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Coordination of the location and time of investment of generation and transmission in a liberalised power system Jean-Michel Glachant (and Vincent Rious) Loyola de Palacio Chair & Florence School of Regulation European University Institute in Florence jean-michel.glachant@eui.eu 30 th July 2010 11th ACCC Regulatory Conference: Surfers Paradise Robert Schuman Centre for Advanced Studies Florence School of Regulation & Loyola de Palacio Chair
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FSR and Loyola de Palacio Chair on Energy Policy Outline Need for coordination between G & T Tool #1 = locational signals Tool #2 = anticipation Scope for maximisation of social welfare? Conclusions
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FSR and Loyola de Palacio Chair on Energy Policy Coordinated gen° and trans° investments by an integrated utility G_Inv._Cost E < Min: Gen Invst Cost + Fuel Cost + Trans Invst Cost Integrated Utility Easy to know the cheapest investment strategy Location + time of investment G_Inv._Cost W
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FSR and Loyola de Palacio Chair on Energy Policy Unbundling and the need for coordination < Min: Gen Investment Cost + Fuel Cost + Tariff G_Inv._Cost W + Trans cost > Suboptimal location ! Locational signals Liberalised power system Inefficient coordination G_Inv._Cost W G_Inv._Cost E
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FSR and Loyola de Palacio Chair on Energy Policy Unbundling and the need for coordination Liberalised power system >> Prompts investors to choose generation technologies with short construction lead time Right of way of powerlines facing increasing oppositions ~ 7 years to build a powerline from study to construction itself because of administrative agreement >> 5 years! Generation technology Time to build (year) Notional size (MW) CCGT2200-800 Wind onshore225 offshore2100 Coal4-5200-1600 Nuclear5-71600 Congestion while the network is not upgraded 5
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FSR and Loyola de Palacio Chair on Energy Policy Transmission planning and generation location in a liberalised power system A story of chicken and egg The TSOs need to know generation location to develop the network The generators may be constrained because of network congestion 6
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FSR and Loyola de Palacio Chair on Energy Policy Outline Need for coordination between G and T Tool #1 = locational signals Tool #2 = anticipation Scope for maximisation of social welfare? Model and results Conclusions
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FSR and Loyola de Palacio Chair on Energy Policy Coordination with short term locat. signals GIC W GIC E < Min Gen Investment Cost + Fuel Cost + Tariff PN W PN E < Network constraints Nodal pricing
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FSR and Loyola de Palacio Chair on Energy Policy GIC W GIC E < Min Gen Investment Cost + Fuel Cost + Tariff PN W PN E < Pb: lumpy transmission investment Nodal pricing marginal signals not enough to achieve coordination Coordination with short term locat. signals Network constraints Lumpiness
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FSR and Loyola de Palacio Chair on Energy Policy Min Gen Investment Cost + Fuel Cost + Tariff + Tariff Coordination with long term locat. signals Tariff W Tariff E > GIC W GIC E < + Tariff = 0 Network tariffs
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FSR and Loyola de Palacio Chair on Energy Policy Outline Need for coordination between G and T Tool #1 = locational signals Tool #2 = anticipation Scope for maximisation of social welfare? Model and results Conclusions
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FSR and Loyola de Palacio Chair on Energy Policy Problem Coordination of location of generation investments with lumpy transmission investments Efficiency of network tariffs –Average participation tariff = each Gen. pays for her traced share of used lines Thought as a good tariff in economic literature –Game theory (Shapley value: fair & symmetric) Not been evaluated yet in interaction with investments (Ignacio!) –Jointly implemented with nodal prices
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FSR and Loyola de Palacio Chair on Energy Policy Structure of the model One generator (!) –Competitive setting -;) Min Gen° invest t cost + fuel cost + tariff One TSO (at least!) –Benevolent -;) Min Trans° invest t cost + cong° cost Influenced by market design –Nodal pricing or Redispatch –No tariff or Average participation tariff Determined by the generators choice Network costs
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FSR and Loyola de Palacio Chair on Energy Policy Characteristics of the model Good news for simplicity of the model -;) Optimistic frame -;) –No uncertainty TSO perfectly informed of generators decision set Generator perfectly informed of TSOs decision set Bad news for simplicity of the model -;( Difficulty to solve -;( –Double optimization No sequential optimization The 2 functions optimized at the same time –Non linear problem Lumpiness of transmission investment Average participation tariff
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FSR and Loyola de Palacio Chair on Energy Policy Optimization algorithm for a realistic model! 2%/y 200 MW 400 MW Problem hard to solve
