A day-ahead self-dispatch optimization framework for load-side virtual control units participating in active power regulation of power grids

Mingze Zhang, Weidong Li, Samson S. Yu, Haomin Li, Yanling Lv and Jiakai Shen

Energy, 2025, vol. 318, issue C

Abstract: Distributed flexible resources on the load side of power systems can be aggregated into virtual control units (VCUs), which are directly dispatched by bulk power grids to participate in active power regulation at the distribution-grid level. However, existing dispatch methods fail to address the self-dispatch optimization challenges for fully-controllable and semi-controllable resources aggregated as VCUs, limiting the potential of load-side resources in the daily full-timescale frequency control ancillary services (FCASs). This study proposes aggregating electric vehicle (EV) battery swapping and charging stations (BSCSs) and small-scale battery energy storage stations (BESSs) into VCUs. To optimize the sequential strategies of these VCUs in responding to full timescale FCAS tasks in the day-ahead stage, two self-dispatch optimization frameworks are developed for the two forms of VCUs. A novel VCU operational mechanism is designed to ensure optimal coordination of multiple tasks by capturing the dynamic and time-varying regulation capabilities of distributed resources. To enhance the coordination of various flexible resources, the proposed framework introduces intra-station self-sufficiency and inter-station mutual aid as operational modes. Case studies for the two VCU configurations demonstrate the effectiveness of the approach. The results show that the VCUs can effectively evaluate and implement optimized allocation strategies allocation for grid dispatch tasks, balancing resource utilization between BESS clusters and BSCSs while accommodating the stochastic EV swapping demands faced by BSCSs.

Keywords: Virtual power plant; Optimal self-dispatch; Dis-aggregation; Active power regulation; Distributed resources coordination (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:318:y:2025:i:c:s0360544225004335

DOI: 10.1016/j.energy.2025.134791

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