated based on conservation of mass and energy Matlab Simulink model The sorption wheel can is can operate at different rotational speeds. High rotational speeds have a high moisture transport and lower rotational speeds are used for enthalpy exchange. This model has two operation modes: active dehumidification and enthalpy exchange. The wheel could also be in a stationary position, in that case there is no energy or moisture exchange. Unfortunately, the mathematical model as described above does not take the rotational speed into account. But according to P. Stabat [8], the effectiveness is a function of the rotational speed. Therefore this component can operate with two different effectiveness values, depending on the operation mode selected. To have a good overview, all the components of the desiccant dehumidifier wheel are masked into one block with five adaptable parameters, given in Table 6. Most of the calculations of the Simulink model are made in a single embedded Matlab file. Only the choice of the effectiveness value according the operation mode and pressure drop are calculated outside that Matlab file. The embedded Matlab file starts with the calculation of F1P, F1R, F2P and F2R based on formula ( 1 ) and ( 7 ). With those values a formula for the four blue lines as in Figure 10 can be made. Based on the chosen effectiveness values and using formula ( 8 ) and ( 9 ), F1D and F2D can be calculated and the formulas for the dashed red lines can be obtained. An iteration based on Newton Raphson method is used to find intersection of those lines. The Newton Raphson method is chosen over a regular solve function, because this method is far less processor intensive This intersection fixes the outlet condition at the process side. Based on conservation of mass, the humidity at the outlet of the regeneration side is calculated, see formula ( 10 ). m reg W 4 + m proc W 2 = m proc W 1 + m reg W 3 ( 10 ) The outlet temperature at the regeneration side can be calculated based on conservation of energy. Appendix - Page

68 m sys h 1 + m reg h 3 = m sys h 2 + m reg h 4 ( 11 ) An overview of the different in and outputs of this model is given in Table 6 below. Table 6: Overview in- and outputs of the desiccant dehumidification wheel model Type Variable Description Unit Input Flow_proc Flow_reg Op_Mode Input air conditions process side (see Table 5) Input air conditions regeneration side (see Table 5) Operation mode: [ ] [ ] [1,2,3] 1 = Active dehumidification mode 2 = Enthalpy exchange mode 3 = Off Output Flow_proc_out Output air conditions process side (see Table 5) [ ] Parameters Flow_reg_out P_drop Ef1a Ef2a Ef1e Ef2e Output air conditions regeneration side (see Table 5) Pressure drop over the wheel Effectiveness 1 in active dehumidification mode Effectiveness 2 in active dehumidification mode Effectiveness 1 in enthalpy exchange mode Effectiveness 2 in enthalpy exchange mode [ ] [Pa] [-] [-] [-] [-] Assumptions The outlet conditions at the process side are calculated without taking differences between process and regeneration air flow rates into account. The air flow rates are only used for calculating the outlet condition at the regeneration side. The model is validated with equal air flows for the process and regeneration sides, therefore large differences in air flow between process and regeneration can affect the validity of the model. Thermal inertia of the components is neglected. The model assumes moist air as input at the regeneration side, it cannot cope with saturated water or steam. The model is not capacity limited, meaning that the dimension and airflow of the model should be equal to the component used for verification Verification A simulation program from Klingenburg (which is a manufacture of these sorption wheels) is used to verify the model and determine the effectiveness values ε1 and ε2 for the different operating modes. The SECO 1750/ model is used, which can operate at 10rpm for enthalpy exchange and at rpm for active dehumidification. The effectiveness values are calibrated using the model from Klingenburg. The range in which the model from Klingenburg works is very limited and the absolute humidity of the process and regeneration side should be close to each other, therefore only a limited amount of verification points were available. The results for active dehumidification mode are given in Table 7 below. Values used for effectiveness are ε1 = 0.13 and ε2 = 0.69 Appendix - Page 17

69 Table 7: Mismatch between SECO model and Matlab model in active dehumidification mode Entrance conditions SECO Simulink model Process air Regeneration air Outlet process air Outlet process air T [ C] W T [ C] W T [ C] W T [ C] W Mismatch [%] 10, ,53 39,7 5,21 38,86 5,238 2,12-0, , ,74 43,6 7,93 43,19 8,033 0,94-1, 13, ,69 48,9 8, 48,77 8,362 0,27-0, , ,78 52,3 13,04 52,36 13,27-0,11-1, ,5 70, ,36 55,23 19,87-0,42-2, ,5 65,62 55,4,6 54,96,56 0,79 0, 40 23, ,46 50,8, 50,69,52 0, -1, , ,13 48,1 21,06 47,96 21,29 0,29-1, , ,53 47,3,79 46,94,72 0,76 0, 13, ,74 46,5 8,91 46,33 9,008 0,37-1,09 13,3 60,9 42,9 10,14 42,95 10,39-0,12-2,41 13, , ,76 10,12 0,57-1,19 13, ,57 41,1 9,89 40,67 9,887 1,05 0,03 Average absolute mismatch: 0,62 1,09 The results for enthalpy exchange mode are given in Table 8 below. Values used for effectiveness are ε1 = 0.9 and ε2 = 0.9 Table 8: Mismatch between SECO model and Matlab model in enthalpy exchange mode Entrance conditions SECO Simulink model Process air Regeneration air Outlet process air Outlet process air T [ C] W T [ C] W T [ C] W T [ C] W Mismatch [%] 10, , ,27 60,38 12,08-0,63 1, , ,74 60,6 15,54 60,94 15,27-0,56 1,74 13, ,69 65,6 15,43 65,94 15, -0,52 0, , ,78 66,2 21, 66,49 21,23-0,44 0, ,5 70,08 66,8 29,38 67,02 29,29-0,33 0, ,5 65,62 62,2,94 62,49,83-0,47 0, , ,46 57,8 25, 58 25,21-0,35 0, , ,13 53,3,95 53,5,94-0,38 0, , ,53 48,9 19,98 49,01 19,9-0, 0,40 13, ,74 61,3 15,47 61,46 15,36-0, 0,71 13,3 60,9 56,7,29 57,02,21-0,56 0,44 13, ,84 52,2 14,67 52,47 14,61-0,52 0,41 13, ,57 47,7 11,77 47,98 11,7-0,59 0,59 Average absolute mismatch: 0,45 0,64 The average mismatch these two components is between 0.45% and 1.09%, maximum mismatch is 2,57%. These differences probably occur because of the different calculation methods. Mass and energy is conserved at all times and therefore small variations in outcome are allowed. Appendix - Page