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FSR and Loyola de Palacio Chair on Energy Policy Optimization algorithm for a realistic model! 2%/y 200 MW 400 MW Problem hard to solve –Solved using an heuristic Genetic algorithm System investment strategies as individuals With reproduction and random mutation process to better off from one period to another
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FSR and Loyola de Palacio Chair on Energy Policy Optimization algorithm Use of a Pareto frontier to find the investment strategies equilibria of our double optimization problem Simulated population Measure of the coordination reached by the points on the Pareto frontier evaluation in terms of social cost Value of the investment strategy for the Generator Value of the investment strategy for the TSO Investment strategies generated at random by the genetic algorithm Pareto Frontier Investment strategies = set of generation + transmission investments
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FSR and Loyola de Palacio Chair on Energy Policy Average participation tariff Results Nodal pricing –Weak effect on coordination –Even in favorable cases: No economies of scale Perfect knowledge of economic signals Interaction between –network investments lumpy –locational signals Locational signals with bounded efficiency
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FSR and Loyola de Palacio Chair on Energy Policy Nodal pricing –Weak effect on coordination –Even in advantagous cases No economies of scale Perfect anticipation of economic signals Results Average participation tariff –Coordination always improved –But suboptimal coordination Not enough locational incentives Or too much in some cases ! Interaction between –locational signals and –network investments lumpy Locational signals with limited efficiency
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FSR and Loyola de Palacio Chair on Energy Policy Results Network tariff more important than nodal pricing for efficient location of G investment Interaction between –locational signals and –network investments lumpy Locational signals with limited efficiency
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FSR and Loyola de Palacio Chair on Energy Policy Outline Need for coordination between G and T Tool #1 = locational signals Tool #2 = anticipation Scope for maximisation of social welfare? Model and results Conclusion #1
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FSR and Loyola de Palacio Chair on Energy Policy Coordination with locational signals? No optimal coordination with locational signals Nodal pricing + average participation tariff –Because of lumpiness of transmission investmentlumpiness –Even if improved coordination (so locational signals are needed) –And average participation tariff more efficient than nodal pricing for efficient location of investment
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FSR and Loyola de Palacio Chair on Energy Policy Coordination with locational signals? These signals = transmit information But limited to current grid and its current use And (+) many other locational constraints existing for generators: access to water, to fuel, to land, to social acceptance (NIMBY) lasting congestions need to develop the network
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FSR and Loyola de Palacio Chair on Energy Policy Outline Need for coordination between G and T Tool #1 = locational signals Tool #2 = anticipation Scope for maximisation of social welfare? Model and results Conclusion
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FSR and Loyola de Palacio Chair on Energy Policy Two alternative behaviors for the TSO Reactive behavior –Waits for generation connection request to study the need of transmission investments Proactive behavior –Anticipates generation connection request in areas with exploitable energy sources Gas Wind –Starts first-step investment process as to get administrative green lights already agreed when generators will request for connection 25
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FSR and Loyola de Palacio Chair on Energy Policy Pros & cons of the two alternative behaviors Reactive behavior * No trsm investment cost put at risk **BUT excessive congestion if CCGTs or wind farms connect while network is still to be upgraded Proactive behavior * No excessive congestion put at risk **BUT proactive behavior is itself costly because (if generation finally doesnt come) TSO did already: the study to upgrade the network And went trough all procedures to obtain the administrative green lights to build the line 26
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FSR and Loyola de Palacio Chair on Energy Policy Unbundling and the need for coordination Liberalised power system >> Prompts investors to choose generation technologies with short construction lead time Right of way of powerlines facing increasing oppositions ~ 7 years to build a powerline from study to construction itself because of administrative agreement >> 5 years! Generation technology Time to build (year) Notional size (MW) CCGT2200-800 Wind onshore225 offshore2100 Coal4-5200-1600 Nuclear5-71600 Congestion while the network is not upgraded 27 Need for coordination between generation and transmission investments
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FSR and Loyola de Palacio Chair on Energy Policy Outline Need for coordination between G and T Tool #1 = locational signals Tool #2 = anticipation Scope for maximisation of social welfare? Model and results Conclusion
