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储能系统技术 储能系统 ★ 5.0

一种考虑飓风影响的风电并网系统鲁棒储能规划新方法

A Novel Robust Energy Storage Planning Method for Grids With Wind Power Integration Considering the Impact of Hurricanes

作者 Huaizhi Yang · Cong Zhang · Jiayong Li · Lipeng Zhu · Ke Zhou
期刊 IEEE Transactions on Sustainable Energy
出版日期 2025年1月
技术分类 储能系统技术
技术标签 储能系统
相关度评分 ★★★★★ 5.0 / 5.0
关键词 储能系统规划 飓风 可再生能源发电 不确定性 改进列与约束生成算法
语言:

中文摘要

本文提出了一种新型储能系统(ESS)规划方法,旨在提升飓风期间ESS的应急能力,同时增强正常天气下可再生能源的消纳水平。所提出的鲁棒储能规划(NREP)模型综合考虑了飓风期间风电出力与输电线路故障的不确定性及其相关性,有效降低了负荷损失和弃风量。通过信息融合构建了与飓风强度相关的时空不确定性集合,提高了线路故障建模精度与求解效率。进一步设计了包含非预期性约束的改进列约束生成(ICCG)算法,能够关联场景并识别发电依赖的最恶劣场景,提升了多时段发电决策在非预期性不确定性下的可行性,并减少了各类场景下的弃风与切负荷损失。仿真结果验证了该方法相较于现有模型与算法的有效性与优越性。

English Abstract

This paper proposes a novel energy storage system (ESS) planning method for improving ESS emergency capability during hurricanes, as well as enhancing the integration of renewable power generation under normal weather simultaneously. First, a novel robust ESS planning (NREP) model is proposed that considers the uncertainties of wind power and transmission line faults, along with their correlation during hurricanes, thereby reducing load shedding losses and wind curtailment. Secondly, to improve both the modeling accuracy of line fault uncertainties and the solution efficiency, a spatio-temporal uncertainty set related to hurricane intensity is constructed through information fusion. Furthermore, an improved column-and-constraint generation (ICCG) algorithm, incorporating nonanticipativity constraints, is proposed to solve the NREP model. The ICCG is able to interrelate scenarios and identify generation-dependent worst-case scenarios, thereby improving the feasibility of multi-period generation decisions under nonanticipative uncertainty realization while reducing losses from wind curtailment and load shedding across all scenarios. Simulation results, obtained by comparisons to previous models and algorithms, validate the effectiveness and superiority of the proposed method.
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SunView 深度解读

该鲁棒储能规划方法对阳光电源PowerTitan大型储能系统和ST系列储能变流器在极端气候场景下的应用具有重要价值。文章提出的时空不确定性建模和改进列约束生成算法,可直接应用于阳光电源储能系统的能量管理策略(EMS)优化,特别是在台风、飓风等极端天气下提升系统应急响应能力。该方法考虑风电出力与线路故障的相关性建模,可增强iSolarCloud云平台的智能调度功能,实现多时段发电决策优化,降低弃风率并保障关键负荷供电。对于沿海风电场配套储能项目,该技术可提升PowerTitan系统的规划精度和经济性,同时为构网型GFM控制策略在极端工况下的鲁棒性设计提供理论支撑。