70 1.2 FAN.MDL fan is an electrical powered device that creates an air flow. All the components in the DEC system have a resistance, or pressure drop. The fan produces a pressure increase such that there is an air flow through the system Mathematical model The power consumption of the fan in an ideal situation is defined as formula ( 12 ). q e = p V μ motor ( 12 ) Where q e is the power consumption of the motor in Watt, p the pressure drop, V the air flow rate in m 3 /s and μ motor the efficiency of the motor between 0 and 1, where 1 means that the motor has an efficiency of 100%. The amount of energy transferred from the motor to the air consists of two parts: the energy that is consumed by the air to overcome the pressure drop and the losses of the motor. Depending on the location of the motor, a part of these losses are also transferred to the air flow. The total amount of energy transferred to the air flow (Q air ) can be calculated with formula ( 13 ). q air = μ motor + 1 μ motor f motorloss q e ( 13 ) Where f motorloss indicates how much of those losses in the fan are transferred to the air. [9][7] Matlab Simulink model The Simulink model for the fan is relatively simple and is therefore made out of Simulink blocks. Based on the entrance conditions, the specific volume and total volume flow is calculated. p is the difference between inlet air pressure and required air pressure. By making use of formula ( 12 ) the energy consumed by the motor can be calculated. Formula ( 13 ) is used to calculate the total energy added to the air flow. Bases on enthalpy of the input air flow and constant humidity ratio, formula ( 14 ) can be used to calculate the enthalpy of the outlet air. This value can be converted to determine the output air conditions. out = in + q air m air ( 14 ) An overview of the different in and outputs of this model is given in Table 9 below. Table 9: Overview in- and outputs of the fan model Type Variable Description Unit Input Flow p_required Input air conditions process side (see Table 5) The required output pressure or outside pressure [ ] [Pa] Output Flow_out P_consumed Output air conditions process side (see Table 5) Energy consumption of the fan [ ] [W] Parameters Eff Fan efficiency, value between 0 and 1, where 1 is an [-] Appendix - Page 19

71 Motor_loss Assumptions efficiency of 100%. Factor that indicates how much of the motor losses is transferred to the air flow. Value between 0 and 1, where 1 is that all losses are transferred to the air flow. [-] μ motor and f motorloss are constant values and not dependent on the flow rate or motor power consumption. Fan power and dimension are not limited, the required pressure difference is always met. Thermal inertia and delays due to inertia of mass are not taken into account in this model Verification The motor efficiency is determined by the specifications of a fan from Verhulst luchtbehandeling, type ER [10] The data of two operating states are given in Table 10. The efficiency is calculated based on formula ( 12 ) and ( 13 ). Table 10: Fan efficiency calculations for the ER fan Specifications Q [m 3 /s] Δp [Pa] Fan Power [kw] Calculated Effiency The efficiency is averaged and estimated to be Another check is the conservation of energy, which is done for different input values. Results in Table 11 show that these differences are so small that they can be neglected. Table 11: Energy conservation test of the fan model Input output Energy Δ p T W m Fan Motor T [ C ] W P [W] generation [Pa] [ C] [kg/s] eff. Loss [%] , , , , ,819 0,6042 0, ,819 0, , ,819 0,6042 0,7 21, , ,819 0,6042 0,7 11, ,819 0,6042 0,7 21, , ,819 0,6042 0,7 31, , ,819 0,6042 0,7 41, , ,819 0,6042 0,7 41, , ,819 0,6042 0,7, , ,819 0,6042 0,7 40, ,0002 Appendix - Page

