EFEU / FLEXe Syri Sanna flexible district heat systems enabling future success
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EFEU / FLEXe Syri Sanna flexible district heat systems enabling future success
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EFEU / FLEXe Syri Sanna flexible district heat systems enabling future success
- 1. Flexible district heat systems enabling future success 31.10.2016, Sanna Syri, professor, Energy Technology and Energy Economics, Aalto University, School of Engineering
- 2. We studied, how city-level district heat (DH) systems could best operate as part of the future energy system. Typical Finnish city level DH systems have both combined heat and power (CHP) plant and heat-only boilers. The overall efficiency is exceptionally high in international comparison. We studied the expected future changes by using the VTT Wilmar electricity market scenarios as input in our modelling. Three scenarios for the Northern European market area for 2050: 1. Shares of wind and PV 28% and 12% 2. Shares of wind and PV 42% and 18% 3. Shares of wind and PV 30% and 30% of all electricity production. District heat system scenarios
- 3. Study case was Järvenpää DH network operated by Fortum Ltd: • Modern biofuel CHP plant • We assumed a minimum operation time of one week for CHP when started • 7 heat-only boilers (natural gas, fuel oil) + possibility for trade with Kerava and Vantaa Simulation and system optimisation (system cost minimisation) in different scenarios was done with EnergyPRO model developed by Aalborg university, Denmark. Case Järvenpää
- 4. Hourly prices as input to EnergyPRO modeling. Electricity price scenarios 0 20 40 60 80 100 120 140 160 1.1. 1.2. 1.3. 1.4. 1.5. 1.6. 1.7. 1.8. 1.9. 1.10. 1.11. 1.12. Electricityprice[€/MWh] Date Scenario 3 (average 66 €/MWh) 0 20 40 60 80 100 120 140 160 1.1. 1.2. 1.3. 1.4. 1.5. 1.6. 1.7. 1.8. 1.9. 1.10. 1.11. 1.12. Electricityprice[€/MWh] Date Scenario 2 (average 63 €/MWh) 0 20 40 60 80 100 120 140 160 1.1. 1.2. 1.3. 1.4. 1.5. 1.6. 1.7. 1.8. 1.9. 1.10. 1.11. 1.12. Electricityprice[€/MWh] Date Scenario 1 (average 70 €/MWh)
- 5. Heat storage (110,000 m3) and heat pump (20 MW) included (scenario 2) 01/11/16 5 Järvenpään voimalaitos, CHP Electricity consumption 01.0515.0401.0415.0301.0315.0201.0215.0101.0115.1201.1215.1101.1115.1001.1015.0901.0915.0801.0815.0701.0715.0601.0615.0501.05 Electricity[MW] 22 20 18 16 14 12 10 8 6 4 2 0 Järvenpään voimalaitos, CHP Ristinummi, HOB Järvenpään lämpölaitos, HOB Tuusulan lämpölaitos, HOB Lahela, HOB Elec Heatpump Bio, HOB Heat consumption Heat rejection 01.0515.0401.0415.0301.0315.0201.0215.0101.0115.1201.1215.1101.1115.1001.1015.0901.0915.0801.0815.0701.0715.0601.0615.0501.05 Heat[MW] 120 100 80 60 40 20 0
- 6. Both heat storages and heat pumps are important elements in future DH systems: • They provide flexibility to operate in very different electricity market situations. • The average heat production cost decreases even with very large heat storages (up to 110 000 m3). • Heat storages proved profitable investments also in the Helsinki urban case study conducted by Aalto School of Science. Soft-linking of different models was successful and provided good insight into the issue. We recommend this for future analyses. Please see posters: District heating network simulation and optimization by VTT, Aalto ENG and Finnish Meteorological Institute FLEXeble District Heating for Prosumers by LUT, Fortum and Aalto ENG Urban networks with high share of variable generation by Aalto SCI for more information! Conclusions