EEN-E Measurement and Control of Energy Systems DRYING OF BIOMASS IN A FIXED BED DRYER LABORATORY EXERCISE INSTRUCTIONS

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1 EEN-E Measurement and Control of Energy Systems DRYING OF BIOMASS IN A FIXED BED DRYER LABORATORY EXERCISE INSTRUCTIONS Aalto University Laboratory of Energy Efficiency and Systems 2016

2 Table of contents DRYING OF BIOMASS IN A FIXED BED DRYER Goals of the work Measurement setup Location Test rig Instrumentation Software Measurements and Tasks Steps of measurement (more detailed description is given by the teacher during the exercise) Calculation of economic issues Reporting Literature... 5 Appendix 1 GENERAL STRUCTURE OF A SCIENTIFIC REPORT

3 DRYING OF BIOMASS IN A FIXED BED DRYER 1. Goals of the work The goal of this exercise is to study the drying of biomass (bark/chips) and representing the results as a drying curve based. After passing the exercise, the student knows which factors influence the characteristics of drying and how these factors effect drying. 2. Measurement setup Pre-drying improves the lower heating value of biomass reducing the marginal fuel consumption of a power plant or heat plant. The dryer investment is covered by savings obtained from the reduced marginal fuel consumption. In this case, the feasibility of biomass drying is evaluated by defining the payback period for a biomass dryer investment. The biomass dryer studied in this work is a continuous fixed bed dryer (Fig. 1). In this measurement, drying curve of biomass is experimentally defined in a fixed bed batch dryer. This data is then used to evaluate how useful the biomass drying process is for the studied plant. Instructions for performing the measurement will be given before the measurement Location The test rig has been built in the Laboratory for Energy Economics and Power Plant Technology, which is located in Building K4 of the Aalto University School of Engineering. The room number is 124. Figure 1. Example of a continuous fixed bed dryer 2.2. Test rig Figure 2 shows the test rig used for the experimental tests. Diameter of the drying chamber is 400mm and other technical data of the test rig is listed in the caption of Figure 2. Hot air is 2

4 used as a drying gas and it always flows through the bed from top to bottom. Part of the air flow is heated in an air heating element to a higher temperature than the desired one, and after heating it is mixed with the hall air in an air duct to obtain the correct air temperature before the bed. The air velocity before the bed is adjusted to the desired one by changing the speed of rotation of the fan. The test rig lies on a scale which always saves the mass of the biomass sample on the computer after a given time interval (e.g. 10 seconds). As the biomass sample dries, the mass decreases and the drying curve is defined on the basis of the mass change. Figure 2 shows the test rig used for the experimental tests. Diameter of the drying chamber is 400mm and other technical data of the test rig is listed in the caption of Figure 2. Hot air is used as a drying gas and it always flows through the bed from top to bottom. Part of the air flow is heated in an air heating element to a higher temperature than the desired one, and after heating it is mixed with the hall air in an air duct to obtain the correct air temperature before the bed. The air velocity before the bed is adjusted to the desired one by changing the speed of rotation of the fan. The test rig lies on a scale which always saves the mass of the biomass sample on the computer after a given time interval (e.g. 10 seconds). As the biomass sample dries, the mass decreases and the drying curve is defined on the basis of the mass change Instrumentation Figure 2 shows the points where instrumentation is installed. Temperature measurement after blower. Pressure measurement after blower. Temperature measurement before drying chamber. Pressure measurement before drying chamber. Temperature measurement after the drying chamber. Pressure measurement after the drying chamber. Scale Software Instrumentation is integrated to Labview, which can be used to store and visualize data. Labview can also be used to adjust the temperature and velocity of air after the blower by varying the rotation speed of the blower (fan). Additionally the scale has its own software. 3