72 1.3 SOLAR_THERMAL_COLLECTOR.MDL A solar collector is designed to collect thermal energy, transmitted by the sun. The solar panel is optimized to effectively transfer the solar energy to the water flowing though the collector Mathematical model The mathematical model can be separated in two different steps. The first step is the calculation of the solar irradiation on the collector based on irradiation, the location of the sun and orientation of the panel. The second step is the simulation of the solar energy absorption in the solar collector. A Matlab file is used to calculate the solar irradiation on the solar collector.[11] The solar collector mode is based on an article of R. Perez. [12] The energy gain from the solar irradiation is calculated with formula ( 15 ), where ε the efficiency of the panel is, G the solar irradiation [W/m 2 ] and A the area of solar panels [m 2 ]. q t = ε G A ( 15 ) The efficiency is a dependent on the type of panel, solar irradiation, ambient- and panel temperature. This can be calculated using a 2nd order efficiency calculation. ε = n o a 1 T m T a G a 2 T m T a 2 G ( ) n o, a 1 and a 2 are solar collector efficiency parameters, which are dependent on the type of panel. T a is the ambient temperature and T m the mean temperature of the solar collector.[13] Matlab Simulink model The Simulink model is build up the same way as the mathematical model, it consist of two Matlab files, one file for calculation of irradiation and one file to calculate the water temperature increase based on the solar irradiation. The Matlab file from A.W.M. van Schijndel could almost directly be used to calculate the solar irradiation on the solar panel. Some minor changes to the in- and outputs are made. The second Matlab file calculated the water temperature increase based on the calculated solar irradiation. This is done by making use of formula ( 15 ) and ( ). All parameters are known except the mean solar panel temperature. The temperature could be estimated by taking the average over the in- and output water temperature. Unfortunately the output water temperature is a function of q t and is still unknown. This is solved by making use of the last known water output temperature and a making use of a memory function, see Figure 11. This value will not differ much from actual water output temperature, because of the high inertia of the water flow. Figure 11: Use of the memory function in Simulink In times of low or none solar irradiation, there is a possibility that negative efficiencies occur. In that case the solar panel loses energy. To prevent this, a function checks for negative efficiencies and converts it back to zero. This is a simplified control which simulates a pump shut down. After calculating q t the total temperature increase of water can be calculated with formula ( 17 ). q t = m c T ( 17 ) Appendix - Page 21

73 Table 12: Overview in- and outputs of the fan model Type Variable Description Unit Input Climate T_in m Multiplexed climate data (Diffuse solar on the horizontal, External dry bulb temperature and Direct normal solar intensity) Input water temperature Water flow speed [ ] [ C] [kg/s] Output T_out Output water temperature [ C] Parameters Panel_size Az Inc n a1 a2 Effective solar collector panel size Azimuth in degrees, 0 = south Inclination in degrees, 0 = horizontal Zero loss efficiency for global or total radiation at normal incidence Parameter that describe the temperature-dependent heat loss Parameter that describe the temperature-dependent heat loss [m 2 ] [deg] [deg] [-] Assumptions Mean collector temperature is defined as an average between water inlet and the last known water outlet temperature. The efficiency of the panel is always positive. Therefore the panel cannot have a thermal energy loss. The model assumes an infinite small amount of water in the collector and has therefore no thermal inertia Verification For verification the data from the Bilt at until is used to verify the solar collector. The results are averaged to obtain daily data. These data is compared with SRCC data from the Apricus AP-.[14] A panel with a net size of 2.99m 2 is used with a water flow speed of 0.083kg/s. The data from the SRCC is interpolated to match the solar irradiation of the simulation. Values from the simulation are compared with the interpolated data. Category (T i -T a ) Clear day (23 MJ/m 2 day) Table 13: SRCC data of the Apricus AP- Mildly cloudy (17 MJ/m 2 day) Interpolated (19.6MJ/ m 2 day) Simulation data (19.6MJ/ m 2 day) Mismatch C ( C) 42.9 MJ/day.9 MJ/day % D (50 C) 36 MJ/day.2 MJ/day % E (80 C).6 MJ/day.8 MJ/day % There is small mismatch between the simulated data and data given by the SRCC. This mismatch is relatively small and could be caused by the different weather and irradiation profiles used. [-] [-] Appendix - Page

74 1.4 THERMAL_BUFFER.MDL The thermal buffer or energy storage tank is designed to store the thermal energy from the solar collector for later use. In this case a water vessel is used that is connected to the solar collector and the load (heating coil). Mixing of the water should be avoided, the tank operates optimally when is has a good thermal stratification. Having a stratified tank instead of uniform temperature has two advantages. Firstly, the water to the load (extracted at the top) has a relative high temperature, this means more useable energy or less auxiliary heating. Secondly, the water to the collector (extracted at the bottom) has a relative low temperature, which is beneficial for the efficiency of the thermal collector. To load From load To maintain an optimal thermal stratification, variable return inlet height can be used. This is beneficial to prevent mixing and keep the thermal stratification. From collector To collector Figure 12: Thermal energy storage tank model Mathematical model A multi-node model is used in this model. The storage tank is divided into equal segments, where every segment is being characterized by a uniform temperature. With a variable return inlet height, it is assumed that water enters the tank in the node of the best matching temperature. This holds for the return inlet from the load and the collector, because both inlet temperatures can vary. Each node can have five different energy flows, which are all calculated each time step for each node: Energy flow from the solar collector Energy flow to the load Energy flow from up neighbour node Energy flow from down neighbour node Energy losses to environment The five energy flows can be calculated by making use of formula ( ) below. dt i M i C f dt = α im collector C f T collector T i + β i m load C f T load T i +δ i γ i C f T i 1 T i + 1 δ i γ i C f T i T i+1 UA i (T i T env ) ( ) Where: α i = 1. If fluid from heat source enters node i, 0 otherwise. β i = 1. If fluid returning from load enters node i, 0 otherwise. i 1 γ i = m collector α j m load β j j =1 δ i = 1, if γ i > 0 0, if γ i 0 N j =i Matlab Simulink model The used model is based on a Matlab model made by Rudi Santbergen[15], which uses the mathematical model described above. Appendix - Page 23

