Virtual power plant formation strategy based on Stackelberg game: A three-step data-driven voltage regulation coordination scheme

Moein Esfahani, Ali Alizadeh, Bo Cao, Innocent Kamwa and Minghui Xu

Applied Energy, 2025, vol. 377, issue PA, No S0306261924017380

Abstract: Rising electricity demand and the swift integration of Distributed Energy Resources (DERs) highlight the imperative for effective voltage regulation (VR) strategies to mitigate voltage violations. Conventional VR methods, plagued by significant operational expenses and slow response times, are increasingly focused on harnessing prosumer flexibility. However, this strategy faces challenges, including uncertainties in VR calculations, designing VR coordination signals, and managing and monitoring prosumer actions. This paper introduces a novel three-step VR coordination scheme to tackle these issues. The first step utilizes a Data-driven Distributionally Robust Optimization (DDRO) algorithm with a Wasserstein metric ambiguity set to calculate the required active and reactive power adjustments for VR. The second step involves generating and disseminating price-based coordination signals via a clustering algorithm, reducing signal complexity. The final step proposes using Virtual Power Plants (VPPs) to aggregate smaller prosumers for VR, applying a bi-level Stackelberg game to account for the impact of distributed coordination signals on VPP member selection. Tested on the IEEE 33-bus system, this framework significantly lowers the computational load by approximately 35 % and cuts VR costs by 5.7 % compared to existing methods.

Keywords: Virtual power plant; Voltage regulation; Stackelberg game; Data-driven optimization; Distribution system (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2024.124355

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