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Analysis of Demand Response in Electric Systems with Strong Presence of Intermittent Generation Using Conditional Value-at-Risk

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  • Rafael V. X. de Souza

    (Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo André 09210-580, Brazil)

  • Thales Sousa

    (Center for Engineering, Modeling and Applied Social Sciences, Federal University of ABC, Santo André 09210-580, Brazil)

Abstract

The integration of renewable sources, such as hydro, wind, and solar power, into electrical systems has profoundly transformed the sector’s dynamics. The inherent intermittency of these energy sources, due to the uncertainty associated with inflows, winds, and solar irradiation, introduces considerable challenges in the operation and planning of the electrical system. In this context, demand response emerges as a promising solution to handle the fluctuations in renewable generation and maintain system stability and reliability. Therefore, this study presents a new approach to the demand response program through the modeling of an optimal power flow problem to minimize operational costs, considering the uncertainties in hydro, wind, and solar generation by applying the Conditional Value-at-Risk (CVaR) risk metric. The mathematical modeling of the problem was conducted, and the problem was solved using the MINOS solver. To validate the model, simulations were carried out using modified IEEE systems of 14, 30, 57, and 118 buses, considering operation planning for the next 24 h. Furthermore, sensitivity analyses were performed by altering the CVaR parameters. As a result of the simulations, the total operational cost, electrical losses, and hourly generation at each bus by source type were determined, highlighting how CVaR impacts the operation of this type of system.

Suggested Citation

  • Rafael V. X. de Souza & Thales Sousa, 2024. "Analysis of Demand Response in Electric Systems with Strong Presence of Intermittent Generation Using Conditional Value-at-Risk," Energies, MDPI, vol. 17(18), pages 1-17, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:18:p:4688-:d:1481986
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    References listed on IDEAS

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    1. Heydarian-Forushani, Ehsan & Golshan, Mohamad Esmail Hamedani & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "A comprehensive linear model for demand response optimization problem," Energy, Elsevier, vol. 209(C).
    2. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Value-at-risk methodologies for effective energy portfolio risk management," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 197-212.
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