The need for market data and market solutions in the heating sector to obtain an efficient integration with the electricity market

Transcription

1 The need for market data and market solutions in the heating sector to obtain an efficient integration with the electricity market Cities & AffaldVarme Aarhus & Aarhus University dept. of engineering Anders Bavnhøj Hansen Chief engineer Research & development Energinet.dk The need for data in the heating sector to obtain an efficient integration with the electricity market 1

2 Agenda 1. Framework conditions scenarios for analysis of City solutions 2. Analysed Power-Heat-Gas-Fuel solutions (City 3. Market solutions to control the system integration 4. The need for data in the heating system 5. Questions The need for data in the heating sector to obtain an efficient integration with the electricity market 2

3 Uncertainties in international framework conditions (fuel and CO2-prices, focus on green energy etc. Paris COP21 A need for scenarios to handle uncertainties Energilagringens rolle i Energinet.dk s fremtidsscenarier

4 Scenarios to cope with an uncertain future Scenario 3: Green Nations Scenario 4: Green Europe Scenario 1: Moderate Nations 2030 Scenario 2: Moderate Europe Danish scenarios based on ENTSO-E European scenarios The need for data in the heating sector to obtain an efficient integration with the electricity market 4

5 Energinet.dk scenarios towards 2030 Scenario 3 Green Nations Danmark showcase for transition towards Well below 2 degr. target Low international cooperation but many countries are ambitios IEA 450 PPM price level (low fuel and high CO2 prices High focus RE Scenario 4 Green Europe EU showcase for Green transition (COP21 Energy Union International cooperation in EU Energy Union with markets for Green gas IEA 450 PPM price level (low fuel and high CO2-prices National focus Denmark low RE-ambition - only whats internationally imposed Low international cooperation Brexit tendencies in Europe no EU carbon market Few reforms of tax/regulation in DK and EU IEA Current Policies fuel prices - High fuel-prices and low CO2-prices Scenario 1 Moderate Nations Low focus RE EU Energy Union Moderate ambition RE in EU and DK High international cooperation EU regulation, standards and grid codes IEA New Policies price level Medium Fuel and CO2-prices The need for data in the heating sector to obtain an efficient integration with the electricity Scenario market 2 Moderate Europe 5

6 Scenarios power, heat and fuel production in scenarios Scenario 3 Green Nations Traditional CHP units Power/heat integrated biorefineries Large heat pumps Individual heat pumps High focus RE Scenario 4 Green Europe Traditional CHP units Power/heat integrated biorefineries Large heat pumps Individual heat pumps National focus Traditional CHP units (coal, n-gas, biomass Boilers for heat production (biomass,gas EU Energy Union Traditional CHP units (Gas, Biomass Boilers for heat production (biomass,gas A few large heat pumps (district heat Electric boilers Scenario 1 Moderate Nations Low focus RE The need for data in the heating sector to obtain an efficient integration with the electricity Scenario market 2 Moderate Europe 6

7 Example on power/heat bio refinery (case

8 From case Cities to national solutions (to be implemented Case City Gas grid and existing Power plant capacity Heat demands Biogas ressources 8

9 Post feasibility study 2035 reduced fossil oil demand

10 Feasibility study reduced fossil oil demand Import power Transit Power system Export power Solar Wind Bio CHP and boiler Gas CHP and boiler Electrolysis DK2014: 7,8 ton CO2/capita from energy High temp Central heat pumps Heat systems (DH and block HT-VP. El-proces Light, it,cool. Procesheat Bio, waste etc. Varmep. Kedel EV/PHEV FM/FC Building heating. Roadtransport Natural gas 6 mio ton CO2 Ethanol Anaerob digestion Gas-systems (methan/synthesisgas/h2 incl. local systems Gas storage Gascathalysis etc. Seatransport Bioplast DK 2035: 1,2 ton CO2/capita (from fossil Energy etc. Transit Thermal gasification Liquid fuels fossil/re (Gasoline, Diesel, Ethanol, Methanol, DME etc The need for data in the heating sector to obtain an efficient integration with the electricity market Case with straw used for biogas Railwaytransport Aviation 10 TWh=36 PJ 10

