考虑分布式电源和电动汽车集群调度的配电网络重构

doi:10.11930/j.issn.1004-9649.202109121

中国电力 ›› 2023, Vol. 56 ›› Issue (1): 119-125.DOI: 10.11930/j.issn.1004-9649.202109121

考虑分布式电源和电动汽车集群调度的配电网络重构

谢学渊¹, 刘潇潇¹, 李超¹, 胡资鹏¹, 刘铠¹, 陈涛²

1. 国网湖南省电力有限公司节能管理分公司，湖南长沙 410000;
2. 东南大学电气工程学院，江苏南京 210096

收稿日期:2021-09-29 修回日期:2022-12-04 出版日期:2023-01-28 发布日期:2023-01-14
作者简介:谢学渊(1967-),男,高级经济师,从事综合能源研究,E-mail:xiexy1@hn.sgcc.com.cn;刘潇潇(1983-),男,硕士,高级工程师,从事信息化建设研究,E-mail:190091108@qq.com;李超(1989-),男,硕士,工程师,从事配网检修研究,E-mail:316815144@qq.com;胡资鹏(1988-),男,硕士,工程师,从事智慧园区建设研究,E-mail:552437178@qq.com;刘铠(1993-),男,工程师,从事电力大数据研究,E-mail:158134534@qq.com;陈涛(1989-),男,博士,讲师,从事电力需求侧管理、人工智能应用研究,E-mail:taoc@seu.edu.cn
基金资助:
国家自然科学青年基金资助项目（52107079）；上海市科技计划资助项目（20dz1206200）。

Distribution Network Reconfiguration Considering Distributed Generation and Electric Vehicle Cluster Scheduling

XIE Xueyuan¹, LIU Xiaoxiao¹, LI Chao¹, HU Zipeng¹, LIU Kai¹, CHEN Tao²

1. Energy Saving Management Branch of State Grid Hunan Electric Power Co., Ltd., Changsha 410000, China;
2. School of Electrical Engineering, Southeast University, Nanjing 210096, China

Received:2021-09-29 Revised:2022-12-04 Online:2023-01-28 Published:2023-01-14
Supported by:
This work is supported by the National Natural Science Foundation of China Youth Fund Project (No.52107079), Shanghai Science and Technology Project (No.20dz1206200).

摘要/Abstract

摘要： 随着分布式电源和电动汽车等灵活性电力资源大量接入配电网，对系统安全可靠性提出了更高要求。提出一种考虑分布式电源和电动汽车集群调度的配电网络重构方法，以提高系统可靠性和经济性。在考虑电压偏差的基础上，以故障停电损失成本作为衡量电网可靠性的经济性指标，对网络拓扑结构进行重新构建。首先以线路的开关状态、电动汽车充、放电状态及功率为决策变量，建立以综合成本最小为目标的配电网络重构模型；然后针对配电网络重构模型，采用共生生物搜索算法进行模型求解；最后，通过仿真算例验证了所提方法的有效性。

关键词: 配电网络重构, 分布式电源, 电动汽车集群调度, 共生生物搜索算法

Abstract: Along with the connection of numerous flexible resources such as distributed generation and electric vehicles (EVs) to distribution networks, higher requirements are raised on system security and reliability. A distribution network reconfiguration method based on distributed generation and EV cluster scheduling is thus proposed to improve the system security and reliability. With consideration of voltage deviation, the network topology structure is reconstructed by taking the failure loss cost of power grid as an economic index to measure the power network reliability. Firstly, a distribution network reconfiguration model is established to minimize the comprehensive cost by taking the switching state of power lines, the charging and discharging state and power of EVs as decision variables. Then, the symbiotic search algorithm is used to solve the reconfiguration model. Finally, the effectiveness of the proposed method is verified via simulation of a distribution system.

Key words: distribution network reconfiguration, distributed generation, electric vehicle cluster scheduling, symbiotic organism search algorithm

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.

XIE Xueyuan, LIU Xiaoxiao, LI Chao, HU Zipeng, LIU Kai, CHEN Tao. Distribution Network Reconfiguration Considering Distributed Generation and Electric Vehicle Cluster Scheduling[J]. Electric Power, 2023, 56(1): 119-125.

