裴志刚,方珺,张志远,陈佳明,伍桂平
PEI Zhigang,FANG Jun,ZHANG Zhiyuan,CHEN Jiaming,WU Guiping

• 1:国网浙江省电力有限公司绍兴供电公司

摘要(Abstract)：

高渗透率分布式光伏接入易致配电网潮流反送与节点电压越限，分布式储能可有效解决上述问题，并在低压时段抬升电压，但其投资与运行成本较高。为此，以最小化储能运行成本和网络线损成本、最大化峰谷套利收益为目标构建多目标优化框架。提出改进MOPSO（多目标粒子群优化）算法，在粒子比较与外部档案更新中采用Deb可行性规则优先保留可行解，并按约束违背程度对不可行解排序，在目标函数评价环节引入动态罚因子，根据种群可行解比例自适应调整惩罚强度。利用灰色关联投影对Pareto解集综合评价，选取单一可实施方案。基于IEEE 33节点配电网的算例表明，改进MOPSO算法可将可行解比例由70%提高至90%，电压偏移量从0.078降至0.043，储能成本下降15.42%，峰谷套利收益提高约58.95%。
The high-penetration integration of distributed photovoltaic(DPV) generation tends to cause reverse power flow and node voltage violations in distribution networks. Distributed energy storage can effectively mitigate these issues and boost voltage during low-load periods; however, its investment and operating costs remain relatively high. To this end, a multi-objective optimization framework is developed to minimize energy storage operating costs and network power losses while maximizing peak-valley arbitrage profits. A modified multi-objective particle swarm optimization(MOPSO) is proposed, in which Deb's feasibility rules are employed in particle comparison and external archive updating to prioritize feasible solutions, while infeasible solutions are ranked according to the degree of constraint violation. A dynamic penalty factor is introduced in objective function evaluation, with the penalty intensity adaptively adjusted based on the proportion of feasible solutions in the population. Grey relational projection is applied to comprehensively evaluate the Pareto solution set, and a single implementable scheme is selected. Case studies based on the IEEE 33-bus distribution network demonstrate that the modified MOPSO increases the proportion of feasible solutions from 70% to 90%, reduces voltage deviation from 0.078 to 0.043, lowers energy storage costs by 15.42%, and improves peak-valley arbitrage profits by approximately 58.95%.

关键词(KeyWords)： 分布式光伏;分布式储能;多目标粒子群算法;Deb可行性规则;动态罚因子;灰色关联投影
DPV;distributed energy storage;MOPSO;Deb's feasibility rule;dynamic penalty factor;grey relational projection

Abstract:

Keywords:

基金项目(Foundation): 国家重点研发计划（2022YFE0140600）

作者(Author): 裴志刚,方珺,张志远,陈佳明,伍桂平
PEI Zhigang,FANG Jun,ZHANG Zhiyuan,CHEN Jiaming,WU Guiping

