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作 者:邢法财 麻常辉 苗伟威 王昊昊 李泽 周宁 程定一 XING Facai;MA Changhui;MIAO Weiwei;WANG Haohao;LI Ze;ZHOU Ning;CHENG Dingyi(State Grid Shandong Electric Power Research Institute,Jinan 250003,China;Shandong Smart Grid Technology Innovation Center,Jinan 250003,China;State Grid Shandong Electric Power Company,Jinan 250001,China;NARI Group Corporation(State Grid Electric Power Research Institute Co.,Ltd.),Nanjing 211106,China)
机构地区:[1]国网山东省电力公司电力科学研究院,济南250003 [2]山东省智能电网技术创新中心,济南250003 [3]国网山东省电力公司,济南250001 [4]南瑞集团有限公司(国网电力科学研究院有限公司),南京211106
出 处:《浙江电力》2024年第10期53-64,共12页Zhejiang Electric Power
基 金:国网山东省电力公司科技项目(2023A-140);国家重点研发计划(2021YFB2400800)。
摘 要:网络重构阶段的目标网架优化对电力系统恢复至关重要。针对现有的节点重要度评价和目标网架优化中无法考虑自然灾害影响、ERBN(节点预期恢复收益)及扩展并发恢复分区需求等问题,提出一种电力系统网络重构方法。首先,考虑节点的重要负荷恢复、扩展可用功率和增量恢复范围能力,综合评估灾害条件下节点的预期恢复收益,并结合可用恢复功率裕度,将发电和非发电节点的重要度统一到预期恢复收益上。然后,提出灾害条件下基于时序蒙特卡洛仿真的多时点可恢复状态模拟方法,并评估模拟电网状态下节点和线路的重要度。基于该重要度优化目标网架,将网架连通和无环网约束转化为罚函数并加入适应度函数,避免了对不合理网架的优化调整计算,提高了算法求解效率。最后,通过算例分析验证了所提方法的有效性。Optimizing the target grid framework during network reconfiguration is crucial for the recovery of the power system.Existing methods for assessing node importance and optimizing the target grid framework often over-look the impact of natural disasters,expected recovery benefits of nodes(ERBN),and the necessity for expanded concurrent recovery zones.To address these challenges,a network reconfiguration method for power systems is pro-posed.First,the ERBN under disaster conditions are comprehensively evaluated,considering the recovery of criti-cal loads,expanded available power,and the capacity for incremental recovery.The importance of both generating and non-generating nodes is unified based on their expected recovery benefits,taking into account the available re-covery power margin.Then,a method for multi-time-point recoverable state simulation based on time sequence Monte Carlo simulation is proposed under disaster conditions to assess the importance of nodes and lines in the simu-lated grid.The grid framework is optimized based on this importance,transforming grid connectivity and loop net-work constraints into penalty functions that are incorporated into the fitness function.This approach eliminates the need for optimization adjustments to unreasonable grid frameworks,thereby improving the efficiency of the algorithm.Finally,the effectiveness of the proposed method is validated through case studies.
分 类 号:TM73[电气工程—电力系统及自动化]
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