Modeling the flexibility offered by coupling the heating sector and the power sector: an assessment at the EU level Matija Pavičević , Juan-Pablo Jimenez, Konstantinos Kavvadias, Sylvain Quoilin Faculty of Engineering Technology Joint Research Centre – European Commission 5th International Conference on Smart Energy Systems 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Introduction • Main questions : • How much flexibility can we obtain from district heating, CHPs and thermal storage in the EU power system? • How does that compare to other flexibility options (hydro, EVs)? • How can this be modeled in a long-term planning context? Dispa-SET Model JRC EU-TIMES JRC models: 5th International Conference on Smart Energy Systems 2 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
JRC-EU-TIMES in a nutshell • Model horizon: 2005-2050 (2075) • Technology rich (300+) bottom-up energy system optimisation (partial equilibrium) model based on the TIMES model generator of the IEA • Designed for analysing the role of energy technologies and their innovation for meeting Europe's energy and climate related policy objectives • Electricity multi-grid model (high, medium and low voltage grid), tracking demand-supply via 12 time slices (4 seasons, 3 diurnal periods), and gas across 4 seasons • 70 exogenous demands for energy services 5th International Conference on Smart Energy Systems 3 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Dispa-SET in a nutshell • Unit commitment and dispatch model of the European power system • Optimises short-term scheduling of power stations in large-scale power systems • Assess system adequacy and flexibility needs of power systems, with growing share of renewable energy generation • Assess feasibility of power sector solutions generated by the JRC-EU-TIMES model • Technology mix from ProRES 2050 scenario used as inputs for Dispa-SET power plant portfolio 5th International Conference on Smart Energy Systems 4 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Dispa-SET 2.3: unit commitment and dispatch Wind, PV Objective Plant output Generation (MWh/h) (MWh/h) Minimise variable system costs • Constraints Power Plant on/off Hourly demand balances Demand • status (binary) (MWh/h) (power and reserve) Ramping constraints, minimum up and • Commodity Variable down times Prices costs/prices (EUR/t) Storage balances (PHS,CAES) • (EUR/MWh) NTC based market coupling • Plant data Emissions Curtailment of wind, PV and load • (MW, eff,…) (t CO2) shedding (optional) • Formulated as a tight and compact mixed integer program (MILP) • Implemented in Python and GAMS , solved with CPLEX 5th International Conference on Smart Energy Systems 5 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Dispa-SET 2.3: System structure & technology overview for a single node Exports Import Electric bus Non-CHP CHP Renewable Generators Generators Generators HPHS BATS Electric WAT HDAM demand Discharge Charge HROR SUN PHOT Transport bus STUR ICEN GTUR COMC WTON WIN WTOF Heat bus BEVS E-Mobility demand TES PEA WST GAS HRD LIG OIL NUC BIO GEO OTH Heating demand • Sector coupling options: P2H, P2V, V2G … 5th International Conference on Smart Energy Systems 6 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
JRC-EU-TIMES ProRES Scenario Used in this case study 6,000 • Ambitious scenario in terms of 5,000 additions of RES-E technologies • Significant reduction of fossil fuel use, 4,000 Capacity [GW] in parallel with nuclear phase out • CCS doesn’t become commercial 3,000 • Deep emission reduction is achieved with high deployment of RES, electrification of transport and heat 2,000 and high efficiency gains • Primary energy is about 430 Ej, 1,000 renewables supply 93% of electricity demand in 2050 0 2016 2030 2050 Scenario 5th International Conference on Smart Energy Systems 7 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Evaluating the “suitable” heating demand Heating and cooling needs are responsible for half of the EU28's energy consumption In this analysis, we consider only space heating and DHW for the residential and tertiary sectors: Industrial Tertiary Residential 0 500 1000 1500 2000 2500 3000 3500 Final Energy consumption for 2015 (TWh) Space Cooling Process Cooling Space Heating Hot Water Process Heating