Managing Volumetric Risk of Long-term Power Purchase Agreements

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Managing Volumetric Risk of Long-term Power Purchase Agreements. / Tranberg, Bo; Hansen, Rasmus Thrane ; Catania, Leopoldo.

I: Energy Economics, Bind 85, 104567, 2020.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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Tranberg, Bo ; Hansen, Rasmus Thrane ; Catania, Leopoldo. / Managing Volumetric Risk of Long-term Power Purchase Agreements. I: Energy Economics. 2020 ; Bind 85.

Bibtex

@article{3d95a9acdc154ccd887c39c3edd23ef4,
title = "Managing Volumetric Risk of Long-term Power Purchase Agreements",
abstract = "There exists a negative dependence between wind power production and electricity spot price. 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 using a new generation of 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 a previously published model of the ARMA-GARCH type. 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.",
author = "Bo Tranberg and Hansen, {Rasmus Thrane} and Leopoldo Catania",
year = "2020",
doi = "10.1016/j.eneco.2019.104567",
language = "English",
volume = "85",
journal = "Energy Economics",
issn = "0140-9883",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - Managing Volumetric Risk of Long-term Power Purchase Agreements

AU - Tranberg, Bo

AU - Hansen, Rasmus Thrane

AU - Catania, Leopoldo

PY - 2020

Y1 - 2020

N2 - There exists a negative dependence between wind power production and electricity spot price. 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 using a new generation of 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 a previously published model of the ARMA-GARCH type. 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.

AB - There exists a negative dependence between wind power production and electricity spot price. 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 using a new generation of 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 a previously published model of the ARMA-GARCH type. 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.

U2 - 10.1016/j.eneco.2019.104567

DO - 10.1016/j.eneco.2019.104567

M3 - Journal article

VL - 85

JO - Energy Economics

JF - Energy Economics

SN - 0140-9883

M1 - 104567

ER -