针对有源配电网故障后借助含分布式电源（DG）微网的恢复控制问题,提出一种考虑微网电压支撑的配电网精准负荷双层供电恢复策略。首先,为充分量化故障时段内重构后孤岛运行风险,从电压稳定和功率平衡的角度定义重构后孤岛运行风险指标,最大程度的利用故障时段内微网DG资源建立重构模型;然后,针对供电恢复重构模型求解难度高的问题,使用灰狼优化算法（GWO）与二阶锥松弛技术分别求解双层重构模型,其中,为解决GWO算法以优质解引导种群进化导致效率受限制的问题,采用粒子群算法（PSO）思想来改善GWO算法的个体位置更新过程,通过融合每个灰狼个体的历史信息以构筑更高效的种群进化方法。最后,采用修正的IEEE 33节点系统,在2种不同类型故障下均能够提供供电恢复方案,验证方法的可行性。
Abstract
Aiming at the problem of recovery control of active distribution network with microgrid containing distributed generation （DG） after fault, this paper proposes a two-layer power supply recovery strategy for precise load of distribution network considering microgrid voltage support. Firstly, in order to fully quantify the risk of island operation after reconfiguration during the fault period, the risk index of island operation after reconfiguration is defined from the perspective of voltage stability and power balance, and the reconfiguration model is established by using the distributed generation resources of microgrid in the fault period to the greatest extent. Then, aiming at the problem of high difficulty in solving the power supply recovery reconstruction model, the grey wolf optimization algorithm （GWO） and the second-order cone relaxation technique are used to solve the two-layer reconstruction model respectively. Among them, in order to solve the problem that the GWO algorithm guides the population evolution with high-quality solutions, which leads to the limitation of efficiency, the PSO algorithm is used to improve the individual position update process of the GWO algorithm, and the historical information of each gray wolf individual is integrated to construct a more efficient population evolution method. Finally, using the modified IEEE 33 node system, the power supply recovery scheme can be provided under two different types of faults, which verifies the feasibility of the proposed method.
关键词
分布式电源 /
配电网 /
孤岛 /
配电网重构 /
供电恢复
Key words
distributed generation /
distribution networks /
islanding /
distribution network reconfiguration /
service restoration
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参考文献
[1] 刘科研, 盛万兴, 马晓晨, 等. 基于多种群遗传算法的分布式光伏接入配电网规划研究[J]. 太阳能学报, 2021, 42(6): 146-155.
LIU K Y, SHENG W X, MA X C, et al.Planning research of distributed photovoltaic source access distribution network based on multi-population genetic algorithm[J]. Acta energiae solaris sinica, 2021, 42(6): 146-155.
[2] 保富, 高宇豆. 基于大数据平台的电压质量诊断与应用分析[J]. 电测与仪表, 2023, 60(10): 112-116.
BAO F, GAO Y D.Voltage quality diagnosis and application analysis based on big data platform[J]. Electrical measurement & instrumentation, 2023, 60(10): 112-116.
[3] 王守相, 刘琪, 赵倩宇, 等. 配电网弹性内涵分析与研究展望[J]. 电力系统自动化, 2021, 45(9): 1-9.
WANG S X, LIU Q, ZHAO Q Y, et al.Connotation analysis and prospect of distribution network elasticity[J]. Automation of electric power systems, 2021, 45(9): 1-9.
[4] 李聪, 秦立军, 段惠. 基于改进群搜索算法的含光伏发电的配电网优化重构研究[J]. 太阳能学报, 2022, 43(4): 213-218.
LI C, QIN L J, DUAN H.Research on reconfiguration of distribution network with photovoltaic generation based on improved group search optimizer[J]. Acta energiae solaris sinica, 2022, 43(4): 213-218.
[5] 马晨霄, 刘洋, 许立雄, 等. 同时考虑孤岛与重构的配电网故障恢复运行策略[J]. 电力建设, 2018, 39(8): 128-136.
MA C X, LIU Y, XU L X, et al.Fault recovery operation strategy for distribution network coordinating islanding and reconfiguration[J]. Electric power construction, 2018, 39(8): 128-136.
[6] 王光华, 李晓影, 宋秉睿, 等. 基于深度强化学习的配电网负荷转供控制方法[J]. 电力自动化设备, 2022, 42(7): 253-260.
WANG G H, LI X Y, SONG B R, et al.Load transfer control method of distribution network based on deep reinforcement learning[J]. Electric power automation equipment, 2022, 42(7): 253-260.
[7] 郭登科, 米文涛, 庄飞虎, 等. 基于K折验证的配电网故障转供可靠性评估研究[J]. 电气传动, 2022, 52(8): 74-80.
