Demand side management for integration of variable renewables

Transcription

1 Demand side management for integration of variable renewables PHYS-E0483 Advances in New Energy Technologies, spring 2016 Jyri Salpakari, M.Sc. (Tech.), PhD student New Energy Technologies group, Aalto SCI

2 Energy system flexibility with variable renewable energy (VRE) Demand and supply balance of electricity in power systems: f and V Variable and uncertain renewable energy (VRE) additional challenge Conventionally: production controlled to meet demand variability and contingencies Storage, demand side management (DSM), interconnections flexibility without extra (often fossil fuelbased) production IEA. Harnessing Variable Renewables: A Guide to the Balancing Challenge,

3 Demand side management (DSM) Load decrease/increase or shifting Shifting requires storage in load process and < 100% utilization rate Can provide DSM without affecting final service (clean dishes, warm apartment, industrial product) 100% efficient virtual energy storage Gellings C, Smith W. Proc IEEE 1989;77:

4 Demand side management (DSM) Significant VRE variation & uncertainty and DSM opportunities both in 1-12 h timescale Benefits besides VRE integration Less price spikes avg. price decrease Less (expensive to run, fossil fuel) peak power plant use Gellings C, Smith W. Proc IEEE 1989;77:

5 DSM programs Price-based DSM Real-time pricing (e.g. Nordpool spot + margin in Finland) Critical peak pricing Time-of-use pricing (e.g. night-rate electricity in Finland) Incentive-based DSM Direct load control Direct participation to energy markets Price-based and market participation: slow energy trading DSM, > 10 min Direct load control: reliability provision with fast DSM, < 10 min - Risk to reduce inherent diversity of loads - Customer often paid for load change compared to baseline, which is impossible to directly measure Laitoksen nimi 2/10/2016 5

6 DSM sources in Finland Total peak load: 14 GW Industry Electrolysers, electric arc furnaces and rolling mills (metal industry): flexible load 2% of total peak load Grinderies (pulp and paper): 6% Electrolyses, extruders and compressors (chemical industry): 1% Mills in cement, lime and gypsum production: 0.04% Service sector Cold food storages, HVAC Not quantified in Finland Residential Electric heating: 23-29%, shiftable by taking advantage of storages: Heat capacity of building envelope Storage integration, e.g. water tank in hydronic heating system Wet and cold appliances: 2.6% 6

7 Thermal storage Sensible heat storage: E= cmδt Stratified water tanks integrated to electric heating/cooling Envelopes of electrically heated buildings Magnesite in storage heaters Latent heat storage: solid-liquid, crystal structure change Heat has low energy quality Good idea with electric heating/cooling Heat pump charging COP 3 Cheap: e.g m 3 water tank only 3 /kwh (batteries: /kwh) Klimstra, Hotakainen. Smart Power Generation,

8 DSM potential in German households Load Night storage heaters Domestic hot water heaters % of min/max net load (load-res), Ventilation 16 GW/79 GW systems Refrigerators Freezers Positive capacity Negative capacity Storage from load shifting Investment costs Variable costs Fixed costs 19 88% 128% 58% 10% 0% 11% 1 5% 17% 90% 113% 0% 11% 8 38% 55% 8% NR NR NR 2 9% 15% 9 19% 12% 90% with freezers 90% with refrigerators % of max RES, 29 GW % of a gas turbine % of pumped hydro, 40 GWh 298% 0% 228% 298% 0% 228% Hot water circulation pumps 3 14% None 98% 1625% 0% 250% Washing machines, dryers and dishwashers 5 24% 72% 105% 185% 0% 183% Heat pumps with storage 0.3 1% 0.7% 8% 38% NR NR 8

9 DSM potential in German households Load Night storage heaters Domestic hot water heaters Ventilation systems Positive capacity Negative capacity Storage from load shifting Investment costs Variable costs Fixed costs 19 88% 128% 58% 10% 0% 11% 1 5% 17% 90% 113% 0% 11% 8 38% 55% 8% NR NR NR Refrigerators 90% with 2 9% 15% freezers 298% 0% 228% Freezers 90% with 9 19% 12% refrigerators 298% 0% 228% Hot water circulation pumps 3 14% None 98% 1625% 0% 250% Washing machines, dryers and dishwashers 5 24% 72% 105% 185% 0% 183% Heat pumps with storage 0.3 1% 0.7% 8% 38% NR NR 9