DOI: 10.19585/j.zjdl.202607004

参考文献(References)：

• [1]国家能源局发布2025年1—10月份全国电力工业统计数据[J].电力勘测设计，2025,(11):85.National Energy Administration released statistical data on the national electric power industry from January to October 2025[J]. Electric Power Survey&Design,2025(11):85.
• [2]Tang W H,Huang Y L,Qian T,et al.Coordinated centrallocal control strategy for voltage management in PVintegrated distribution networks considering energy storage degradation[J].Applied Energy,2025,389:125684.
• [3]张晋铭，欧阳森，吴晗，等.计及配电网可靠性和运行经济性的电网侧储能优化配置[J].电力自动化设备，2024,44(7):62-68.Zhang Jinming,Ouyang Sen,Wu Han,et al.Optimal configuration of grid-side energy storage considering reliability and operation economy of distribution network[J].Electric Power Automation Equipment,2024,44(7):62-68.
• [4]Ding Y,Hu L,Liu P,et al. A flexibility-integrated duallayer multi-objective optimization framework for building air conditioning systems[J]. Applied Thermal Engineering,2025,279:127487.
• [5]孙英聪，陈来军，唐明睿，等.集中式共享储能运行优化关键技术与研究展望[J].高电压技术，2025,51(9):4505-4519.Sun Yingcong,Chen Laijun,Tang Mingrui,et al.Key technology and research prospect for the operation optimization of centralized shared energy storage systems[J].High Voltage Engineering,2025,51(9):4505-4519.
• [6]Elseify M A,Mostafa R R,Hashim F A,et al. Optimal scheduling of photovoltaic and battery energy storage in distribution networks using an ameliorated sand cat swarm optimization algorithm:Economic assessment with different loading scenarios[J].Journal of Energy Storage,2025,116:116026.
• [7]Zhang L Z,Kuang J Y,Sun B,et al.A two-stage operation optimization method of integrated energy systems with demand response and energy storage[J].Energy,2020,208:118423.
• [8]华昊辰，翟家祥，陈星莺，等.基于增强精英保留遗传算法的虚拟微网群动态划分及能量局域自治[J].中国电机工程学报，2024,44(12):4652-4665.Hua Haochen,Zhai Jiaxiang,Chen Xingying,et al.Dynamical partitioning and local energy autonomy of virtual microgrid groups based on strengthen elitist genetic algorithm[J].Proceedings of the CSEE,2024,44(12):4652-4665.
• [9]Yin C,Wang J X,Tang W Y,et al.Health-aware energy management strategy toward Internet of storage[J].IEEE Internet of Things Journal,2023,10(9):7545-7553.
• [10]马鹏，齐军，熊逸，等.考虑响应可靠性与经济性的需求侧精准调峰策略[J/OL].电力系统自动化，1-14[2025-03-07]. http：//kns. cnki. net/kcms/detail/32.1180. TP. 20241014.0901.006.html.Ma Peng,Qi Jun,Xiong Yi,et al.A demand side precise peak shaving strategy considering response reliability and economy[J/OL].Automation of Electric Power System,1-14[2025-03-07]. http：//kns. cnki. net/kcms/detail/32.1180.TP.20241014.0901.006.html.
• [11]蔡晖，窦飞，万文文，等.计及源荷不确定性的柔性互联配电系统两阶段电压优化[J].电网技术，2022,46(4):1566-1574.Cai Hui,Dou Fei,Wan Wenwen,et al.Two-stage voltage optimization of flexible interconnected distribution system considering source and load uncertainty[J].Power System Technology,2022,46(4):1566-1574.
• [12]Yin S,Wang Y L,Zhang Q Y.Mechanisms and implementation pathways for distributed photovoltaic grid integration in rural power systems:a study based on multi-agent game theory approach[J].Energy Strategy Reviews,2025,60:101801.
• [13]孙华鹏，丁孝华，吴志，等.计及自动电压控制系统限值优化调整的配电网调压策略[J].电力系统自动化，2025,49(12):184-193.Sun Huapeng,Ding Xiaohua,Wu Zhi,et al.Voltage regulation strategy for distribution network considering optimal adjustment of automatic voltage control system limits[J].Automation of Electric Power Systems,2025,49(12):184-193.
• [14]Hua H C,Qin Y C,He Z C,et al.Energy sharing and frequency regulation in energy network via mixed H2/H∞control with Markovian jump[J].CSEE Journal of Power and Energy Systems,2021,7(6):1302-1311.