75 This model is adapted to work in Simulink with variable inputs and time step calculations. The model only assumes a variable inlet for the water from the collector. The water inlet from the load was fixed to the bottom node. The model is adapted to make this variable as well. Auxiliary heating inside the vessel is not used and therefore removed from the calculations. Table 14: In- and outputs of the buffer model Type Variable Description Unit Input Tct Tlt Mc ml Water temperature from the collector to the tank Water temperature from the load to the tank Water mass flow through the collector Water mass flow through the load [ C] [ C] [kg/s] [kg/s] Output Ttc Water temperature from the tank to the collector [ C] Parameters Ttl Ttank Ttank_m Tta K_insu D_insu Col_inlet Load_inlet plot Water temperature from the tank to the load Amount of nodes and initial temperature of each of the nodes Tank size Ambient temperature Heat conduction coefficient of the insulation material Thickness of the insulation material Variable or fixed collector inlet height (0=fixed (to top node) 1=variable) Variable or fixed load inlet height (0=fixed (to bottom node) 1=variable) Plot figure of the temperature profile inside the tank (1=yes) Assumptions Water is used for storage and is always in liquid phase. A complete mixed situation is assumed within each node Verification Every time step, the model from Rudi Santbergen does three different verification checks: Power conservation Energy conservation Inversions in temperature profile [ C] [ C] [kg] [ C] [W/m K] [m] [-] If the calculations do not agree with one of these criteria above, an error message is generated. The model always fulfills the first two criteria. Inversions in the energy profile can occur when fixed inlets are used and in special situations. This is when the inlet from the collector or load changes the temperature of that node above the temperature of the higher neighbour node or below the temperature of the lower neighbour node. The temperature differences between two inversed nodes decrease and eventually eliminate over time. [-] [-] 1.5 ROTARY_HEAT_EXCHANGER.MDL The rotating wheel of the rotary heat exchanger is in most cases composed of thin waved aluminum foil. One half of the wheel is placed in the process air, the other half in the return air flow. The wheel rotates slowly. Air is blown through the wheel and the material absorbs energy at one side and Appendix - Page

76 releases it at the other side. Depending on the material of the wheel, it transfers sensible and/or latent heat. A distinction between three different types of rotors can be made: Condensation rotor: The material of the wheel consists of untreated aluminum. Latent heat recovery will only occur when moisture condensates on the rotor. Hygroscopic rotor: A chemical treatment on the material of the wheel increases the moisture adsorption and therefore improves the latent energy recovery. Sorption rotor: In this case the wheel is coated with a hygroscopic material (such as lithium bromide or silica gel). This ensures moisture transport, even with the absence of moisture condensation. This wheel has still a large sensible heat recovery in comparison with the desiccant dehumidification rotor. In this system a condensation rotor is used, because a minimum of moisture transfer is preferred Mathematical model The model is based on a fixed efficiency for sensible energy transfer, which is based on the temperature difference between the inlet air at both sides and defined as formula ( 19 ), where Φ the sensible energy efficiency is and m min the minimum mass flow (process or return). q sens = Φ m min C air (T return T process ) ( 19 ) The outlet temperatures can be calculated based on enthalpy and humidity values Matlab Simulink model Based on formula ( 19 ) the sensible energy transfer and enthalpy change of both air flows is calculated. The amount of moisture transfer can be calculated based on the assumption that condensation only occurs when the relative outlet humidity is above 95% RH. The amount of moisture transfer is equal to the change in humidity from the inlet state to the 95% RH at outlet temperature. Simulink checks which inlet temperature is the highest. Only at this side there is a possibility of condensation, because the temperature at that side of the wheel will decrease and there is a possibility that humidity exceeds 95% RH at the outlet side. If the relative humidity at the outlet side is below 95% RH, the outlet temperatures are calculated based on the calculated outlet enthalpy values and a constant humidity ratio. Otherwise, a polynomial fit is used to calculate the outlet temperature at 95% RH for the calculated outlet enthalpy value. The absolute humidity at 95% RH is calculated at that outlet temperature. The difference between absolute inlet and outlet humidity is equal to the moisture transfer. The outlet temperature at the other side is calculated based on the new absolute humidity and enthalpy value. This method is based on an example calculation from ASHRAE[9] and is only valid for small amounts of moisture transfer, because the energy content of the condensed water is neglected. Appendix - Page 25

77 Table 15: In- and output variables for the heat exchanger wheel Type Variable Description Unit Input Flow_proc Flow_ret Input process air conditions (see Table 5) Input return air conditions (see Table 5) [-] [-] Output Flow_proc_out Flow_ret_out Output process air conditions (see Table 5) Output return air conditions (see Table 5) [-] [-] Parameters S_eff P_loss Sensible energy transfer efficency Pressure loss over the heat exchanger wheel [-] [Pa] Assumptions The efficiency for sensible energy flow is assumed constant There is only a latent energy flow, when the relative outlet humidity at one side is above 95% RH. The enthalpy of the condensed water is neglected by adding the energy lost through condensation of vapor to the sensible heat lost of the outlet air Verification To verify the proper working of the rotary heat exchanger, the output of the Simulink model is compared with a simulation software program from Klingenburg (which simulates the RRS-P-C /1750-) and a check for conservation of energy and mass is made. In all calculations made, the model conserves its energy and mass. Appendix - Page

