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作 者:李娟 汪家铭 许苏迪 姜云龙 杨雄 LI Juan;WANG Jiaming;XU Sudi;JIANG Yunlong;YANG Xiong(State Grid Jiangsu Electric Power Co.,Ltd.Electric Power Science Research Institute,Nanjing 221103,China)
机构地区:[1]国网江苏省电力有限公司电力科学研究院,江苏南京221103
出 处:《中国电力》2023年第12期191-198,共8页Electric Power
基 金:国网江苏省电力有限公司科技项目(J2022025)。
摘 要:针对原有配电网故障恢复策略在处理高渗透率分布式光伏并网时效率低、易陷入局部收敛等问题,提出了一种基于量子萤火虫算法的配电网故障恢复策略。首先,以最小化失电负荷量为主和最小化网络损耗为从,构建主从双目标优化目标函数,并计及约束条件建立含分布式光伏并网的配电网故障恢复模型。其次,为克服标准萤火虫算法的不足,采用量子编码和量子旋转门的方式提高萤火虫算法的寻优速度和全局搜索能力,缩短故障恢复模型求解时间。然后,采用量子萤火虫算法求解故障恢复模型,通过控制配电网系统开关的通断,在保证重要负荷恢复供电的基础上尽可能多地恢复失电负荷,同时减少网络损耗。最后,在IEEE 33节点系统上进行算例分析以验证所述方法的可行性和优越性。Existing distribution network fault recovery strategy tends to be inefficient and locally convergent for high penetrated distributed photovoltaic grid connection.Hence in this paper,a distribution network fault recovery strategy is proposed based on quantum firefly algorithm.The objective function is constructed in terms of a master-slave dual objective optimization to minimize both the load loss and network losses,and corresponding fault recovery model with distributed photovoltaic grid connection is established by taking into account of the constraints.To overcome the drawbacks of the standard firefly algorithm,quantum encoding and quantum rotation gates were applied to enhance the optimization efficiency and global search capability of the firefly algorithm such that the total solution time can be greatly shortened.Next from the fault recovery model solved after proposed algorithm,by controlling the on-off status of the circuit breakers in the distribution network system,the lost load can be restored as much as possible to ensure the restoration of power supply to critical loads,while minimizing network losses.Finally,case studies were conducted on the IEEE 33 bus system to verify the feasibility and advantages of the proposed method.This work is supported by Science and Technology Project of State Grid Jiangsu Electric Power Co.,Ltd.(No.J2022025).
关 键 词:配电网 故障恢复 分布式光伏 量子旋转门 量子萤火虫算法
分 类 号:TP18[自动化与计算机技术—控制理论与控制工程] TM73[自动化与计算机技术—控制科学与工程]
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