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Managing volumetric risk of long-term power purchase agreements

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  • Tranberg, Bo
  • Hansen, Rasmus Thrane
  • Catania, Leopoldo

Abstract

A negative dependence between wind power production and electricity spot price exists. This is an important fact to consider for risk management of long-term power purchase agreements (PPAs). In this study we investigate this dependence by constructing a joint model using constant as well as time-varying copulas. We propose to use score-driven models as marginal model for the spot price of electricity as these are more robust to extreme events compared to ARMA–GARCH models. We apply the new model to pricing and risk management of PPAs and benchmark it against the ARMA–GARCH specification. Our comparison shows that the score-driven model results in a statistically significant improvement of predicting the Value-at-Risk (VaR), which is of high importance for risk management of long-term PPAs. Further, comparing constant and time–varying copulas we find that all time-varying copulas are significantly better than their constant counterparts at predicting the VaR, hence time–varying copulas should be used in risk management of PPAs.

Suggested Citation

  • Tranberg, Bo & Hansen, Rasmus Thrane & Catania, Leopoldo, 2020. "Managing volumetric risk of long-term power purchase agreements," Energy Economics, Elsevier, vol. 85(C).
    • Handle: RePEc:eee:eneeco:v:85:y:2020:i:c:s0140988319303627
    DOI: 10.1016/j.eneco.2019.104567
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    4. Jose Barroco & Peerapat Vithayasrichareon, 2023. "Accelerating the Energy Transition through Power Purchase Agreement Design: A Philippines Off-Grid Case Study," Energies, MDPI, vol. 16(18), pages 1-26, September.

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    More about this item

    Keywords

    Volumetric risk; Time-varying copula model; Score-driven model; Risk management; Power purchase agreement; Electricity market;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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