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Probabilistic Peak Demand Estimation Using Members of the Clayton Generalized Gamma Copula Family

Author

Listed:
  • Moshe Kelner

    (Actuarial Research Center, University of Haifa, Haifa 3498838, Israel
    Noga—Israel Independent System Operator Ltd., Haifa 3508418, Israel)

  • Zinoviy Landsman

    (Actuarial Research Center, University of Haifa, Haifa 3498838, Israel
    Faculty of Sciences, Holon Institute of Technology, Holon 5810201, Israel)

  • Udi E. Makov

    (Actuarial Research Center, University of Haifa, Haifa 3498838, Israel)

Abstract

Climate change impacts many aspects of life and requires innovative thinking on various issues. The electricity sector is affected in several ways, including changes in the production components and consumption patterns. One of the most important issues for Independent System Operators, a state-controlled organization responsible for ensuring the reliability, availability, and quality of electricity delivery in the country, is the response to climate change. This is reflected in the appropriate design of production units to cope with the increase in demand due to extreme heat and cold events and the development of models aimed at predicting the probability of such events. In our work, we address this challenge by proposing a novel probability model for peak demand as a function of wet temperature (henceforth simply temperature), which is a weighting of temperature and humidity. We study the relationship between peak demand and temperature using a new Archimedean copula family, shown to be effective for this purpose. This family, the Clayton generalized Gamma, is a multi-parameter copula function that comprises several members. Two new measures of fit, an economic measure and a conditional coverage measure, were introduced to select the most appropriate family member based on the empirical data of daily peak demand and minimum temperature in the winter. The Clayton Gamma copula showed the lowest cost measure and the best conditional coverage and was, therefore, proven to be the most appropriate member of the family.

Suggested Citation

  • Moshe Kelner & Zinoviy Landsman & Udi E. Makov, 2022. "Probabilistic Peak Demand Estimation Using Members of the Clayton Generalized Gamma Copula Family," Energies, MDPI, vol. 15(16), pages 1-15, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:6081-:d:894448
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    References listed on IDEAS

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