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202109121

https://www.electricpower.com.cn/CN/Y2023/V56/I1/119

参考文献

[1] 王利利, 王皓, 任洲洋, 等. 计及灵活资源调节潜力的高压配电网新能源接纳能力评估[J]. 中国电力, 2022, 55(10): 124–131
WANG Lili, WANG Hao, REN Zhouyang, et al. Evaluation of renewable energy accommodation capacity of high voltage distribution networks considering regulation potential of flexible resources[J]. Electric Power, 2022, 55(10): 124–131
[2] 陈浩, 胡俊杰, 袁海峰, 等. 计及配电网拥塞的集群电动汽车参与二次调频方法研究[J]. 中国电力, 2021, 54(12): 162–169
CHEN Hao, HU Junjie, YUAN Haifeng, et al. Research on supplementary frequency regulation with aggregated electric vehicles considering distribution network congestion[J]. Electric Power, 2021, 54(12): 162–169
[3] 姜萌萌, 佟永吉, 陈明丰, 等. 基于灾害条件的主动配电网快速重构策略研究[J]. 智慧电力, 2021, 49(5): 85–92
JIANG Mengmeng, TONG Yongji, CHEN Mingfeng, et al. Rapid reconfiguration strategy of active distribution network under disaster conditions[J]. Smart Power, 2021, 49(5): 85–92
[4] GUO X T, YAN F L, XUE X W, et al. QoS-aware data center network reconfiguration method based on deep reinforcement learning[J]. Journal of Optical Communications and Networking, 2021, 13(5): 94–107.
[5] 孔令飞, 王淳, 熊云, 等. 模拟植物多向生长的配电网重构算法[J]. 电测与仪表, 2016, 53(24): 1–5
KONG Lingfei, WANG Chun, XIONG Yun, et al. Plant multi-direction growth simulation algorithm for the distribution network reconfiguration[J]. Electrical Measurement & Instrumentation, 2016, 53(24): 1–5
[6] 彭文强, 毛弋, 邓海潮, 等. 改进型细菌觅食算法应用于配电网络重构[J]. 电力系统及其自动化学报, 2017, 29(7): 93–97
PENG Wenqiang, MAO Yi, DENG Haichao, et al. Application of improved bacterial foraging algorithm to distribution network reconfiguration[J]. Proceedings of the CSU-EPSA, 2017, 29(7): 93–97
[7] 程虹, 高元海, 王淳, 等. 基于无重访NSGA-Ⅱ算法的配电网多目标重构[J]. 电力系统保护与控制, 2016, 44(23): 10–16
CHENG Hong, GAO Yuanhai, WANG Chun, et al. Multi-objective distribution network reconfiguration base on non-revisiting NSGA-Ⅱ algorithm[J]. Power System Protection and Control, 2016, 44(23): 10–16
[8] 刘志勇, 刘杨华, 林舜江, 等. 基于模糊多目标协调优化的配电网络重构研究[J]. 电力系统保护与控制, 2014, 42(4): 133–138
LIU Zhiyong, LIU Yanghua, LIN Shunjiang, et al. Fuzzy multi-objective coordination optimization for distribution network reconfiguration[J]. Power System Protection and Control, 2014, 42(4): 133–138
[9] 李旸, 唱友义, 梁晓赫. 新能源接入的配电网效益最优重构方法研究[J]. 控制工程, 2021, 28(5): 931–937
LI Yang, CHANG Youyi, LIANG Xiaohe. Research on an optimal reconfiguration method of distribution network benefits with new energy access[J]. Control Engineering of China, 2021, 28(5): 931–937
[10] 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 Xiaoming, LV Hongfang, ZHU Hui. Reconfiguration of distribution network based on improved artificial fish swarm algorithm[J]. Electrical Measurement & Instrumentation, 2020, 57(17): 72–78,98
[11] MUHAMMAD M A, MOKHLIS H, NAIDU K, et al. Distribution network planning enhancement via network reconfiguration and DG integration using dataset approach and water cycle algorithm[J]. Journal of Modern Power Systems and Clean Energy, 2019, 8(1): 86–93.
[12] WANG C, LEI S B, JU P, et al. MDP-based distribution network reconfiguration with renewable distributed generation: approximate dynamic programming approach[J]. IEEE Transactions on Smart Grid, 2020, 11(4): 3620–3631.
[13] 张涛, 张东方, 王凌云. 基于二进制量子粒子群的含电动汽车主动配电网多目标重构[J]. 电测与仪表, 2018, 55(9): 42–47
ZHANG Tao, ZHANG Dongfang, WANG Lingyun. Multi-objective reconstruction of active distribution network with electric vehicle based on binary quantum particle swarm optimization[J]. Electrical Measurement & Instrumentation, 2018, 55(9): 42–47
[14] 孙琪, 于永进, 王玉彬, 等. 采用改进鲸鱼算法的配电网综合优化[J]. 电力系统及其自动化学报, 2021, 33(5): 22–29
SUN Qi, YU Yongjin, WANG Yubin, et al. Comprehensive optimization of distribution network using improved whale optimization algorithm[J]. Proceedings of the CSU-EPSA, 2021, 33(5): 22–29
[15] WANG X Y, SUN C, WANG R T, et al. Two-stage optimal scheduling strategy for large-scale electric vehicles[J]. IEEE Access, 2020, 8: 13821–13832.
[16] 甘季伟, 姚志垒. 基于需求响应的电动汽车充放电策略对比与分析[J]. 电力需求侧管理, 2021, 23(3): 36–40
GAN Jiwei, YAO Zhilei. Comparison and analysis of charging and discharging strategies for electric vehicles based on demand response[J]. Power Demand Side Management, 2021, 23(3): 36–40
[17] 贾鹤鸣, 李瑶, 姜子超, 等. 基于改进共生生物搜索算法的林火图像多阈值分割[J]. 计算机应用, 2021, 41(5): 1465–1470
JIA Heming, LI Yao, JIANG Zichao, et al. Multi-threshold segmentation of forest fire images based on modified symbiotic organisms search algorithm[J]. Journal of Computer Applications, 2021, 41(5): 1465–1470
[18] 秦旋, 房子涵, 张赵鑫. 混合共生生物搜索算法求解置换流水车间调度问题[J]. 浙江大学学报(工学版), 2020, 54(4): 712–721
QIN Xuan, FANG Zihan, ZHANG Zhaoxin. Hybrid symbiotic organisms search algorithm for permutation flow shop scheduling problem[J]. Journal of Zhejiang University (Engineering Science), 2020, 54(4): 712–721
[19] KAVOUSI-FARD A, ALI ROSTAMI M, NIKNAM T. Reliability-oriented reconfiguration of vehicle-to-grid networks[J]. IEEE Transactions on Industrial Informatics, 2015, 11(3): 682–691.
[20] 王毅, 麻秀, 万毅, 等. 基于分时充放电裕度的电动汽车有序充放电引导策略[J]. 电网技术, 2019, 43(12): 4353–4361
WANG Yi, MA Xiu, WAN Yi, et al. Sequential charge-discharge guidance strategy for electric vehicles based on time-sharing charging-discharging margin[J]. Power System Technology, 2019, 43(12): 4353–4361
[21] 潘樟惠, 高赐威, 刘顺桂. 基于需求侧放电竞价的电动汽车充放电调度研究[J]. 电网技术, 2016, 40(4): 1140–1146
PAN Zhanghui, GAO Ciwei, LIU Shungui. Research on charging and discharging dispatch of electric vehicles based on demand side discharge bidding[J]. Power System Technology, 2016, 40(4): 1140–1146
[22] 朱磊, 黄河, 高松, 等. 计及风电消纳的电动汽车负荷优化配置研究[J]. 中国电机工程学报, 2021, 41(增刊1): 194–203
ZHU Lei, HUANG He, GAO Song, et al. Research on optimal load allocation of electric vehicle considering wind power consumption[J]. Proceedings of the CSEE, 2021, 41(S1): 194–203
[23] HAN C, ZHOU G, ZHOU Y Q. Binary symbiotic organism search algorithm for feature selection and analysis[J]. IEEE Access, 2019, 7: 166833–166859.
[24] 刘云, 张洁羽, 樊浩研, 等. 分布式电源配电网络多目标优化重构方法研究[J]. 国外电子测量技术, 2021, 40(3): 83–87
LIU Yun, ZHANG Jieyu, FAN Haoyan, et al. Research on multi objective optimization reconfiguration method of distributed generation distribution network[J]. Foreign Electronic Measurement Technology, 2021, 40(3): 83–87
[25] 刘永梅, 王金丽, 杨红磊, 等. 计及柔性负荷调节能力的有源配电网动态优化方法[J]. 高电压技术, 2021, 47(1): 73–80
LIU Yongmei, WANG Jinli, YANG Honglei, et al. Dynamic optimal method of distribution network in consideration of flexible load adjustment capability[J]. High Voltage Engineering, 2021, 47(1): 73–80