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FSR and Loyola de Palacio Chair on Energy Policy Problem Efficiency of anticipating generation connection for the TSO in terms of minimization of her total network costs? –If no anticipation congestion for quite long period while network must be upgraded –If TSO anticipes the first-stage costs costly if anticipated generators do not connect One must arbitrate between these two costs weighed by a probability for the connection of generation (been evaluated by an expert panel « à dire dexpert ») 29
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FSR and Loyola de Palacio Chair on Energy Policy Construction Generation Investment Year CU(d) CW(d) Transmission Investment d 0 Study, admin. proced. construction Investment sequencing with reactive TSO 30 Excessive congestionOptimal value for network capacity
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FSR and Loyola de Palacio Chair on Energy Policy Construction Year Study, admin. proced. construction Generation and Network Investments CU(0) 0 Investment sequencing with proactive TSO 31
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FSR and Loyola de Palacio Chair on Energy Policy Probability limit and condition for proactive TSO with known first-stage costs 32 First-stage costs = 10% of transmission investment costs
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FSR and Loyola de Palacio Chair on Energy Policy With first-stage costs = 50% of transmission investment costs Still efficient for the TSO to be proactive when 40% probability for the connection of a new plant Probability limit and condition for a proactive TSO with unknown first-stage costs
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FSR and Loyola de Palacio Chair on Energy Policy Outline Need for coordination between G and T Tool #1 = locational signals Tool #2 = anticipation Scope for maximisation of social welfare? Model and results Conclusions
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FSR and Loyola de Palacio Chair on Energy Policy Conclusion (1/4) A model to evaluate the efficiency of anticipating plants investment to minimize the total network costs Illustration on simple realistic examples (like CCGT or wind farms) –Efficient to anticipate the connection of power plants for the TSO –Planning in advance network reinforcement –Reduce congestion costs 35
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FSR and Loyola de Palacio Chair on Energy Policy Conclusion (2/4) –Efficient for TSO to anticipate the connection of new generator All the more that (a/) –Proactive behavior favours dialog between TSO and market participants about planning assumptions Facilitates coordination through sharing information Facilitates dialog and acceptability from local populations 36
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FSR and Loyola de Palacio Chair on Energy Policy Conclusion (3/4) All the more that (b/) –Possibility to send potential locational signals related to the anticipated network Volume signals: new generation capacity that will not constrain the grid Tariff and price signals: potential levels of locational network access fees and energy prices for different network and generation scenarios 37
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FSR and Loyola de Palacio Chair on Energy Policy Conclusion (4/4) All the more that (c/) –Possible to incentivise TSOs to be proactive Make them bear a part of congestion costs Example in France: the TSO compensates the wind farms when they have a curtailment obligation for more than 3 years 38
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FSR and Loyola de Palacio Chair on Energy Policy Future research on network anticipation Feedback effects with locational signals Effects of (milestones payment) in connection tariffs to create increasing locational commitment from generator 39
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FSR and Loyola de Palacio Chair on Energy Policy Conclusion of conclusions Tool 1- Coordination of generation and transmission investment with signals because of intrinsic lumpy network cost structure –information sharing with Generation –Necessary but not sufficient locational signal when generation quicker to develop than the network
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FSR and Loyola de Palacio Chair on Energy Policy Conclusion of conclusions Tool 2- Importance of information / consultation platform for network planning –Information sharing building of common knowledge about possible future(s) more certainty for investors –All the more needed to integrate new generation technologies new location, new network usage
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FSR and Loyola de Palacio Chair on Energy Policy Thats it: Even in a Surfers (non)Paradise more coordination between Gen. and Transmission is not necessarily a luxury…
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Jean-Michel Glachant Loyola de Palacio Chair & Florence School of Regulation European University Institute in Florence jean-michel.glachant@eui.eu Robert Schuman Centre for Advanced Studies Florence School of Regulation & Loyola de Palacio Chair Thank you for your attention Questions ? Comments ? Coordination of the location and time of investment of generation and transmission in a liberalised power system
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