A Multifactor Approach to Modelling the Impact of Wind Energy on Electricity Spot Prices

Rowińska, Paulina A.; Veraart, Almut E. D.; Gruet, Pierre

doi:10.2139/ssrn.3110554

Cited by 8 publications

(8 citation statements)

References 30 publications

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“…Proposition 9. Let Assumption 8 hold true, and let φ i * denote the optimal position of the i th agent in the N -player complete information setting, given by (5), and by φ M F,i * the optimal position in the mean field setting, given by (24). Then, for all N ≥ 1, the differences between the strategy of a single agent, the aggregate strategy and the equilibrium price in the N -agent model and the corresponding quantities in the mean-field model can be bounded as follows.…”

Section: Assumptionmentioning

confidence: 99%

“…Karanfil and Li [18] draw similar conclusions from an empirical study of the Danish market, and exhibit the impact of renewable energies on prices, bid-ask spread and volatility. Gruet, Rowińska and Veraart [24] establish a negative correlation between the wind energy penetration and the day ahead market prices. They also show that taking into account wind energy generation improves goodness of fit in their multifactor model for the German and Austrian day ahead market.…”

Section: Introductionmentioning

confidence: 96%

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Price formation and optimal trading in intraday electricity markets

Féron¹,

Tankov²,

Tinsi³

2020

Preprint

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We develop a tractable equilibrium model for price formation in intraday electricity markets in the presence of intermittent renewable generation. Using stochastic control theory we identify the optimal strategies of agents with market impact and exhibit the Nash equilibrium in closed form for a finite number of agents as well as in the asymptotic framework of mean field games. Our model reproduces the empirical features of intraday market prices, such as increasing price volatility at the approach of the delivery date and the correlation between price and renewable infeed forecasts, and relates these features with market characteristics like liquidity, number of agents, and imbalance penalty.

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Section: Assumptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Price formation and optimal trading in intraday electricity markets

Féron¹,

Tankov²,

Tinsi³

2020

Preprint

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show abstract

“…The CARMA(2,1) kernel with a symmetric NIG process for the stationary law also models the prices well. The arithmetic LSS model ( 28) is also considered in 2020 by Rowińska et al [176] with the addition of a long-term factor which is a Lévy martingale process. The estimation of the model is then carried out on spot prices and FPDs in Epex and EEX.…”

Section: Semi-stationary Lévy Processesmentioning

confidence: 99%

A survey of electricity spot and futures price models for risk management applications

Deschatre¹,

Féron²,

Gruet³

2021

Preprint

Self Cite

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This review presents the set of electricity price models proposed in the literature since the opening of power markets. We focus on price models applied to financial pricing and risk management. We classify these models according to their ability to represent the random behavior of prices and some of their characteristics. In particular, this classification helps users to choose among the most suitable models for their risk management problems.

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“…In all of the aforementioned papers on price impact models dealing with singular stochastic controls (Al Motairi and Zervos 2017;Becherer et al 2017Becherer et al , 2018Ferrari and Koch 2019;Guo and Zervos 2015), the agents' actions can lead to an immediate jump in the underlying price process, whereas in our setting, it cannot. Our model is instead analogous to , , which show how to incorporate a market impact due to cross-border trading in electricity markets, and to Rowińska et al (2018), which models the price impact of wind electricity production on power prices. In these latter models, price impact is localized on the drift of the power price.…”

Section: Introductionmentioning

confidence: 99%

Optimal installation of renewable electricity sources: the case of Italy

Awerkin

Vargiolu

2021

Decisions Econ Finan

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Starting from the model in Koch and Vargiolu (SIAM J Control Optim 59(4): 3068-3095, 2021), we test the real impact of current renewable installed power in the electricity price in Italy, and assess how much the renewable installation strategy which was put in place in Italy deviated from the optimal one obtained from the model in the period 2012-2018. To do so, we consider the Ornstein-Uhlenbeck (O-U) process, including an exogenous increasing process influencing the mean-reverting term, which is interpreted as the current renewable installed power. We estimate the parameters of this model by using real data of electricity prices and energy production from photovoltaic and wind power plants from the six main Italian price zones. We obtain that the model fits well the North, Central North and Sardinia zones: among these zones, the North is impacted by photovoltaic production, Sardinia by wind and the Central North does not present significant price impact. Then, we implement the solution of the singular optimal control problem of installing renewable power plants, in order to maximize the profit of selling the produced energy in the market net of installation costs. We extend the results of Koch and Vargiolu (SIAM J Control Optim 59(4): 3068-3095, 2021) to the case when no impact on power price is presented and to the case when N players can produce electricity by installing renewable power plants. To this extent, we analyze both the concepts of Pareto optima and of Nash equilibria. For this latter, we present a verification theorem in the 2-player case and an explicit characterization of a Nash equilibrium in the no-impact case. We are thus able to describe the optimal strategy and compare it with the real installation strategy that was put in place in Italy.

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A Multifactor Approach to Modelling the Impact of Wind Energy on Electricity Spot Prices

Cited by 8 publications

References 30 publications

Price formation and optimal trading in intraday electricity markets

Price formation and optimal trading in intraday electricity markets

A survey of electricity spot and futures price models for risk management applications

Optimal installation of renewable electricity sources: the case of Italy

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