考虑分布式电源和电动汽车集群调度的配电网络重构

Distribution Network Reconfiguration Considering Distributed Generation and Electric Vehicle Cluster Scheduling

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]	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.
[2]	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.
[3]	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.
[4]	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.
[5]	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.
[6]	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.
[7]	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.
[8]	张黎明, 李浩, 吴亚雄, 高崇, 张俊潇, 刘涌. 基于运行优化的含储能电力系统可靠性评估方法[J]. 中国电力, 2022, 55(9): 23-28.
[9]	杨作祥, 王晶晶, 吴江, 唐莎莎, 侯斌. 计及源荷不确定性的配电网综合节能潜力评估方法[J]. 中国电力, 2022, 55(8): 151-156,164.
[10]	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.
[11]	赵一男, 宋斌, 钱振宇, 李顺昕. 未来配电网的分布式形态及规划方法[J]. 中国电力, 2022, 55(4): 70-77.
[12]	陈卫东, 郭敏, 吴宁, 奉斌. 基于图像匹配的微电网负荷响应分布式电源波动控制方法[J]. 中国电力, 2022, 55(3): 57-63,73.
[13]	杨亘烨, 孙荣富, 丁然, 徐海翔, 陈璨, 吴林林, 陈奇芳, 夏明超. 计及光伏多状态调节能力的配电网多时间尺度电压优化[J]. 中国电力, 2022, 55(3): 105-114.
[14]	张燕, 乔松博, 徐奇锋, 俞静. 基于纳什议价理论的分布式绿色电力交易优化分析[J]. 中国电力, 2022, 55(12): 168-178.
[15]	王巍璋, 王淳, 尹发根. 基于可达矩阵和贝叶斯定理的含分布式电源的配电网故障区段定位[J]. 中国电力, 2021, 54(7): 93-99,124.

模态框（Modal）标题

考虑分布式电源和电动汽车集群调度的配电网络重构

Distribution Network Reconfiguration Considering Distributed Generation and Electric Vehicle Cluster Scheduling

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