• [15]杨景旭，羿应棋，张勇军，等.基于加权分布熵的配电网电动汽车并网运行风险分析[J].电力系统自动化，2020,44(5):171-179.Yang Jingxu,Yi Yingqi,Zhang Yongjun,et al.Operation risk analysis of electric vehicle integrated to distribution network based on weighted distribution entropy[J].Automation of Electric Power Systems,2020,44(5):171-179.
• [16]陈泽兴，林楷东，张勇军，等.电-气互联系统建模与运行优化研究方法评述[J].电力系统自动化，2020,44(3):11-23.Chen Zexing,Lin Kaidong,Zhang Yongjun,et al.A review of modeling and optimal operation of integrated electricitygas system[J]. Automation of Electric Power Systems,2020,44(3):11-23.
• [17]丁煜蓉，陈红坤，吴军，等.计及综合能效的电-气-热综合能源系统多目标优化调度[J].电力系统自动化，2021,45(2):64-73.Ding Yurong,Chen Hongkun,Wu Jun,et al. Multiobjective optimal dispatch of electricity-gas-heat integrated energy system considering comprehensive energy efficiency[J].Automation of Electric Power Systems,2021,45(2):64-73.
• [18]马光，朱文，顾慧杰，等.基于加权最小绝对值状态估计的有源配电网拓扑辨识方法[J].中国电力，2024,57(1):167-174.Ma Guang,Zhu Wen,Gu Huijie,et al.Topology identification method for active distribution network based on weighted minimum absolute value state estimation[J].Electric Power,2024,57(1):167-174.
• [19]Kahagalage S,Turan H H,Jalalvand F,et al. A novel graph-theoretical clustering approach to find a reduced set with extreme solutions of Pareto optimal solutions for multi-objective optimization problems[J]. Journal of Global Optimization,2023,86(2):467-494.
• [20]赵佩，代业明.基于实时电价和加权灰色关联投影的SVM电力负荷预测[J].电网技术，2020,44(4):1325-1332.Zhao Pei,Dai Yeming. Power load forecasting of SVM based on real-time price and weighted grey relational projection algorithm[J].Power System Technology,2020,44(4):1325-1332.
• [21]Fernandes T R,Venkatesh B,De Almeida M C.Distribution system topology identification via efficient MILPbased WLAV state estimation[J].IEEE Transactions on Power Systems,2023,38(1):75-84.
• [22]徐玉琴，方楠.基于分段线性化与改进二阶锥松弛的电-气互联系统多目标优化调度[J].电工技术学报，2022,37(11):2800-2812.Xu Yuqin,Fang Nan.Multi objective optimal scheduling of integrated electricity-gas system based on piecewise linearization and improved second order cone relaxation[J].Transactions of China Electrotechnical Society,2022,37(11):2800-2812.
• [23]Qiao J P,Mi Y,Shen J,et al.Active and reactive power coordination optimization for active distribution network considering mobile energy storage system and dynamic network reconfiguration[J]. Electric Power Systems Research,2025,238:111080.
• [24]Babalik A,Cinar A C,Kiran M S.A modification of treeseed algorithm using Deb’s rules for constrained optimization[J].Applied Soft Computing,2018,63:289-305.
• [25]文贤馗，周科，张俊玮，等.基于单端口降阶模型的分布式光伏接入配电网交互影响分析[J].电力工程技术，2025(4):187-196.Wen Xiankui,Zhou Ke,Zhang Junwei,et al.Interaction effect analysis of distributed photovoltaic access to distributed network based on single-port reduced model[J].Electric Power Engineering Technology,2025(4):187-196.
• [26]高翔，安育伦，张义涛，等.基于多目标约束的分布式储能容量配置技术研究[J].高压电器，2025,61(6):200-209.Gao Xiang,An Yulun,Zhang Yitao,et al.Research on capacity configuration technology of distributed energy storage based on multi-objective constraints[J].High Voltage Apparatus,2025,61(6):200-209.
• [27]胥德玉，黄媛，唐志远，等.面向配电网分布式光伏消纳和可靠性提高的构网型储能优化配置[J].电力建设，2026,47(1):1-14.Xu Deyu,Huang Yuan,Tang Zhiyuan,et al.Research on grid-forming energy storage configuration for distributed photovoltaic consumption and reliability improvement of distribution network[J]. Electric Power Construction,2026,47(1):1-14.
• [28]田世明，马涛，徐玉婷，等.分布式储能单元集群一致性自律调节研究[J].电力电子技术，2025,59(4):62-65.Tian Shiming,Ma Tao,Xu Yuting,et al.Research on consensus based self-control for distributed energy storage unit cluster[J].Power Electronics,2025,59(4):62-65.