78 Table : Verification of the heat exchanger wheel Process Return Process Return Error [%] T in W in T in W in W out W out [C] [C] T out [C] T out [C] T out W out T out W out Simulink 36,7 0 23,3 0 Klingenburg 36,7 0 23,3 0 0,0 0,0 0,0 0, Simulink 53,4 0,6 0 Klingenburg 53,5 0,5 0 0,2 0,0 0,4 0, Simulink 70,1 0 29,9 0 Klingenburg 70,5 0 29,5 0 0,6 0,0 1,3 0, Simulink 36,7 0 23,6 10 Klingenburg 36,8 0 23,4 10 0,3 0,0 0,8 0, Simulink 53,4 0 27,21 10 Klingenburg 53,6 0,6 10 0,4 0,0 2,2 0, Simulink 70,1 0,81 10 Klingenburg 70,7 0 29,8 10 0,9 0,0 3,3 0, Simulink 35,57 0,442 25,41 19,56 Klingenburg 36,8 0,38 25,99 3,5 14,0 1,6 2, Simulink 45,75 2,976 36,09 37,02 Klingenburg 54 3,65,2 33,13,0,6 5,2 10, Simulink 66, 1,442 36,78 38,56 Klingenburg 71,2 1, ,59 7,3,6 2,1 5, Simulink 35,29 10,44 25,41 19,56 Klingenburg 36,7 10,19 25,1 19,12 4,0 2,4 1,2 2, Simulink 45, 12,98 36,09 36,09 Klingenburg 53,8 12,72,6 33,92,8 2,0 4,1 6, Simulink 65,5 11,44 36,78 38,56 Klingenburg 70,9 10, ,76 8,2 5,9 2,1 4, Simulink 36,78 38,56 65,5 11,44 Klingenburg 36 36,76 70,9 10,77 2,1 4,7 8,2 5,9 The results of the Simulink model at low or none moisture transfer rates are comparable with the Klingenburg model. Some small mismatches still exist, most likely because the efficiency for sensible energy flow is not constant in the Klingenburg model. In cases of large latent transfer the model has a relative large mismatch, which is as expected. This is not a problem for the use in a DEC system, because in normal operation there is no potential for condensation. 1.6 HEATING_COIL.MDL The heating coil exchanges heat from one medium to another. In this case it transfers energy from water to air. This is done by flowing air trough coils with a large surface area where air passes by. The large surface area is preferred to optimize the energy transport Mathematical model A simple mathematical model for the heat exchanger is used. The amount of energy transport is based on formula ( ), ( 21 ) and ( ) below. Appendix - Page 27

79 C min = MIN(m water Cp water, m air Cp air ) ( ) q max = C min T wate rin T air in ( 21 ) q actual = εq max ( ) C min is the minimum energy capacitance. Based on that, the ideal energy transport q max can be calculated. An effectiveness factor ε is used to determine the actual energy transport q actual Matlab Simulink model The Simulink model is based on the mathematical model described above. One embedded Matlab file does the actual calculations. To be able to take the effect of moisture in the air into account, the calculations of the air properties is done based on enthalpy values. Water and air outlet temperatures can be determined by formula ( 23 ) and ( ) below. q actual T water out = T water in + ( 23 ) m water Cp water ai rout = ai rin + q actual m air ( ) Assumptions The heat exchanger is considered massless. Energy exchange efficiency is considered constant Verification To check if the model works according to the theory described above a static energy conservation check is done. Simulated values in Simulink are compared with manual calculations. Table 17: Verification of the heat exchanger Input Output t air [ C] W air m air [kg/s] t air [ C] m water [kg/s] T air [ C] T water [ C] q [kw] Simulation 33,98 36,63 14,07 Calculation,06 36,63 14, Simulation 67,97 73,27,14 Calculation 68,14 73,27, Simulation 33,86 36,63 14,07 Calculation,07 36,63 14, Simulation 67,71 73,27,14 Calculation 68,13 73,27, Simulation 33,86 39,33 14,07 Calculation,07 39,33 14, Simulation 67,71 78,65,14 Calculation 68,13 78,65, Simulation 31,53,00 58,52 Calculation 31,71,00 58, Simulation 63,06 52,00 117,00 Calculation 63,41 52,01 117,06 Appendix - Page

80 All calculated values are within 0.63% of the simulated values. Energy conservation is also checked, maximum error between inlet and outlet energy content is 0.012%. 1.7 HUMIDIFIER.MDL A humidifier increases the humidity of the air flowing through it. This is done by pumping air through a nozzle to generate a mist of small water droplets. These droplets evaporate in the air that is flowing through. The evaporation of air consumes energy which is absorbed from the air and thus the air temperature decreases. Water used for humidification should be pre-treated to reduce pollution on the nozzles and other components. A pre-treatment is also necessary to reduce bacterial growth. A reverse osmosis filter is used to filter the water used for humidification Mathematical model The outlet temperature and humidity can be calculated based on formula ( 25 ) below. m da 1 + m w w = m da 2 ( 25 ) Where 1 the inlet enthalpy content is and 2 the outlet enthalpy. The absorbed water m w can be calculated with formula ( ). m w = m da (W 2 W 1 ) ( ) The total water consumption is higher than the water absorbed by the air (m w ), because in reality not all water sprayed through the nozzles is absorbed by the water. The total energy consumption of the high pressure pump used for the reverse osmosis filter can be determined by formula ( 12 ) of the fan model Matlab Simulink model The Simulink model contains an algebraic loop. The loop exists because the outlet temperature is used as an input to calculate the outlet humidity ratio. The outlet humidity is required to calculate the outlet temperature. A simplified overview of this loop is found in Figure 13. Simulink can cope with these kinds of algebraic loops and is able to calculate the outlet temperatures. W 2 Output humidity ratio Humidity setpoint [%] T 1 W 1 Calculate inlet enthalpy Formula ( 25 )and h 1 ( ) h 2 W 1 W 2 Calculate outlet temperature T 2 Figure 13: Simplified overview of the algebraic loop inside the humidifier model After solving the algebraic loop, the amount of absorbed water is known. A polynomial function is made to calculate the total water consumption based on the consumed water and the humidity output level. Appendix - Page 29

