Self-Scheduling Virtual Power Plant for Peak Management

Hossein Shokouhinejad () and Eduardo Castillo Guerra
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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

Energies, 2024, vol. 17, issue 11, 1-20

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.

Keywords: virtual power plant; peak management; robust optimization; uncertainty; self-scheduling (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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