• [29]关逸飞，王玥娇，刘奕元，等.计及资源差异特性的分布式光伏与储能聚合运营优化方法[J].山东电力技术，2024,51(12):34-43.Guan Yifei,Wang Yuejiao,Liu Yiyuan,et al.Distributed photovoltaic and energy storage aggregation operation optimization method for resource differences[J]. Shandong Electric Power,2024,51(12):34-43.
• [30]黄兴华，范元亮，张功林，等.含分布式光伏中低压配电网多时间尺度协同无功优化策略[J].智慧电力，2024,52(11):8-15.Huang Xinghua,Fan Yuanliang,Zhang Gonglin,et al.Multi-time scale collaborative reactive power optimization strategy for medium and low voltage distribution networks with PV[J].Smart Power,2024,52(11):8-15.
• [31]王尚斌，苑丽伟，方莹，等.计及新能源波动的分布式储能分层控制策略[J].山东电力技术，2024,51(9):74-84.Wamg Shangbin,Yuan Liwei,Fang Ying,et al. Distributed energy storage layered control strategy considering renewable energy fluctuations[J].Shandong Electric Power,2024,51(9):74-84.
• [32]缪雨函，许寅，王颖.面向恢复力提升的高比例分布式光伏接入配电网规划方法[J].山东电力技术，2024(8):1-9.Miao Yuhan,Xu Yin,Wang Ying.Planning of distribution system integrated with high-penetration photovoltaic for the resilience improvement[J].Shandong Electric Power,2024(8):1-9.
• [33]杨书强，范文奕，赵阳，等.具有APF功能的分布式光伏并网及其改进控制[J].电力电子技术，2024,58(5):59-63.Yang Shuqiang,Fan Wenyi,Zhao Yang,et al. Modified control of distributed photovoltaic grid-connected system with APF function[J].Power Electronics,2024,58(5):59-63.
• [34]陆春光，王朝亮，刘炜，等.融合时空信息的高比例分布式光伏低压台区户变识别方法[J].电力需求侧管理，2024,26(3):107-111.Lu Chunguang,Wang Chaoliang,Liu Wei,et al.Transformer-customer identification method in low voltage station with high proportion distributed photovoltaic based on fusing spatial-temporal information[J]. Power Demand Side Management,2024,26(3):107-111.
• [35]高博，闫振华，张沈习，等.含智能楼宇的主动配电网分布式光伏最大准入容量计算方法[J].电测与仪表，2025,62(12):176-183.Gao Bo,Yan Zhenhua,Zhang Shenxi,et al. Calculation method of maximum distributed photovoltaic hosting capacity of active distribution network with intelligent buildings[J].Electrical Measurement&Instrumentation,2025,62(12):176-183.
• [36]林俊，贡晓旭，高丽萍，等.高渗透率分布式光伏接入的配电网台区防逆流调控技术[J].电工技术，2025(16):130-135.Lin Jun,Gong Xiaoxu,Gao Liping,et al. Anti-backflow regulation technology for distribution network station area with high permeability distributed photovoltaic access[J].Electric Engineering,2025(16):130-135.
• [37]李响，王世谦，李秋燕，等.考虑DG和EV接入的分布式智能配电网联合规划[J].中国电机工程学报，2024,44（增刊1）:159-167.Li Xiang,Wang Shiqian,Li Qiuyan,et al.Joint planning of smart distribution grid considering distributed generation and electric vehicle charging station[J].Proceedings of the CSEE,2024,44(S1):159-167.
• [38]唐西胜，李伟，沈晓东.面向新型电力系统的储能规划方法研究进展及展望[J].电力系统自动化，2024,48(9):178-191.Tang Xisheng,Li Wei,Shen Xiaodong.Research progress and prospect of energy storage planning method for new power system[J].Automation of Electric Power Systems,2024,48(9):178-191.
• [39]张忠会，雷大勇，蒋昌辉，等.基于二阶锥规划和NNC法的交直流混合配电网双层规划模型及其求解方法[J].中国电机工程学报，2023,43(1):70-84.Zhang Zhonghui,Lei Dayong,Jiang Changhui,et al.A bilevel planning model and its solution method of AC/DC hybrid distribution network based on second-order cone programming and NNC method[J]. Proceedings of the CSEE,2023,43(1):70-84.
• [40]景祥，秦文萍，逯瑞鹏，等.信息物理耦合环境中面向韧性全过程提升的配电网无功规划[J].电力系统自动化，2025,49(6):96-105.Jing Xiang,Qin Wenping,Lu Ruipeng,et al. Reactive power planning of distribution network for whole-process resilience enhancement in cyber-physical coupling environment[J].Automation of Electric Power Systems,2025,49(6):96-105.
• [41]Ahmed H M A,Awad A S A,Ahmed M H,et al.Mitigating voltage-sag and voltage-deviation problems in distribution networks using battery energy storage systems[J].Electric Power Systems Research,2020,184:106294.
• [42]Liu Y W,Tang Y G,Hua C C.Multi-objective nutcracker optimization algorithm based on fast non-dominated sorting and elite strategy for grid-connected hybrid microgrid system scheduling[J]. Renewable Energy,2025,242:122455.