81 The total water consumption is equal to the amount of water that passes through the reverse osmosis filter. The energy consumption of that pump can be calculated using formula ( 12 ) of fan model. Table : In- and outputs of the humidifier model Type Variable Description Unit Input Flow_sys SetP Input air conditions (see Table 5) Relative outlet humidity level [-] [%] Output Flow_sys_out H_consump Energy_cons Output air conditions (see Table 5) Total water consumption Energy consumption of the high pressure pump [-] [kg/s] [W] Parameters max_added_humid P_drop Motor_eff P_osmosis Maximum added humidification per kg dry air Pressure drop over the humidifier High pressure pump efficiency Reverse osmosis filter entrance pressure [Pa] [-] [Pa] Assumptions Humidity set point is always achieved Humidifier works adiabatic Humidifier has no response time The pump has a constant efficiency and outlet pressure Verification A simulation program from Klingenburg is used to verify the model and to determine the missing variables. This simulation program simulates the KB type humidifiers from Klingenburg. According the specifications, the pressure drop over the humidifier is between 8-10 Pa, depending on the model. An average of 9 Pa is used. The motor efficiency is determined based on formula ( 12 ) and calculations made by simulation model from Klingenburg. Table 19: Calculated motor efficiencies at air inlet of C and % humidity Outlet humidification level [%] Pressure [bar] Water consumption [kg/h] Energy consumption [kw] calculated efficiency ,3 0, 0, ,75 0,19 0, ,77 0,15 0, ,92 0, 0, ,44 0,12 0,8444 Table : Calculated motor efficiencies at air inlet of 50 C and % humidity Outlet humidification level [%] Pressure [bar] Water consumption [kg/h] Appendix - Page Energy consumption [kw] calculated efficiency ,14 0,38 0, ,73 0, 0, ,61 0,3 0,8574

82 Consumption factor [-] Sustainable Energy Technology: Research Graduation Project Ralph van Oorschot The calculated efficiency values determined from Table 19 and Table are averaged and the motor efficiency is assumed to be 0.8. The Klingenburg model is also used to determine a function that calculates a factor between absorbed and total consumed water. The output humidity is of major influence to this factor. The water consumption of 50 different simulations is calculated with the Klingenburg model. Input temperature differs between 15 and 35 degrees and humidity levels from 10% to 50%. A polynomial fit for this consumption factor is made, which is shown in Figure 14. 2,2 2 1,8 consumption factor 3rd order polynomal y = 5E-06x 3-0,0008x 2 + 0,0447x + 0,5672 1,6 1,4 1, Output humidity level [%] Figure 14: Consumption factor as function of the output humidity level The last variable to set is the reverse osmosis entrance pressure. According the specifications is should be between 110 and 1 bar, therefore the average of 1 bar is chosen. The differences between Klingenburg and Simulink are shown in Table 21. Appendix - Page 31

83 Table 21: Verification of the heat exchanger t in [ C] Input values Output klingenburg model Output Simulink model Absolute mismatch W in H2O H2O [g/kg W out t out W out cons. q e t out W out cons. P W ] [%] [ C] [kg/h] [kw] [ C] [kg/h] [kw] T [%] [%] H cons [%] P [%] 5 61,00 15,70 6,74 14, 0,05 15,68 6,79 15,47 0,06 0,11 0,76 8,36 27, ,40 14,00 7,40 21, 0,07 14,08 7,46,35 0,09 0,59 0,79 5,44 31, ,80 12, 8,09,41 0,11 12,42 8,15 33,64 0,14 0,98 0,78 3,80 25, ,70,00 9,61 14, 0,05,04 9,65,29 0,07 0,25 0,44 14,05 33, ,40 15,00 10,03 21,21 0,07 15,03 10,07 23, 0,10 0, 0,43 9,36 36, ,60 19,80 7,10,96 0,08 19,75 7,17,12 0,07 0, 1,03 6,84 6, ,60 17,60 7,96 25,44 0,12 17,65 8,04,02 0,11 0, 1,06 2, 10, ,50 14,60 9,17 43,76 0,15 14,74 9, 43,39 0, 0,94 1,00 0,85, ,60,60 9,77 14,46 0,05,57 9,84 15,71 0,06 0,15 0,73 8,61 29, ,10,90 10,48 21,80 0,07,88 10,55 23,09 0,09 0,12 0,66 5,90 35, ,80 17,10 11, 33,31 0,12 17, 11,,52 0,14 0,45 0,72 3,64, ,10 21,00 13,61 14, 0,05 21,03 13,66,44 0,07 0,15 0,38 15,14 35, ,,00 14,01,92 0,07,08 14,06,81 0,09 0,40 0,36 9,03, ,50,60 7,94,14 0,10,61 8,05,89 0,10 0,04 1,40 3,12 2, ,, 8,91 33,92 0,, 9,02 33,53 0,14 0,40 1,23 1, 13, ,,80 10, 55,61 0,,93 10,42 52,84 0, 0,77 1,15 4,99 8, ,00,70 10,11,96 0,08,65 10,,17 0,07 0,21 1,07 7,13 6, ,50,50 11,00 25,44 0,12,52 11,11,04 0,11 0,08 0,96 2,36 10, , 19,10 12,38 45,84 0,17 19, 12,49 45, 0,19 0,62 0,86 1,47 9, ,60 25,50 13,82 13,82 0,05 25,41 13,92,13 0,07 0,37 0,70,74, ,10 23,70 14,55,38 0,08 23,68 14,64 23,73 0,10 0,08 0,62 6,04, ,50 21,90 15,,21 0,13 21,95 15,37 35, 0,14 0, 0,58 2,90 11,39 Average absolute mismatch [%]: 0,35 0,81 6,33,98 The output humidity and temperature is very close to simulation program of Klingenburg. The total water consumption has an average absolute error of 6.33%. This mismatch is also visible in Figure 14, the actual values differ from the calculated polynomial. The total energy consumption differs strong from the simulation program from Klingenburg. A part of this mismatch could be addressed to the incorrect calculation of the total water consumption. Another cause is entrance pressure which is assumed constant in the Simulink model and differs in the Klingenburg model. Appendix - Page

