基于HSA-PSO的配电网源-储协同优化控制方法

doi:10.11930/j.issn.1004-9649.202101025

中国电力 ›› 2022, Vol. 55 ›› Issue (4): 63-69.DOI: 10.11930/j.issn.1004-9649.202101025

• 基于电力电子装备的配电网运行控制与形态演变 • 上一篇下一篇

基于HSA-PSO的配电网源-储协同优化控制方法

党彬¹, 邹启群¹, 张滨¹, 付东¹, 尤梦凯², 乐健²

1. 国网安阳供电公司，河南安阳 455000;
2. 武汉大学电气与自动化学院，湖北武汉 430072

收稿日期:2021-01-06 修回日期:2022-03-07 出版日期:2022-04-28 发布日期:2022-04-24
作者简介:党彬（1974—），男，高级工程师，从事电网规划技术研究，E-mail：1679264596@qq.com;邹启群（1971—），男，高级工程师，从事电力系统继电保护技术研究，E-mail：929679076@qq.com;尤梦凯（1994—），男，通信作者，硕士研究生，从事智能电网运行与控制技术研究，E-mail：you845990369@qq.com;乐健（1975—），男，副教授，从事电网规划技术研究，E-mail：lej01@tsinghua.org.cn
基金资助:
国家重点研发计划资助项目(配电网业务资源协同及互操作关键技术，2021 YFB2401302)

Generation-Storage Cooperative Optimization Control Method for Distribution Network Based on HSA-PSO Algorithm

DANG Bin¹, ZOU Qiqun¹, ZHANG Bin¹, FU Dong¹, YOU Mengkai², LE Jian²

1. State Grid Anyang Power Supply Company, Anyang 455000, China;
2. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China

Received:2021-01-06 Revised:2022-03-07 Online:2022-04-28 Published:2022-04-24
Supported by:
This work is supported by the National Key Research and Development Program of China (Key Technologies for Distribution Network Business Resource Collaboration and Interoperability, No.2021 YFB2401302).

摘要/Abstract

摘要： 目前通常采用增加无功补偿装置的手段来解决高渗透率分布式电源接入时的配电网电压控制及网损优化问题，而兼顾分布式电源和储能系统调节作用的控制方法较少。考虑储能系统和分布式电源的协同配合，建立以配电网电压偏差最小、有功网损最小及分布式电源消纳量最大的配电网多目标优化控制模型。有效结合和声搜索算法和粒子群优化算法，提出具有自适应能力的和声搜索-粒子群算法（HSA-PSO）对所建立的模型进行求解。通过仿真算例验证了本文优化控制方法的有效性。

关键词: 分布式电源, 分布式储能, 协调控制, 网损优化

Abstract: Currently voltage control and network loss caused by the integration of high-penetration of distributed generations are usually tackled out by means of reactive power compensation. However, there are fewer control methods that take into account distributed generations and energy storage systems. Based on the cooperation control of distributed generations and energy storage systems, this paper establishes a multi-objective optimal control model of the distribution network with the goals of minimizing voltage deviation, minimizing network power loss and maximizing the consumption of distributed generation. Combining harmony search algorithm and particle swarm optimization algorithm effectively, a harmony search-particle swarm optimal algorithm(HSA-PSO) is proposed to solve the established model. The simulation example verifies the effectiveness of the optimization control method.

Key words: distributed generation, distributed energy storage, coordinated control, network loss optimization

党彬, 邹启群, 张滨, 付东, 尤梦凯, 乐健. 基于HSA-PSO的配电网源-储协同优化控制方法[J]. 中国电力, 2022, 55(4): 63-69.

DANG Bin, ZOU Qiqun, ZHANG Bin, FU Dong, YOU Mengkai, LE Jian. Generation-Storage Cooperative Optimization Control Method for Distribution Network Based on HSA-PSO Algorithm[J]. Electric Power, 2022, 55(4): 63-69.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202101025

