Modelling of reserve procurement and exchange of balancing services in Northern Europe: Real-time dispatch
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1 1 International workshop on Exchange of balancing services - Market design and modelling Modelling of reserve procurement and exchange of balancing services in Northern Europe: Real-time dispatch Hossein Farahmand Norwegian University of Science and Technology (NTNU)
2 2 Outlines Simulation Procedure (sequential market clearing) Day-ahead dispatch and reserve procurement Real- time activation of reserve resources
3 3 Modelling the integrated multinational balancing market using PSST 1 Day-ahead dispatch: Optimum dispatch of generation at the beginning of each PTU, reserve procurement Real-time dispatch : activation of regulating power Power (MW) reserve. Scheduled generation in day-ahead deispatch Real-time demand PTU-1 PTU-2 PTU-3 PTU-4 PTU-5 Hour 1-Power System Simulation Toolbox, M. Korpås, L. Warland, J. O.. Tande, K. Uhlen, K. Purchala, and, S. Wagemans, rid modelling and power system data, TradeWind report D3.2, Dec. 2007
4 4 Simulation Procedure Power flow case description enerator capacities enerator cost curves (marginal cost) Reservoir levels (Hydro) Reserve Requirements Time dependent Load series Wind series Inflow (hydro) Water values Real-time Imbalance Scenario Demand forecast error Wind forecast error Day-ahead common market ( the whole European Continent) Scheduled Dispatch Water Values Real-time System Balance (Northern Continental Europe) Production cost Optimal production dispatch Optimal HVDC lines flow Power Exchange between areas Balancing Cost Optimal dispatch of regulating objects Optimal exchange of balancing services.
5 5 Day ahead market Common market for the whole European continent including the Nordic area, the Central European system, reat Britain and Ireland Reserve procurement is done simultaneously with the day-ahead dispatch, it is limited to the Northern European area. A DC optimal power flow (DCOPF) is used for dayahead dispatch The objective is to minimize the operating cost We used an LP based algorithm to avoid excessive calculation times.
6 6 Regulating reserve resources Non-regulating generation Nuclear Lignite-Coal Wind Renewable other than wind Regulating generation as Oil Oil-as Hard-Coal Hydro Pump storage
7 7 Thermal units Start-up cost d d x τ [ ] x d τ [ ] x τ [ ] 1, g, 0,1 2, g, 0,1 3, g, 0,1 0 th P g th, d P g, τ th p g ( ) th, d th, d th, d 1, g, τ 2, g, τ 3, g, τ th, d th, d th, d 1, g, τ 1, g, τ 1 gt, th, d th, d 2, g, τ 3, g, τ ( ) p = x P + x P P g, τ T th, d th, d th th, d th th g, τ 1, g, τ g 2, g, τ g g x x + x g, τ T x x strt g, τ T x + x 1 g, τ T Numerical tools for offshore grid and wind farm electrical design Trondheim
8 8 Challenge Mid-merit unit Start-up cost: 5000 Marginal cost: 20 /MWh Peak unit Start-up cost: 1000 Marginal cost: 40 /MWh h=1 h=2 h=3 h=5 h=6
9 9 Case study for reserve procurement Norway Sweden Finland NO3 NO2 NO1 SE3 SE2 SE1 F2 F1 Denmark West DK_W DK_E Denmark East Amprion NL The Netherlands Subarea Amp EnB W EnBW trans 1 trans 2 trans 3 transpower 50 Hetrz 50 Hertz Control Area AC lines HVDC lines
10 10 Different levels of regulating NO3 market integration SE3 F2 Case1: before merging of erman control areas NO2 NO1 DKW DKE SE2 SE1 F1 Case2: after merging of erman control areas Case3: System wide procurement Amprion NL D5 D2 D1 D3 50 Hertz D6 EnBW D4 transpower
11 11 Results of simulation Procured upward regulating reserve Hour1 Hour 2 req. Case 1 Case2 Case3 Case 1 Case2 Case3 SE NO Fi DKE DKW Sum Hertz trans Amp EnBW NL Sum
12 12 Available Transmission Capacity From To Capacity case 3 available capacity SE2 DKW NO1 DKW NO1 NL DKE DKW DKW: =248 MW = 248 MW SE1 Trans DKE 50 Hertz sum 367 DKW Trans Numerical tools for offshore grid and wind farm electrical design Trondheim
13 13 System Balancing Exchange of balancing services Market design and modelling, 28 October 2010
14 14 Real-time dispatch Minimum deviation from a base system state is calculated to deal with real time deviation (Incremental DC OPF) N N u u d d i i i i i= 1 i= 1 Min F = c P + c P ~ Bus i P = Pi P = P P max min = P max i min i Upward generator downward generator ~ P =P u i P =P -P max max i i P = 0 min ~ P =P max -P i ΔP D d i P =0 P =P -P min min i i
15 15 Balancing Cost Operating Point 55 /MWh 50 /MWh 45 /MWh P down P up
16 16 Flow Based Activation of Reserves in the Nordic Power System Activation of reserve resources in the Nordic power system. The algorithm Incremental DC Power Flow (IDC_OPF) considers the effect of transmission congestion and losses. The results of this model are compared with today s practice for some cases of up- and downward regulation, and a potential for the cost reduction is observed. 1- H. Farahmand, S. Hosseini,. Doorman, O. Fosso, Flow Based Activation of Reserves in the Nordic Power System, IEEE eneral Meeting, Minneapolis, 2010
17 17 Principal Method Day-ahead market is modelled by DC-OPF for the whole European on an aggregated level Balancing market is modelled with: The IDC_OPF formulation. The transmission congestion The transmission losses. Today s practice is modelled in two steps Calculation of the market dispatch based on the area model Inter-area congestion is relieved by counter trading. This model is approximated by using a DC-OPF model within the zone
18 18 Results Today s practice of system operation is not optimal (common merit order list), Congestion is not handle in an optimum way Large regulation steps are taken on a few generators Losses are not taken into account In IDC-OPF the cost of losses and congestion is explicitly considered. Instead of using one or a few generators for the regulation, we uses four to six generators in the optimal solution. Introducing AC makes the implementation of the problem feasible.
19 19 Future Scenarios (2020)
20 20 Future work Simulation of the future scenarios => grid connection and system integration of large offshore wind farms Update the water value based on the result of extended EMPS model Use the momentary parameter in real-time dispatch (enerators ramp-rate and HVDC ramping )
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