10 DSM potential of German service sector Load Food store refrigerators Electric hot water generation Ventilation systems Positive capacity Negative capacity Investment costs Variable costs Fixed costs Max. 1 7% Max. 10% % 1% 0% Avg % Avg. 3% 7 45% 1% 0% Avg % Avg. 5% % 1% 0% Air conditioning Avg % Avg. 8% 4 148% 1% 0% Night storage heaters Avg. 1 5% Avg. 33% 2 12% 1% 0% Municipal waste water treatment Avg % None 4 187% 1% % 10

11 DSM potential of German industry Load Chloralkali electrolysis Positive capacity Negative capacity Storage from load shifting Investment costs Variable costs Fixed costs 0.8 4% Small 3% < 0.3% > 147% 0% Mechanical wood pulp refining 0.3 2% % 1% 3 4% < 15% 0% Aluminum electrolysis 0.4 2% None None < 0.3% % 0% Cement milling 0.3 2% % 8% 4 5% % 0% Steel melting in electric arc furnaces 1 7% None None < 0.3% > 2941% 0% Compressed air with variable speed compressors 0.3 1% % 40% 6% NR NR Ventilation systems Avg. 1 7% Cooling and freezing in food industry Avg. 2 9% Process cooling in chemical industry Avg % Avg % Avg % NR 97% NR 0% NR NR NR 0% None None NR NR 0% 11

12 Two example industrial processes behind the German numbers Mechanical wood pulp refining Wood chips ground mechanically to pulp by refiner plates Pulp can be stored, utilization level typically 80% shiftable load Full activation or shutdown possible in a few minutes, not in immediate sequence (too much wear to components) Positive capacity: average load, 80% of 312 MW = 250 MW Negative capacity: average unused capacity: 62 MW Pulp storages usually can store 1.5 h maximum capacity production: 468 MWh Electric arc furnaces Scrap steel melted with electric arc 45 min of melting, 15 min empty & refill Run at full capacity load shedding only possible Immediate shutdown possible Disruption > 30 min scrap metal cooled down, whole process has to begin again Positive capacity: 1097 MW 2/10/

13 Behavior and decision-making effects? DSM affects people and organizations How do their behavior and decisions affect realisation of DSM potential? Discuss in groups (10 min), two cases Residential consumer Operator of energy-intensive industrial process 13

14 Behavior and decision-making effects Residential consumers Motivation? Electricity cost small part of household income (USA 2009: 2.8%), DSM savings 2-30% of this (USA, Finland) Risk-averse thinking: may prefer risk premium in constant price vs. real-time pricing and DSM Response may be poor if requires manual control Acceptance of direct load control? Industrial organizations Electricity directly from suppliers, financial hedging (analogous to residential) Processes integrated with customers: co-operation required Labor-intensive processes: salary expenses fixed Motivating staff 14

15 DSM field experiments, projects and modeling: overview and highlights DSM potential reviewed: estimates, limited by controllability of loads and consumer behavior Studied by field tests, DSM programs and modeling DSM programs and experiments: 10-50% controllable loads achieved USA, Finland, Nordic countries Residential consumers, large programs with different consumers DSM modeling: 5-35% cost savings, max. 50% peak load reduction achieved Different loads: e.g. steel plant, residential cooling, dairy DSM with VRE: 26-34% increase in wind energy demand with control of residential loads Correlation between lower electricity cost and increased wind power use Populations of thermostatically controlled loads can be managed to follow VRE variability: 3.4 MW of load per 1 MW of VRE 15

16 Conclusion: DSM with VRE Can contribute emission-free, cost-competitive flexibility for VRE integration Potential especially in electric heating & cooling, energyintensive industrial loads Large VRE share increases electricity price variation price-based DSM more profitable DSM through DLC can provide e.g. reserves for frequency control 2/10/