https://www.electricpower.com.cn/CN/Y2022/V55/I4/63

参考文献

[1] 丁阳, 汪沨, 宾峰, 等. 计及分布式电源不确定性的快速网络重构[J]. 电力系统及其自动化学报, 2018, 30(9): 57–63
DING Yang, WANG Feng, BIN Feng, et al. Fast network reconfiguration considering distributed power supply uncertainty[J]. Proceedings of the CSU-EPSA, 2018, 30(9): 57–63
[2] 赵福林, 俞啸玲, 杜诗嘉, 等. 计及需求响应的含大规模风电并网下电力系统灵活性评估[J]. 电力系统保护与控制, 2021, 49(1): 42–51
ZHAO Fulin, YU Xiaoling, DU Shijia, et al. Assessment on flexibility of a power grid with large-scale wind farm integration considering demand response[J]. Power System Protection and Control, 2021, 49(1): 42–51
[3] 刘东, 张弘, 王建春. 主动配电网技术研究现状综述[J]. 电力工程技术, 2017, 36(4): 2–7,20
LIU Dong, ZHANG Hong, WANG Jianchun. Review on the state of the art of active distribution network technology research[J]. Electric Power Engineering Technology, 2017, 36(4): 2–7,20
[4] 裴哲义, 丁杰, 李晨, 等. 分布式光伏并网问题分析与建议[J]. 中国电力, 2018, 51(10): 80–87
PEI Zheyi, DING Jie, LI Chen, et al. Analysis and suggestion for distributed photovoltaic generation[J]. Electric Power, 2018, 51(10): 80–87
[5] TONKOSKI R, LOPES L A C, EL-FOULY T H M. Coordinated active power curtailment of grid connected PV inverters for overvoltage prevention[J]. IEEE Transactions on Sustainable Energy, 2011, 2(2): 139–147.
[6] ZHANG H B, WANG S. A distributed dynamic power flow algorithm for an interconnected system containing two-terminal LCC-HVDC Tie-line[J]. IEEE Access, 2021, 9: 28673–28683.
[7] 彭生江, 陆军, 张中丹, 等. 光伏接入对电网的影响研究[J]. 电力系统保护与控制, 2021, 49(5): 157–164
PENG Shengjiang, LU Jun, ZHANG Zhongdan, et al. Research on the influence of photovoltaic access on a power grid[J]. Power System Protection and Control, 2021, 49(5): 157–164
[8] SREEKUMAR S, DEY B K, PILLAI S R B. Distributed rate adaptation and power control in fading multiple access channels[J]. IEEE Transactions on Information Theory, 2015, 61(10): 5504–5524.
[9] ZHANG X X, CHEN W R, DAI C H, et al. Dynamic multi-group self-adaptive differential evolution algorithm for reactive power optimization[J]. International Journal of Electrical Power & Energy Systems, 2010, 32(5): 351–357.
[10] RAMESH S, KANNAN S, BASKAR S. Application of modified NSGA-II algorithm to reactive power optimization[C]//Trends in Computer Science, Engineering and Information Technology, 2011.
[11] 马骞, 苏寅生, 黄河. 针对风电波动抑制的电池储能SOC鲁棒优化模型[J]. 可再生能源, 2019, 37(2): 237–242
MA Qian, SU Yinsheng, HUANG He. Robust optimization model for battery energy storage capacity for wind power fluctuation suppression[J]. Renewable Energy Resources, 2019, 37(2): 237–242
[12] DUNN B, KAMATH H, TARASCON J M. Electrical energy storage for the grid: a battery of choices[J]. Science, 2011, 334(6058): 928–935.
[13] DING C, ZHANG H M, LI X F, et al. Vanadium flow battery for energy storage: prospects and challenges[J]. The Journal of Physical Chemistry Letters, 2013, 4(8): 1281–1294.
[14] 王昊昊, 徐泰山, 马彦宏, 等. 计及多类型电源协调的有功控制策略[J]. 电力系统保护与控制, 2019, 47(4): 167–175
WANG Haohao, XU Taishan, MA Yanhong, et al. A novel active power control strategy considering multi-resource coordination[J]. Power System Protection and Control, 2019, 47(4): 167–175
[15] 刘洪, 徐正阳, 葛少云, 等. 考虑储能调节的主动配电网有功—无功协调运行与电压控制[J]. 电力系统自动化, 2019, 43(11): 51–58
LIU Hong, XU Zhengyang, GE Shaoyun, et al. Coordinated operation of active-reactive power and voltage control for active distribution network considering regulation of energy storage[J]. Automation of Electric Power Systems, 2019, 43(11): 51–58
[16] 赵健, 王奕凡, 谢桦, 等. 高渗透率可再生能源接入系统中储能应用综述[J]. 中国电力, 2019, 52(4): 167–177
ZHAO Jian, WANG Yifan, XIE Hua, et al. An overview of energy storage applications in power systems with high penetration renewable energy resources[J]. Electric Power, 2019, 52(4): 167–177
[17] 孙舟, 田贺平, 王伟贤, 等. 含新能源接入的配电网中储能系统协调控制策略[J]. 现代电力, 2018, 35(1): 19–25
SUN Zhou, TIAN Heping, WANG Weixian, et al. Coordinated control strategy of energy storage systems in distribution network with the integration of new energy[J]. Modern Electric Power, 2018, 35(1): 19–25
[18] 杨雨瑶, 张勇军, 林国营, 等. 含光储联合发电系统的配电网双目标拓展无功优化[J]. 电力系统保护与控制, 2018, 46(22): 39–46
YANG Yuyao, ZHANG Yongjun, LIN Guoying, et al. Double-objective extended reactive power optimization in distribution network with photovoltaic-energy storage hybrid systems[J]. Power System Protection and Control, 2018, 46(22): 39–46
[19] 衣庆圆, 马平. 考虑有功网损和时序性的可再生能源DG的优化配置[J]. 青岛大学学报(工程技术版), 2018, 33(4): 61–68
YI Qingyuan, MA Ping. Optimal allocation of renewable energy DG considering active power loss and timing characteristics[J]. Journal of Qingdao University (Engineering & Technology Edition), 2018, 33(4): 61–68
[20] XIE L, SU Y R. A multi-level-objective-oriented method for coordination and control of voltage and reactive power in distribution network[J]. Applied Mechanics and Materials, 2012, 263/264/265/266: 664–669.
[21] HASSAN R, COHANIM B, DE WECK O, et al. A comparison of particle swarm optimization and the genetic algorithm[C]//46 th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. Austin, Texas. Reston, Virigina: AIAA, 2005.
[22] ZHANG X, WANG X C, QI X W. Reactive power optimization for distribution system with distributed generations based on AHSPSO algorithm[C]//2016 China International Conference on Electricity Distribution (CICED). Xi'an, China. IEEE, 2016: 1–4.
[23] 高立群, 葛延峰, 孔芝, 等. 自适应和声粒子群搜索算法[J]. 控制与决策, 2010, 25(7): 1101–1104
GAO Liqun, GE Yanfeng, KONG Zhi, et al. Adaptive harmony PSO search algorithm[J]. Control and Decision, 2010, 25(7): 1101–1104
[24] MISTRY K, ZHANG L, NEOH S C, et al. A micro-GA embedded PSO feature selection approach to intelligent facial emotion recognition[J]. IEEE Transactions on Cybernetics, 2017, 47(6): 1496–1509.
[25] 刘逸. 粒子群优化算法的改进及应用研究[D]. 西安: 西安电子科技大学, 2013.
LIU Yi. Improvements and applications of particle swarm optimization algorithm[D]. Xi'an: Xidian University, 2013.

