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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摘要

储能系统具备高效快速响应能力,是缓解高渗透率可再生能源电力系统复杂功率不平衡问题的重要资源。然而,现阶段针对突发事件的储能系统实时调度往往忽略了不同类型储能响应速率的影响,且缺乏对响应后储能系统可调能力恢复的再调度过程深入探索。为此,本文首先构建了储能系统实时调度-再调度框架,精细刻画了实时阶段快速响应与可调能力恢复运行全流程;其次,分别从调度中心与储能电站视角,构建了计及多类型储能资源功率响应速率与基于状态转移机制的实时功率决策方法,实现了功率波动的快速平抑;再次,考虑功率计划失效风险,建立了储能系统能量软边界,兼顾在线计算与离线训练优势,提出了融合在线信息与不确定性因素的综合近似未来成本函数,支撑可调能力恢复过程实时决策;最后,通过算例验证了方法的有效性,能够充分激发储能系统快速响应能力,实现储能系统可调节能力的稳定恢复,有效支撑电力系统稳定运行。

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	胡俊杰
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关键词 ：储能系统, 实时调度, 再调度, 功率响应速率, 可调节能力恢复

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

收稿日期: 2025-05-09

PACS:

TM734

基金资助:

江苏省自然科学基金（BK20232026）和国家自然科学基金（52177080）资助项目

通讯作者: 胡俊杰男,1986年生,教授,博士生导师,研究方向为新能源电力系统运行调度等。E-mail：junjiehu@ncepu.edu.cn

作者简介: 陈泉希女,2001年生,硕士研究生,研究方向为新型电力系统优化调度,智能技术在电力系统中的应用。E-mail：quanxichen@ncepu.edu.cn

引用本文:

胡俊杰, 陈泉希, 潘羿. 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[J]. 电工技术学报, 0, (): 20250776-20250776. Hu Junjie, Chen Quanxi, Pan Yi. Real-Time Scheduling-Rescheduling Strategy of Energy Storage System for Fast Response and Adjustable Capacity Restoration. Transactions of China Electrotechnical Society, 0, (): 20250776-20250776.

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