Competitiveness and System Value of Electricity Generation Technologies The Brazilian Case LUCIANO LOSEKANN DIOGO LISBONA EDMAR DE ALMEIDA
Energy Planning questions How to compare different types of electricity generation technologies? What is the value of the electricity generated by each source?
Traditional answer: levelized cost of electricity LCOE annualized capital cost internalizing externalities LCOE = discount rate capital costs + fixed O&M annual expected generation hours + variable O&M + fuel + carbon price $/MWh projected capacity factor Treats electricity as a homogeneous good (subject to single price law) Academics, policy makers, and industry actors compare different sources in terms of LCOE
LCOE is based on evident misconception: electricity is not a homogeneous good It is not economically viable store electricity on a large scale Real-time balancing between supply and demand Renewable energy diffusion Electricity can be generated both through dispatchable and nondispatchable sources (availability depends on the weather) Electricity is a heterogeneous good in space and time dimensions Value depends on when, where, and how it is produced Joskow (2011), Boresntein (2012), Hirth (2013), Schmalensee (2016), Finon (2016), and many others recognize that we must compare different types of technologies according to their expected generation profiles and respective market values
Benefit-cots analysis (LACE LCOE) levelized avoided cost of electricity (LACE) different time periods expected generation weighted by marginal price backup cost (LCOE of SCCT) capacity contribution for peak hours LACE = $/MWh t=1 T marginal generation price t dispatched hours t + capacity payment capacity credit annual expected generation hours projected capacity factor LACE: expected revenue from energy market + capacity market Benefit (marginal value) = avoided cost by the displacement of more costly dispatches and by avoided additional capacity reserve US EIA annually publishes estimates for several sources since 2013
Variable renewable energy (VRE) Avoided costs or additional (hidden) costs? In traditional power systems (not designed for VRE), a high VRE penetration level imposes: DYNAMIC EQUILIBRIUM PROBLEMS (SYSTEM ADEQUACY) MERIT-ORDER EFFECT SELF-CANNIBALIZATION EFFECT STATIC EQUILIBRIUM PROBLEMS (REAL-TIME BALANCING) GRID CONSTRAINTS
VRE: a new protagonist Prominence imposes challenges LOW CAPACITY CREDIT LOAD (GW) LOAD DURATION CURVE NET LOAD DURATION CURVE BASELOAD REDUCTION OVERPRODUCTION HOURS OF ONE YEAR
From cost to value Assimilating integration costs All sources are subject to integration cost (even if negative = benefit) It is not a market failure, but it is inherent to any kind of source In the policy debate is often suggested that once the cost of a source reaches a certain level (in relation to the wholesale average electricity price or the grid parity), this source becomes competitive This is completely misleading! Given the integration cost recognition, a certain source is never competitive ad infinitum At a certain cost level, a certain AMOUNT of a source power is competitive
System Value Approach and the Brazilian case The IEA advocates and spreads the system value approach in its reports The IEA has also studied the Brazilian case, BUT Neglected the comparison method deployed in centralized auctions to selected the source of new capacity
BRAZIL SOUTHEAST/MIDWEST HYDRO RESERVOIRS = 212 TWh POWER CONSUMPTION TWh SOURCE: CCEE, ONS, EPE
High complementarity between hydro and VRE Lower Integration Costs? SOURCE: CCEE
Expansion through centralized auctions SOURCE: CCEE
Cost-benefit Index (ICB) Compares and selects different sources that are contracted by "availability contracts" in the expansion auctions Thermal power (NG, coal, oil products, biomass), wind, and solar Objective: estimate future operation costs and availability costs (the cost of new capacity contracted and not dispatched in the future) ICB captures the system value of backup thermal complementation and the complementarity of VRE in face of hydro predominance Calculation depends on operation marginal cost (OMC) projected 2000 monthly hydrological series (values of OMC) Horizon of simulation: 60 months
Cost-benefit Index (ICB) calculation COP = i=1 60 2000 j=1 [CVU (GERA i,j INFLEX) #hours] 12 i j = Fixed Revenue CEC = i=1 60 2000 j=1 [PLD (GF GERA i,j ) #hours] 12 i j ICB Fixed Costs + E Operation Costs + E Availability Cost 8760 x Physical Guarantee $/MWh estimated benefit of capacity for the future supply (reduces capacity credit by taking into account expected capacity factor)
Energy contracted in all expansion auctions GWavg 6% 15% 7% 22% 12% 7% 5% 46% 18% 1% 18% 6% 36% SOURCE: CCEE
Energy contracted in auctions with ICB GWavg 16 GWavg [Oil 33% Hydro 30%] 10 GWavg [NG 35% Wind 33%] SOURCE: CCEE
Integration Costs in Brazil backward-looking or forward-looking? BACKWARD-LOOKING ICB is in accordance with hydrological variability favored flexible thermal power plants (low fixed cost and high variable cost) and complementary sources to hydropower (wind) But ICB is insensitive about VRE variability Does not account for short-term variability, neither the location of power plants System is changing transformations point to a new operation paradigm FORWARD-LOOKING Loss of the hydro reservoirs regularization degree Higher annual depletion higher thermal complementation Higher penetration level of VRE (new dimension of variability) Short-term variability (cost) must be internalized Flexibility (benefit) must be recognized (pricing)
System transformation marginal value of water (shadow electricity price) is changing water tank is losing importance due to load increases and stagnation of storable energy SOURCE: ONS
After all, what is the moral of the story? We cannot compare different sources without taking into account integrations costs For expansion purposes, we must look to dynamic integration costs The big challenge of system value approach lies in correctly identifying, at an appropriate time, the ongoing system transformations
Thanks for your attention! lucianolosekann@id.uff.br