整合电池储能经济与控制,提升电网稳定性和收益
Advances in Battery Energy Storage Management: Control and Economic Synergies
- 从电网服务、实时控制、优化调度等五方面综述储能管理
- 提出经济与控制协同机制,助力数字孪生系统构建
- 适合关注储能经济性与系统可靠性融合的研究者
现有电池储能系统(BESS)研究主要集中在控制设计以保障电网稳定,以及储能调度的技经分析。随着辅助服务在电网中占比增加,亟需更全面的能源管理系统,既要优化收益,又要确保锂离子电池的安全、高效与可靠运行。本文通过文献综述,探索经济维度与操作维度的协同路径,重点分析电网工况下的经济性如何与储能控制策略对齐。这种协同可推动数字孪生技术发展,实现虚拟化建模,提升电网稳定性与收益潜力。综述涵盖五大方向:(1)储能提供的辅助服务功能;(2)面向实时功率流动的控制体系;(3)储能调度优化算法;(4)储能系统的技经评估;(5)数字孪生技术在真实场景中的应用。识别潜在协同效应、研究空白与趋势,为未来储能管理与部署创新提供基础。
原文摘要 · Abstract (English)
The existing literature on Battery Energy Storage Systems (BESS) predominantly focuses on two main areas: control system design aimed at achieving grid stability and the techno-economic analysis of BESS dispatch on power grid. However, with the increasing incorporation of ancillary services into power grids, a more comprehensive approach to energy management systems is required. Such an approach should not only optimize revenue generation from BESS but also ensure the safe, efficient, and reliable operation of lithium-ion batteries. This research seeks to bridge this gap by exploring literature that addresses both the economic and operational dimensions of BESS. Specifically, it examines how economic aspects of grid duty cycles can align with control schemes deployed in BESS systems. This alignment, or synergy, could be instrumental in creating robust digital twins virtual representations of BESS systems that enhance both grid stability and revenue potential. The literature review is organized into five key categories: (1) ancillary services for BESS, exploring support functions that BESS can provide to power grids; (2) control systems developed for real-time BESS power flow management, ensuring smooth operations under dynamic grid conditions; (3) optimization algorithms for BESS dispatch, focusing on efficient energy allocation strategies; (4) techno-economic analyses of BESS and battery systems to assess their financial viability; and (5) digital twin technologies for real-world BESS deployments, enabling advanced predictive maintenance and performance optimization. This review will identify potential synergies, research gaps, and emerging trends, paving the way for future innovations in BESS management and deployment strategies.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。