Cooking Non H&C Data source: JRC IDEES Database 5th International Conference on Smart Energy Systems 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Evaluating the “suitable” heating demand • We consider only the heating demand that fulfills the following conditions: • Medium heat demand density areas: > 120 TJ/km² • Maximum distance from a Power plant: 100 km JRC Power plant Pan-European Thermal database: Atlas Peta v4.3: Considered heat demand: 3520 TWh 690 TWh (630 TWh in 2050) 5th International Conference on Smart Energy Systems 9 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Modeling the flexibility resources linked to DH • CHP’s and TES Flexibility of CHP + thermal storage: 100% • Back-pressure 90% • no flexibility, based on P2H ratio, 80% installed heat capacity = 100% of % of total heat capacity 70% maximum hourly heat demand 60% • Extraction + TES Back-pressure 50% • dispatch flexibility, based on P2H Extraction + TES 40% ratio and Power Loss Factor 30% • additional flexibility, provided by 20% thermal storage unit (24H) 10% 0% NOFLEX THFLEX ALFLEX 5th International Conference on Smart Energy Systems 10 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Alternative flexibility options: Hydro • Flexibility of hydro units: • HROR units • no flexibility, based on availability factors • HDAM units Hydro units • dispatch flexibility, based on 100% inflows and accumulation capacity 90% • HPHS units 80% % of total hydro capacity • load shifting flexibility, pumped 70% storage units based on inflows 60% HPHS from upper and lower streams and 50% HDAM accumulation capacity 40% HROR 30% 20% 10% 0% NOFLEX THFLEX ALFLEX 5th International Conference on Smart Energy Systems 11 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Alternative flexibility options: electric vehicles • We assume that EVs constitute 75% of the whole vehicle fleet by 2050 • Flexibility by EVs: • Base case: • no flexibility, based on charging patterns, charging demand EV’s and V2G units integrated into the electricity 100% demand 90% • V2G 80% • Possibility for the system to use the % of total EV capacity 70% connected batteries. Restricted by 60% the charging paterns and the share EV 50% of the fleet that is connected to the P2G 40% grid and available for providing 30% flexibility 20% 10% 0% NOFLEX THFLEX ALFLEX 5th International Conference on Smart Energy Systems 12 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Example simulation results (Summer) – NOFLEX 5th International Conference on Smart Energy Systems 13 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Example simulation results (Summer) – THFLEX 5th International Conference on Smart Energy Systems 14 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Example simulation results (Summer) – ALFLEX 5th International Conference on Smart Energy Systems 15 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Flexibility - load shifting (Fuel / Technology) 1.6 100% 90% 1.4 80% 1.2 70% 1 Energy [PWh] 60% BIO_STUR GAS_COMC 0.8 50% GAS_GTUR GAS_STUR 40% OTH_BEVS 0.6 WAT_HPHS 30% 0.4 20% 0.2 10% 0 0% NOFLEX THFLEX ALFLEX NOFLEX THFLEX ALFLEX Scenario Scenario 5th International Conference on Smart Energy Systems 16 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
CO 2 Emissions and share of renewables 1000.00 100% 90% 900.00 80% 800.00 Generation by fuel type 70% 700.00 60% 600.00 CO2 [milion t] 50% 500.00 40% 400.00 30% 300.00 20% 200.00 10% 100.00 0% NOFLEX THFLEX ALLFLEX 0.00 NOFLEX THFLEX ALFLEX RES Non-RES NUC Scenario 5th International Conference on Smart Energy Systems 17 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
Effect of flexible technologies on curtailment and load shedding Curtailment Load Shedding Curtailment Max Curtailment Load Shedding Max Load Shedding 1800 1.5 25 0.18 0.16 1600 1.45 20 1400 0.14 Max Load Shedding[TW] Max Courtailment [TW] Load Shedding [TWh] Courtailment [TWh] 1200 0.12 1.4 15 1000 0.1 800 0.08 1.35 10 600 0.06 400 0.04 1.3 5 200 0.02 0 1.25 0 0 NOFLEX HYFLEX EVFLEX THFLEX ALFLEX NOFLEX HYFLEX EVFLEX THFLEX ALFLEX Scenario Scenario 5th International Conference on Smart Energy Systems 18 4th Generation District Heating, Electrification, Electrofuels and Energy Efficiency
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