GUO D K, MI W T, ZHUANG F H, et al.Research on reliability evaluation of distribution network fault transfer based on K-fold verification[J]. Electric drive, 2022, 52(8): 74-80.
[8] 端木浚程, 袁越. 配电网孤岛划分的启发式方法[J]. 电测与仪表, 2023, 60(3): 26-32.
DUANMU J C, YUAN Y.A heuristic method for island partition of distribution network[J]. Electrical measurement & instrumentation, 2023, 60(3): 26-32.
[9] NAFISI H, FARAHANI V, ASKARIAN ABYANEH H, et al.Optimal daily scheduling of reconfiguration based on minimisation of the cost of energy losses and switching operations in microgrids[J]. IET generation, transmission & distribution, 2015, 9(6): 513-522.
[10] 向佳霓, 赵建立, 顾霈, 等. 考虑需求响应的配电网重构经济性和可靠性研究[J]. 电工技术, 2022(19): 20-23.
XIANG J N, ZHAO J L, GU P, et al.Research on economics and reliability of distribution network reconfiguration considering demand response[J]. Electric engineering, 2022(19): 20-23.
[11] 章立宗, 吴磊, 蒋玮, 等. 考虑二次转供的配电网负荷转供方案多目标优选技术[J]. 电网技术, 2019, 43(7): 2321-2328.
ZHANG L Z, WU L, JIANG W, et al.Research on distribution network load transfer scheme based on multi-objective optimization considering secondary re-sale strategy[J]. Power system technology, 2019, 43(7): 2321-2328.
[12] 张熙, 程小华, 曾君, 等. 基于动态规划与最优流模式的微网孤岛重构[J]. 电网技术, 2020, 44(12): 4608-4616.
ZHANG X, CHENG X H, ZENG J, et al.Microgrid island reconfiguration based on dynamic programming method and optimal flow pattern[J]. Power system technology, 2020, 44(12): 4608-4616.
[13] 阳晓明, 吕红芳, 朱辉. 基于改进人工鱼群算法的配电网络重构[J]. 电测与仪表, 2020, 57(17): 72-78, 98.
YANG X M, LYU H F, ZHU H.Reconfiguration of distribution network based on improved artificial fish swarm algorithm[J]. Electrical measurement & instrumentation, 2020, 57(17): 72-78, 98.
[14] 吉兴全, 连承宇, 张玉敏, 等. 基于智能软开关的三相不平衡配电网动态重构策略[J]. 智慧电力, 2023, 51(5): 111-118.
JI X Q, LIAN C Y, ZHANG Y M, et al.Dynamic reconfiguration of three-phase unbalanced distribution networks based on SOP[J]. Smart power, 2023, 51(5): 111-118.
[15] 黄曜, 林凌雪, 管霖. 考虑DG与负荷时变性的配电网分时段动态重构[J]. 电气自动化, 2022, 44(6): 25-27, 31.
HUANG Y, LIN L X, GUAN L.Time-divided dynamic reconfiguration of distribution network considering time-varying DG and load[J]. Electrical automation, 2022, 44(6): 25-27, 31.
[16] 谭慧娟, 李世明, 郭文鑫, 等. 基于混沌自适应人工鱼群算法的含家庭储能配电网快速重构方法[J]. 太阳能学报, 2022, 43(5): 468-477.
TAN H J, LI S M, GUO W X, et al.Fast reconfiguration method of distribution network with household energy storage based on chaotic adaptive artificial fish swarm algorithm[J]. Acta energiae solaris sinica, 2022, 43(5): 468-477.
[17] PEICAN K, YONGLE A.Distribution network reconstruction with DG based on improved sparrow search algorithm[J]. Academic journal of engineering and technology science, 2023, 6(4): 1-10.
[18] 郝文斌, 曾鹏, 谢波, 等. 基于博弈论的含氢能配电网系统优化重构研究[J]. 太阳能学报, 2023, 44(8): 77-84.
HAO W B, ZENG P, XIE B, et al.Game theory-based optimal reconfiguration for distribution network system with hydrogen energy[J]. Acta energiae solaris sinica, 2023, 44(8): 77-84.
[19] SUN Q, YU Y J, LI D B, et al.A distribution network reconstruction method with DG and EV based on improved gravitation algorithm[J]. Systems science & control engineering, 2021, 9(2): 6-13.
[20] 霍崇辉, 王淳, 陶多才, 等. 考虑精准负荷控制的配电网供电恢复策略[J]. 电网技术, 2020, 44(10): 4020-4028.
HUO C H, WANG C, TAO D C, et al.Restoration strategy of distribution network considering precise load control[J]. Power system technology, 2020, 44(10): 4020-4028.
基金
国网湖北省电力有限公司电力科学研究院科技项目（SGHBDK00PWJS2200077）
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