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Self-Scheduling Virtual Power Plant for Peak Management

Author

Listed:
  • Hossein Shokouhinejad

    (Department of Electrical & Computer Engineering, University of New Brunswick (UNB), Fredericton, NB E3B 5A3, Canada)

  • Eduardo Castillo Guerra

    (Department of Electrical & Computer Engineering, University of New Brunswick (UNB), Fredericton, NB E3B 5A3, Canada)

Abstract

An efficient and reliable management system for a cluster of distributed energy resources (DERs) is essential for the sustainable and cost-effective peak management (PM) operation of the power grid. The virtual power plant (VPP) provides an efficient way to manage a variety of DERs for the PM process. This paper proposes a VPP framework for PM of local distribution companies by optimizing the self-scheduling of available resources, considering uncertainties and constraints. The study examines two separate scenarios and introduces novel algorithms for determining threshold values in each scenario. An approach is suggested for the transaction between VPP and the aggregator models. The proposed technique intends to determine the optimal amount of capacity that aggregators can allocate for the day-ahead PM procedure while accounting for both thermostatically controlled and non-thermostatically controlled loads. The proposed VPP framework shows promising results for reducing demand charges and optimizing energy resources for PM.

Suggested Citation

  • Hossein Shokouhinejad & Eduardo Castillo Guerra, 2024. "Self-Scheduling Virtual Power Plant for Peak Management," Energies, MDPI, vol. 17(11), pages 1-20, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:11:p:2705-:d:1407540
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    References listed on IDEAS

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    1. Oshnoei, Arman & Kheradmandi, Morteza & Blaabjerg, Frede & Hatziargyriou, Nikos D. & Muyeen, S.M. & Anvari-Moghaddam, Amjad, 2022. "Coordinated control scheme for provision of frequency regulation service by virtual power plants," Applied Energy, Elsevier, vol. 325(C).
    2. Chapaloglou, Spyridon & Nesiadis, Athanasios & Iliadis, Petros & Atsonios, Konstantinos & Nikolopoulos, Nikos & Grammelis, Panagiotis & Yiakopoulos, Christos & Antoniadis, Ioannis & Kakaras, Emmanuel, 2019. "Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island’s power system," Applied Energy, Elsevier, vol. 238(C), pages 627-642.
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