11 District/block heat production (PJ Building heat (PJ ocess heat (PJ Production and consumption of heat case study Heat pumps Excess heat biofuel and electrolysis etc Process heat Biomass boiler Gas boiler Heat pump - process District/block heat Solar/geoth. etc. Boilers Boiler 20 0 CHP District- and block heat Building heating Heat pump - individual District/block heat

12 Examples of heat and power prices in a 2035 case simulation! (large plant with integrated power/heat/fuel production Individual climate units to produce heat in hours with low electricity prices? International Conference on Smart Energy Systems and 12

13 Some questions Use of local climate units (heat pumps/cooling integrated with DH Delivery from commercial buildings with cooling units Delivery of heat to DH? Need for data Marginal price/value at delivery point Temperature levels for delivery at DH point and value of delivery Market solutions to integrate power and heat Use of big data technology on DH data collection to identify How to combine 2016 metered data with Scenario 2030 data? International Conference on Smart Energy Systems and 13

14 Examples of heat and power prices in a 2035 case simulation! (large plant with integrated power/heat/fuel production A need for a market solutions in heat and power to handle fluctuating prices International Conference on Smart Energy Systems and 14

15 Analysis of Energy System dynamics - including power TSO/DSO (and potentially heat market EUR/MWh jan- apr- jul- okt- jan- apr- jul- okt- jan- apr- jul- okt- jan- apr- jul- okt- jan- apr- jul- okt Day-ahead Systembalance (e.g. 5 min Reg. Energy conversion units Electric vehicles Heat pumps/climate units Other flexible units G G 2 DSO D-LMP Reg. G n Import el El-system Export el Vind Bio Kraftvarme Gas Kraftvarme Elektrolyse Central varmep. Decentral varmep. El-proces lys, it, køl Sol- Fjern- og blokvarme systemer Procesvarme Bølge Bio, affald mv. Kul Naturg Olie Import Smart Energy Søtransport system compliant Flytransport with COP21 Anaerob Gaskatalyse mv. forgasnin Ethanol Termisk forgasn. Gas-systemer (metan/syntesegas/h2 Gaslagre Flydende brændstoffer (Benzin, Diesel, Metanol, DME etc. Varmep Kedel EV ICE/FC Bygn opvarmn. Vejtransport Banetransport

16 Analysis of Energy System dynamics step response Step increase energy price EUR/MWh Day-ahead jan- apr- jul- okt- jan- apr- jul- okt- jan- apr- jul- okt- jan- apr- jul- okt- jan- apr- jul- okt Systembalance price (e.g. 5 min Power-price (balance price Power EV Nodal tarif Simple PI tarif regulator Nodal tarif Total price Smart Energy system compliant with COP21

17 Analysis of Energy System dynamics - including power TSO/DSO (and potentially heat market EUR/MWh jan- apr- jul- okt- jan- apr- jul- okt- jan- apr- jul- okt- jan- apr- jul- okt- jan- apr- jul- okt Day-ahead Systembalance (e.g. 5 min C MPC input? Energy conversion units Electric vehicles Heat pumps/climate units Other flexible units G 1 System identification (Data mining, AI G 2 DSO D-LMP MPC input? C G n Import el El-system Export el Vind Bio Kraftvarme Gas Kraftvarme Elektrolyse Central varmep. Decentral varmep. El-proces lys, it, køl Sol- Fjern- og blokvarme systemer Procesvarme Bølge Bio, affald mv. Kul Naturg Olie Import Smart Energy Søtransport system compliant Flytransport with COP21 Anaerob Gaskatalyse mv. forgasnin Ethanol Termisk forgasn. Gas-systemer (metan/syntesegas/h2 Gaslagre Flydende brændstoffer (Benzin, Diesel, Metanol, DME etc. Varmep Kedel EV ICE/FC Bygn opvarmn. Vejtransport Banetransport

18 Summing up In the high RE scenarios (3,4 there is a number of energy conversion processes (bio-to-fuel, power-to-gas, CHP producing waste heat Production price (marginal for power, heat and gas-price are fluctuating There is a need for an intelligent heating system with dynamic pricing for heat (high/low temperature Big data methodology, data-mining and AI could lead to deeper knowledge on system response related to state-parameters in the heating system The knowledge form system-identification could be used to controlling/market solutions in power and heat systems (E-MPC etc The need for data in the heating sector to obtain an efficient integration with the electricity market 18

19 Thank you for attention Link: The need for data in the heating sector to obtain an efficient integration with the electricity market 19