基于HSA-PSO的配电网源-储协同优化控制方法

Generation-Storage Cooperative Optimization Control Method for Distribution Network Based on HSA-PSO Algorithm

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	吴云锐, 张建坡, 田新成, 应恺锋, 陈忠. 计及频率适应和快速稳定特性的多端直流电网改进协调控制策略[J]. 中国电力, 2025, 58(3): 31-42.
[2]	何涂哲秋, 徐子东, 车欣, 张镇勇. 基于电力云边协同的非侵入式Modbus TCP协议安全增强方法[J]. 中国电力, 2024, 57(9): 53-60.
[3]	么钟然, 孙丽颖. 考虑线路阻抗的分布式储能SOC均衡控制策略[J]. 中国电力, 2024, 57(9): 238-246.
[4]	赵平, 贾浩森, 高亨孝, 李振兴. 应对岸上故障的海上风电多端柔直系统协调控制策略[J]. 中国电力, 2024, 57(8): 85-95.
[5]	彭寒梅, 尹棠, 肖千皓, 谭貌, 苏永新, 李辉. 高比例分布式电源配电网中低压柔性互联协调规划[J]. 中国电力, 2024, 57(8): 117-129.
[6]	徐峰亮, 王克谦, 王文豪, 王鹏, 王焕昌, 张帅, 赵凤展. 计及运行灵活性的中压配电系统源-网-储协同扩展规划[J]. 中国电力, 2024, 57(7): 98-108.
[7]	邵冲, 胡荣义, 余姣, 王明典. 考虑荷电与储氢状态的风光氢储系统动态控制仿真模型[J]. 中国电力, 2024, 57(7): 109-124.
[8]	凡鹏飞, 李宝琴, 侯江伟, 李嵘, 宋崇明, 林凯骏. 配电网分布式电源经济可承载力评估[J]. 中国电力, 2024, 57(7): 196-202.
[9]	王家武, 赵佃云, 刘长锋, 陈康, 张玉敏. 基于目标级联法的多主体主动配电网自治协同优化[J]. 中国电力, 2024, 57(7): 214-226.
[10]	罗美玲, 马英, 黄伟兵, 孟令昆, 于晓军, 郑涛. 计及电压幅值检测延时及相位跳变的IIDG故障电流解析计算[J]. 中国电力, 2024, 57(2): 72-81.
[11]	张俊成, 黎敏, 刘志文, 谭靖, 陶毅刚, 罗天禄. 配电网用户侧多类型柔性资源调节能力评估方法[J]. 中国电力, 2023, 56(9): 96-103,119.
[12]	王激华, 叶夏明, 秦如意, 应芳义, 俞佳捷. 基于指数型下垂控制的氢电混合储能微网协调控制策略研究[J]. 中国电力, 2023, 56(7): 43-53.
[13]	叶畅, 伊华茂, 朱炯达, 赵晶晶, 吴炼. 考虑灵活性供需平衡及响应速度的分布式电源集群划分方法[J]. 中国电力, 2023, 56(2): 150-156.
[14]	郭之栋, 胡存刚, 芮涛, 罗魁, 林振锋. 基于动态电价机制的用户侧分布式储能电能交易策略[J]. 中国电力, 2023, 56(1): 28-37.
[15]	谢学渊, 刘潇潇, 李超, 胡资鹏, 刘铠, 陈涛. 考虑分布式电源和电动汽车集群调度的配电网络重构[J]. 中国电力, 2023, 56(1): 119-125.

模态框（Modal）标题

基于HSA-PSO的配电网源-储协同优化控制方法

Generation-Storage Cooperative Optimization Control Method for Distribution Network Based on HSA-PSO Algorithm

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics