面向快速响应与可调能力恢复的储能系统实时调度-再调度策略

doi:10.19595/j.cnki.1000-6753.tces.250776

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Abstract

With the increasing penetration of renewable energy, power system is facing more severe challenges related to random power fluctuations and supply-demand imbalances during operation. Energy storage systems (ESS) possess rapid response capability and flexible bidirectional regulation characteristic, enabling them to provide swift and adaptable power regulation and balancing service during real-time power system operation. Currently, ESS primarily participates in power system regulation through electricity market, where economic benefits remain a key factor influencing the extent of ESS involvement. However, this approach often overlooks the actual requirements for efficient adjustment and response speed during real-time emergencies. Moreover, as most real-time emergencies are short-lived issues, there is currently a lack of in-depth research on the rescheduling process for restoring ESS to planned operation and recoverable regulation capability after resolving such issues. To address these gaps, this paper develops a comprehensive real-time ESS response-recovery scheduling framework and proposes a real-time scheduling-rescheduling strategy for ESS, focusing on rapid response and regulation capability recovery.
This paper first establishes a real-time scheduling-rescheduling framework for energy storage systems (ESS), meticulously characterizing the complete operational process encompassing rapid response and adjustable capacity recovery during real-time operation. Secondly, to rapidly mobilize resource response capability during contingency, we develop a real-time power decision-making method from both the dispatch center and energy storage station perspectives. This method comprehensively considers: decision-making time at the dispatch center, decision-making time at energy storage stations, and response time of energy storage resources. By incorporating the power response rates of multiple ESS types and state transition mechanisms, the proposed method achieves rapid mitigation of power fluctuations. Moreover, post-contingency when ESS energy levels often deviate from original operating plans, we construct an energy soft boundary for ESS to maintain subsequent operational effectiveness while considering economic benefits in real-time spot markets. Accounting for power plan failure risks and balancing the advantages of online computation with offline training, we propose a Synthesize Approximate Future Cost Function (SAFCF) that integrates online information with uncertainty factors. This function supports real-time rescheduling decision-making for adjustable capacity recovery processes. Lastly, case studies verify the effectiveness of the proposed method, which can fully activate the rapid response capability of energy storage systems, achieve stable recovery of their adjustable capacity, and effectively support stable operation of power systems.
Through case study validation and comparative analysis of the proposed model, the following conclusions can be drawn: ①The real-time dispatch command decomposition model based on state transition avoids repeated resource sorting and optimization processes, significantly improving the decision-making speed of energy storage stations. The fast response model under emergency prioritizes allocating power deficits to the energy storage stations with the fastest response rates, enabling more rapid compensation of power deviations compared to traditional methods. ②The proposed SAFCF effectively integrates the advantages of both online computation and offline training, achieving real-time decision-making that balances economic efficiency with stable recovery of adjustable capacity. The rescheduling model based on SAFCF can effectively perceive future information for real-time decisions, ensuring stable recovery of adjustable capacity while reducing ESS operating costs. Moreover, its high decision-making efficiency meets real-time operational requirements.

Key words： Energy storage system real-time scheduling rescheduling model power response speed adjustable capacity restoration

Received: 09 May 2025

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TM734

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	Hu Junjie
	Chen Quanxi
	Pan Yi

Cite this article:

Hu Junjie,Chen Quanxi,Pan Yi. Real-Time Scheduling-Rescheduling Strategy of Energy Storage System for Fast Response and Adjustable Capacity Restoration[J]. Transactions of China Electrotechnical Society, 0, (): 20250776-20250776.

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