84 1.8 COMMONLY USED CONVERSIONS Because of the fixed variables for the in- and outlet conditions, some conversions of units are necessary within the models. In the following sub-chapters the most common required conversions are explained. The conversions are all based on the ASHRAE psychometrics standards of 09.[] Absolute / Relative humidity conversion The conversion between absolute and relative humidity is a three step model. First the saturation pressure is calculated. Based on that, the saturation humidity ratio is calculated. Finally the ratio between the saturation humidity ratio and the actual humidity ratio is the relative humidity. The formula to calculate the saturation pressure (p ws ) is dependent on the temperature, for an estimation in the range between -100 to 0 C formula ( 27 ) is used and between 0 to 0 C formula ( ) is used. ln p ws = C 1 t + C 2 + C 3 t + C 4 t 2 + C 5 t 3 + C 6 t 4 + C 7 ln t ( 27 ) ln p ws = C 8 t + C 9 + C 10 t + C 11 t 2 + C 12 t 3 + C 13 ln t ( ) Where: C 1 = E+03 C 2 = E+00 C 3 = E 03 C 4 = E 07 C 5 = E 09 C 6 = E 13 C 7 = E+00 C 8 = E+03 C 9 = E+00 C 10 = E 02 C 11 = E 05 C 12 = E 08 C 13 = E+00 The saturation humidity ratio (W s ) can be estimated by formula ( 29 ) and the relative humidity is a ratio between the saturation humidity ratio and the actual humidity ratio. p ws W s = ( 29 ) p p ws μ = W W s ( ) Specific volume The specific volume (v) [m 3 /kg da ] can be estimated by formula ( 31 ) where p is the pressure in kpa. v = t W p ( 31 ) Enthalpy conversion Calculation of specific enthalpy in [kj]/kg da ] of moist air can be useful to calculate air temperatures changes. = 1.006t + W( t) ( ) Appendix - Page 33

85 APPENDIX VI: AVAILABLE CONTROL STRATEGIES A chronological overview of articles about different developed control strategies is given in this chapter. Special interest is given at the different operating modes, measured parameters, controlled parameters and the results of the control strategy. In chapter 1.5 a short overview of these articles is given with a sub-conclusion. 1.1 CONTROL DESIGN OF OPEN-CYCLE DESICCANT COOLING SYSTEMS USING A GRAPHICAL ENVIRONMENTAL TOOL (03)[17] One of the first articles that deal with control strategies of DEC systems is written in 03. Although it uses costly regeneration energy, instead of solar heat for regeneration the control principle can still be used. The DEC system is used to provide cooling for a building in Paris and Nice in France. This control strategy switches between three modes: ventilation, indirect humidification and DEC. It uses two control parameters: regeneration temperature and airflow rate. A model made in Matlab/Simulink with the SIMBAD library is used for simulation of the control strategy. Switching between different operation modes is done by T 1, T 2 and the occupation level. T 1 represents the difference between outdoor air temperature and air temperature at the outlet of the indirect humidifier and T 2 is the difference between indoor air temperature and supply air temperature. The control scheme is graphically shown in Figure 15, where depicts hysteresis operation. Figure 15: Control strategy diagram [17] 1.2 PARAMETRIC ANALYSIS OF A SOLAR DESICCANT COOLING SYSTEM USING THE SIMSPARK ENVIRONMENT (05)[] A DEC system with 14.8m 2 of solar collectors is used for the cooling of a training room in Chambery in Eastern France. The goal of this article is to decrease primary energy consumption and increase system performance. The operating modes are basically the same as in [17], it can also switch between ventilation, indirect evaporation and DEC mode. Switching between different operation modes is also done by T 1, T 2 and the occupation level. A simulation in simspark is made to simulate control strategy. In occupation mode, the air flow is kept constant. If room temperature exceeds C and storage temperature if higher than 50 C, the system switches to the DEC mode till the temperature reaches 23 C. If the storage temperature is lower than 50 C, the system continues running in indirect Appendix - Page

86 humidification or ventilation mode. In inoccupation mode, the system runs either in ventilation or in indirect humidification mode, depending on the value of T 1 and only if room temperature exceeds 23 C and T 2 exceeds 4.5 C. Occupation mode Figure : Control strategy diagram [] Inoccupation mode Table shows the effect of the ventilation air flow rate during inoccupation period on several parameters. It can be seen that as the air flow rate increase the installation runs less in desiccant mode, the amount of hours when extra external (auxiliary) cooling is required decreases, the cooling requirement factor (IB) decreases and electrical energy consumption increases. With an air flow of 0.2 kg/s (2.8ACH) it has the highest benefits with the least electrical consumption. Table : The effect of different air flow rates 1.3 PROPOSAL FOR A NEW HYBRID CONTROL STRATEGY OF A SOLAR DESICCANT EVAPORATIVE COOLING AIR HANDLING UNIT (07)[19] The article is split up into two steps, first the identification of the control parameters and then the control strategy of these parameters. A simulation in TRNSYS is made, which is validated with data from an installation in Freiburg (Germany). The control parameters and operation modes of this installation are given in Table 23. Appendix - Page 35

