The Impact Of Renewable Energies On EEX Day-ahead Electricity Prices
The impact of renewable energies onEEX day-ahead electricity pricesFlorentina ParaschivMichael SchürleUniversity of St. GallenInstitute for Operations Researchand Computational FinanceComputational Management ScienceLisbon, 29th – 31st May 2014
Impact of renewableenergies on electricityprices - Page 2AgendaResearch question: Did the promotion of renewable energies inGermany lead to lower electricity prices as sustainable energies(wind, photovoltaic etc.) have low or zero marginal costs?In this talk: Overview of energy policy regulations with respect to use ofrenewable energies Fundamental variables that drive electricity prices on the dayahead market Load profiles differ for different times of the day, thus the model isestimated individually for each hour Estimation approach Results and interpretation
Impact of renewableenergies on electricityprices - Page 3Promotion of renewable energies in Germany Renewable Energy Act (EEG, 2000):– Producers of renewable energies (wind, PV etc. ) receive aguaranteed compensation (technology dependent feed-in tariffs)– Priority is granted to renewable energies– The additional costs of renewable energy sources are apportioned toenergy suppliers, which pass it ultimately to end consumers throughthe EEG surcharge In the first phase of the implementation (2000 – 2009), a significantincrease in electricity production from renewable energy sourcescould be observed Especially the high volume of PV installations made feed-in tariffsunbearable; as a consequence they were reduced Simultaneously, the EEG surcharge increased due to theincreasing production from renewable energy sources:– Its calculation is based on the difference between feed-in tariffs andmarket prices which dropped significantly due to the merit order effect– End consumers finance the extension of renewable energies
Impact of renewableenergies on electricityprices - Page 4Promotion of renewable energies in Germany In a second phase (2009 – 2011), it became clear that thetransmission grid is not capable to handle the growing supply offluctuating renewable energies:– Most wind capacities are installed in the north of Germany,energy consumption is concentrated in the south– In regions with high supply of renewables, modern and efficientpower plants are shut down to avoid a potential grid breakdown whilein regions where the grid is not fully developed, inefficient (oil-fired)plants must run to stabilize the grid In case of excess supply of electricity, prices can fall down to zeroor even below:– Renewable energies are fed in with priority– A large conventional (nuclear or coal-fired) plant is less flexible andcannot be shut down or ramped up immediately and only at highcosts; therefore operators are willing to accept a negative price Since demand and supply have to match and storage capacitiesare limited, large price fluctuations and extreme spikes may occur
Impact of renewableenergies on electricityprices - Page 5Merit order curve Available sources of energy are ranked in ascending order of theirmarginal costs of production Plants with the lowest marginal cost are the first to be broughtonline, those with the highest marginal costs are the last The plant with the highest marginal costs that is required to meetthe demand determines the market clearing tynuclearlignitecoalhardcoalnaturalgasoil
Impact of renewableenergies on electricityprices - Page 6Merit order effect Renewable energies have lower marginal costs than traditionalsources (wind: 4 /MWh, nuclear: 10 /MWh, lignite: 15 /MWh,gas: 40 /MWh) In times of high feed-in from renewable energies, they replaceconventional plants, which should lead then to lower prices on theday-ahead market (grid operators are obliged to market electricityfrom renewable turalgasoil
Impact of renewableenergies on electricityprices - Page 7Electricity production in Germany by source [%] There was a significant increase in the use of renewable energiesduring the investigated period This caused large changes in the supply mix We have to restrict the following analysis to the time after 2010due the availability of certain data (e.g., PV infeed)
Impact of renewableenergies on electricityprices - Page 8Fundamental variables driving electricity prices Demand for electricity could be estimated from the vertical net load(VNL) published by all four transmission system operators (TSOs) The VNL represents the sum of all power which is transferred fromthe high voltage transmission grid to the next lower level, i.e., thedistribution grid Electricity from renewable sources is not fed into the high voltagetransmission grid but directly into the medium voltage transmissiongrid; therefore the VNL does not include wind and PV energy The total demand should be calculated asDemandt VNLt Total Wind Infeedt Total PV Infeedt Since day-ahead prices are modeled, we have to take into accountexpected (rather than realized) demand The latter is obtained from an individual model (ARMAX/GARCH):– Seasonal effects modeled by dummy variables, weather information– Each hour of the day modeled separately
Impact of renewableenergies on electricityprices - Page 9Fundamental variables driving electricity prices Supply: As fundamental variables we take into account– prices for coal, gas, oil, CO2 emission allowances,– expected infeed from renewable energies (wind, PV),– expected power plant availability Learning effects:– Price of corresponding hour on previous day– Average price of all hours on previous day Price volatility: Standard deviation of hourly prices of last 5 days List of all variables and data granularity:
Impact of renewableenergies on electricityprices - Page 10Estimation There has been a shift in the merit order curve due to theincreasing infeed from renewable sources We expect that the traditional fuels have a decreasing impact onelectricity prices while the importance of renewables goes up To assess the change in the sensitivities of prices to the variousfundamentals, we choose a model with time-varying coefficients forthe electricity price yi,t at each hour of the day i 1, , 24:y i ,t z 'i ,t γ i ,t ε i ,tmeasurement equation γ i ,t γ i ,t 1 ηi ,ttransition equationγ i ,t : (γ i ,1,t , γ i ,2,t , , γ i ,k ,t )'ηi ,t : (ηi ,1,t ,ηi ,2,t , ,ηi ,k ,t )'ε i ,t N (0,σ i ), ηi ,t N (0, Ωi ) zi is the vector of the previously described exogenous variables The regression coefficients are stochastic variables that followrandom walks and are estimated with a Kalman filter approach
Impact of renewableenergies on electricityprices - Page 11Results: Learning (1) Results are shown here only for hours 3 (night), 12 (noon) and 18(evening), as these are representative for different times of the day Negative coefficients of lagged spot price for specific hour revertslevel of electricity price for that hour on the next day
Impact of renewableenergies on electricityprices - Page 12Results: Learning (2) Positive coefficients of lagged average spot (signal from last day) Consistent with discussion in literature: one would expect a positiveelasticity of spot prices to lagged prices:– Market agents tend to reinforce previously successful offers in themarket which preserves price level– Signaling between agents keeps prices moving in the same direction
Impact of renewableenergies on electricityprices - Page 13Results: Volatility Coefficient changed from negative to positive after 2012 Increase may be associated with higher infeed of volatilerenewable energies Impact of volatility on prices can be interpreted as compensationfor risk Hedging of price risk via spot market became more expensive
Impact of renewableenergies on electricityprices - Page 14Responses to fuel prices: Coal It strongly depends on the hourly load profile when productioncapacities based on coal, gas and oil are in use More distinct marginal effects for hours with high demand, inparticular hour 18 (production mainly coal based) Coal is still most relevant fuel for electricity production in Germany,therefore we observe less price adaption w.r.t. coal than for gas
Impact of renewableenergies on electricityprices - Page 15Responses to fuel prices: Gas and oil Gas and oil fired plants run in hours of high demandWe observe higher marginal effects for hour 12 (gas: see right axis)Continuous price adaption process, coefficients quite variableSince 2011 decrease in coefficients for gas particularly for hour 12due to growth in PV infeed (highest around noon)
Impact of renewableenergies on electricityprices - Page 16Response to CO2 prices Continuous price adaption process to prices of emissionallowances Marginal effect is clearly higher for evening and night hours whenproduction is mainly coal based (see left axis) Adaption of electricity prices to CO2 prices can be explained by thefact that coal fired plants pollute more than gas and oil fired ones
Impact of renewableenergies on electricityprices - Page 17Response to demand and supply Apparently no substantial price adaption to demand and supply(i.e., power plant availability, PPA) Model is estimated individually for each hour of the day Load is (in the short run) inelastic Demand and PPA are easily predictable
Impact of renewableenergies on electricityprices - Page 18Response to renewable energies: Wind Negative coefficients imply that wind infeed decreases prices Variable price adaption process, particularly at night hours During the night, an excess of produced electricity meets a lowdemand Then, even negative prices may occur which are caused to a largeextent by wind infeed
Impact of renewableenergies on electricityprices - Page 19Response to renewable energies: PV Again, the negative sign implies that PV infeed decreases prices The coefficients fluctuate less since PV infeed in a certain hour ismore constant than wind The impact on the price reduction is higher at noon since thesunshine is most intense then while demand is large
Impact of renewableenergies on electricityprices - Page 21Conclusions and outlook Sensitivities of day-ahead electricity prices to the fundamentalvariables coal, gas, oil and renewable energies vary over time The increasing infeed of renewable energies (wind, PV) led to adecrease in prices on the day-ahead market in Germany, due tothe merit order effect There is a continuous adaption process of electricity prices tomarket fundamentals Our results show the importance of linking electricity spot prices tomarket fundamentals; a purely stochastic model can be too simple The promotion of renewable energies simulated their fastdevelopment Excess supply from renewable energies in the north of Germanymust be efficiently distributed to regions with excess demand;this requires an extension of the transportation grid Production, transportation and storage cannot be treated separately and must be considered together in future promotion schemes
electricity prices while the importance of renewables goes up To assess the change in the sensitivities of prices to the various . Then, even negative prices may occur which are caused to a large extent by wind infeed . Impact of renewable energies on electricity prices - Page 19 .
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