5 Figure 2. Technical data: maximum power of heating unit 30kW, maximum temperature of drying air c. 200 C, maximum air velocity per cross sectional area of the drying chamber c m/s, diameter of the drying chamber 400mm, height of the drying chamber 800mm. 3. Measurements and Tasks The task is to present the drying curve of a given amount of moist biomass. Make a measurement plan for the drying test where you define the temperature of the inlet air, air velocity before the bed and bed height. Define the drying curve on the basis of the measurement data using regression analysis. Time is on x-axel and moisture content (amount of H2O kg/amount of dry solid material kg) on the y-axel.amount of water to dry solids Moisture content [kg H2O /kg d.b. ] Temperature of the inlet air 70 C Absolute humidity of the inlet air 3-4g/kg da N o kg H20 (kg d.b. s) -1 y = x x x R 2 = Time [s] Calculate the bulk density of biomass on the basis of measurement data Define the outgoing moisture content for biomass after the dryer. Give also some reasoning why you have ended up to this moisture content. Define the heat consumption and specific heat consumption of the dryer on the basis of the measurement data. Calculate the investment of drying of biomass based on the measurements Calculate the potential savings of other fuel Discuss the economic benefit of investing on a dryer 4

6 4. Steps of measurement (more detailed description is given by the teacher during the exercise) Definition of initial moisture contents of biomass Initial preparations of measurement Labview Scale software Valves, fan, heater Preparations for the material to be dried Loading of the dryer Actual measurement Closing down the measurement 5. Calculation of economic issues The investment costs of the dryer in million Euros can be estimated using the following correlation: Inv. = 0.013(V/1000) 0.7 without HRU (heat recovery unit), where V is the volume flow rate through the dryer in an hour at the inlet temperature of drying air. Assume some pressure drop over the drying system to calculate the electricity consumption of the fan (two times the pressure drop over the bed). Efficiency of the fan is 0.7. Take also into account the reduction of CO2-emissions when you calculate savings of the dryer investment. Use a current market price for CO2-ton. Currently the boiler consumes peat (cost 12 /MWH). Assume that biomass can be obtained for free and the drying air (85 C) is also for free. The boiler heat capacity is 50 MW, which needs to be kept in this value always. The amount of biomass is limited to 2 kg/s. Peat is available as much as needed. Lower heating value (LHW) of moist fuel calculated on dry basis qu = qi 2.443u where qi = lower (effective) heating value of completely dry fuel [MJ/kgds] u = moisture content of fuel on dry basis [kgh2o/kgds] Lower heating value (LHW) of moist fuel calculated on wet basis qw = (1-w)qi w2.443 qi = lower (effective) heating value of completely dry fuel [MJ/kgds] w = moisture content of fuel on wet basis [kgh2o/kgwet] Fuel input into the boiler Фfuel = mdsqu or Фfuel = mwetqw mds = mass flow rate of dry fuel [kgds/s] mw = mass flow rate of moist fuel [kgwet/s] 6. Reporting Follow the guidelines given in Appendix Literature Mujumdar, Arun S., ed. Handbook of industrial drying. CRC Press,

7 Appendix 1 GENERAL STRUCTURE OF A SCIENTIFIC REPORT 1 Cover which includes o name and date of the exercise o students participating in the exercise o a contact person whom feedback and possible remarks should be directed to 2 Contents with page numbering 3 A short description of the exercise 4 Description of the measurement setup and the instruments used in the measurement 5 Step-by-step workflow of the exercise 6 Analysis of the measurement results o applying calibration corrections (if known) o statistical processing of repeated measurements (averages, standard deviations) o values of quantities calculated based on the results o possible theoretical comparison calculations o comparing results with each other 7 Error analysis o Discuss what measurement errors can occur and why is the scale more accurate in approximating the drying of biomass than the equipment that measures the moisture content in air 8. Financial calculations 9 Conclusions o conclusions from the results themselves o conclusions from the studied phenomena etc. 10 Sources 11 Appendices o logger data o extensive tables o program codes etc. 6

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