87 Table 23: Tested parameters definition [19] Control parameters Ventilation Indirect humidification Combined humidification DEC Inferior limit Superior limit Flow rate x x x x 3 ACH 8 ACH Regeneration x x x 70% 95% humidifier efficiency Process humidifier x x 70% 95% efficiency Desiccant wheel air x flows ratio Regeneration temperature x :C 95:C The following things can be concluded from changing the control parameters: Increase in flow rate must be used with care, because it induces in almost all cases a drop in performance. The variation of the air flow ratio in the desiccant wheel has a positive effect on the cooling power efficiency, but not on the cooling power. The variation of the regeneration temperature is an interesting tool to modulate the cooling power in the DEC mode. An increase of regeneration temperature from 50 to 90:C results in a rise of 0% of the cooling power and of 40% of cooling primary efficiency. The control strategy is based on the enthalpy difference ( H) between the outdoor air and the air removed from the room. Simulations show that the cooling power is very dependent of the differential of enthalpy, and rather little on the indoor temperature. H is used to choose the best operating mode corresponding to the least of energy spend. The control is done in three steps, first the system chooses the operation mode based on the H and indoor temperature, as shown in Figure. Then for the combined humidification mode, a control on indoor relative humidity is carried out, in order to make sure that humidity does not exceed 65%, otherwise the system shifts to DEC mode. Finally the controller chooses the values of the controlled parameters of the operating mode according to the indoor temperature. The air flow is controlled by a PID-controller and the regeneration temperature by a P-controller. The system is compared with a compression chiller system with a COP that is assumed to be 2.8. The results of a cooling season are found in Table. The primary energy consumption of a compression chiller is definitely higher (45%) than a desiccant cooling system with the hybrid control strategy. Figure 17: Decision scheme for operation mode [14] Appendix - Page 36

88 Table : Comparison of a reference system with a DEC system with the new control strategy[19] Reference system DEC system Cooling demand (kwh) Chiller consumption (kwh) 10 - AHU consumption (fans, rotors, pump) (kwh) Auxiliary heater consumption (kwh) Primary energy consumption (kwh) Primary energetic efficiency (-) PRIMARY ENERGY OPTIMIZED OPERATION OF SOLAR DRIVEN DESICCANT EVAPORATIVE COOLING SYSTEMS THROUGH INNOVATIVE CONTROL STRATEGIES (09)[] The analyzed DEC system is installed in the University of Applied Sciences in Stuttgart. For regeneration m 2 of vacuum tube and m 2 of solar air collector can be used. The vacuum tubes are connected to two 00 l hot water storage tanks. The simulation of this installation is made in INSEL. The system has four operation modes: ventilation, indirect humidification, combined humidification and DEC mode. The controlled parameters are: flow speed, humidification and regeneration temperature. The control strategy is based on the room temperature and humidity. Air flow rates are kept at a minimum rate at temperatures below.5 C. < 23.5⁰C Free cooling mode ⁰C Indirect humidification ⁰C Direct humidification, controlled in 7 stages in order to reach C supply temperature and humidity is limited to 10g/kg ⁰C DEC mode, P-controller regulates regeneration temperature according to the room temperature >.5⁰C DEC mode with increased air flow. A PID controller tries to control the air volume flow rate in order to control the room temperature. The control range is between 4-8ACH. Five different cases are compared and simulated for a seasonal cooling period: Case 1: Standard control cascade - Uses fan speed control as first option Case 2: Electricity optimized standard control cascade - Uses fan speed control as last option (method as explained above) Case 3: Advanced model based control Uses an online optimizer tool which selects the operating mode. One case without and one with the bypass of sorption wheel Case 4: Reference system - Ventilation system with air volume flow control and compression chiller with average COP of 2.8 Appendix - Page 37

89 Figure : Simulation results for the overall primary energy ratio of a cooling period.[] As clearly visible from Figure, the standard control reaches the lowest PER. The electricity optimized, which uses fan speed control as last option has more than doubled the PER. The third and fourth column based on the online optimizer tool, which also increases the PER. 1.5 CONCLUSION The used operating modes are more or less the same in the articles. The systems in the last two articles also use combined humidification. In Table 25 an overview of the different operating modes is given. An x indicates that the component of the system is switched on, otherwise it is switched off. Table 25: Different operation modes for a DEC system Operation mode Fan(s) Direct humidifier Indirect humidifier Heat recovery wheel Desiccant wheel Off Ventilation (free cooling) x Direct humidification x x Indirect humidification x x x Combined humidification x x x x Desiccant Evaporative Cooling (DEC) x x x x x All the systems use the air flow rate as control parameter and all except one use the regeneration temperature to control the room temperature. The last article also uses humidification as a control parameter, but only in direct and indirect humidification modes. The measured parameters differ much from each other, only the room temperature is used as measured parameter in all the systems. Only the first two articles have a different operation scheme for an occupied and unoccupied room. Unfortunately, none of the control strategies make use of thermal inertia of the room in an unoccupied situation. An overview of the reviewed articles is given in Table. Appendix - Page 38