考虑数据时变性的主动配电网动态网络重构
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摘要
目前的配电网网架重构主要考虑停电发生时刻单场景下的电网信息,但实际上贯穿于整个故障修复时期,仅考虑停电发生时刻的电网信息可能造成后续时段电网过载,因此本文提出计及数据时变性的动态网络重构方案。本文以分布式电源大规模接入下的主动配电网为研究对象,首先基于贪婪法思想提出单一场景下的网络重构方法,然后利用负荷及各类分布式电源的预测信息,以故障排除周期内能量损失最少为目标建立基于连续场景考虑数据时变性的动态网络重构模型。同时本文引入滚动优化的思想,对动态网络重构方案进行纠偏,以适应分布式电源的随机波动。最后,通过仿真分析,论证了分布式电源对优化系统恢复方案的作用,说明了所提模型和方法的有效性。
The distribution network reconfiguration mainly considers the grid information in the single scene when the fault occurs,but actually it is through the whole fault repair period,and thus only consider the grid information at the time of power failure may lead to the overload of the grid in subsequent periods. Therefore,this paper proposes a dynamic network reconstruction scheme that takes into account the time-varying data. This paper takes the active distribution network under the large-scale access of distributed power supply as the research object. Firstly,a network reconfiguration method in a single scenario is proposed based on greedy method. Then,a dynamic network reconfiguration model considering time-varying data in continuous scenarios is established with the objective of minimizing energy loss during the fault removal cycle by using the prediction information of load and various distributed generations( DG). At the same time,the idea of rolling optimization is introduced to correct the deviation of the dynamic network reconfiguration scheme to adapt to the random fluctuation of distributed generation. Finally,through simulation analysis,the effect of distributed power supply on optimizing system recovery scheme is demonstrated,and the effectiveness of the proposed model and method is illustrated.
The distribution network reconfiguration mainly considers the grid information in the single scene when the fault occurs,but actually it is through the whole fault repair period,and thus only consider the grid information at the time of power failure may lead to the overload of the grid in subsequent periods. Therefore,this paper proposes a dynamic network reconstruction scheme that takes into account the time-varying data. This paper takes the active distribution network under the large-scale access of distributed power supply as the research object. Firstly,a network reconfiguration method in a single scenario is proposed based on greedy method. Then,a dynamic network reconfiguration model considering time-varying data in continuous scenarios is established with the objective of minimizing energy loss during the fault removal cycle by using the prediction information of load and various distributed generations( DG). At the same time,the idea of rolling optimization is introduced to correct the deviation of the dynamic network reconfiguration scheme to adapt to the random fluctuation of distributed generation. Finally,through simulation analysis,the effect of distributed power supply on optimizing system recovery scheme is demonstrated,and the effectiveness of the proposed model and method is illustrated.
引文
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[13]HUAJIE DING,ZECHUN HU,YONGHUA SONG.Rolling optimization of wind farm and energy storage system in electricity markets[J].IEEETransactions on Power Systems,2015,30(05):2676-2684.
[14]WEI ZHU,ZHONGPING JIANG.Event-based leader-following consensus of multi-agent systems with input time delay[J].IEEE Transactions on Automatic control,2015,60(05):1362-1367.
[15]BAO YUQING,LI YANG,WANG BEIBEI,et al.Demand response for frequency control of multi-area power system[J].Journal of Modern Power Systems and Clean Energy,2017,5(01):20-29.
[16]肖浩,裴玮,孔力.基于模型预测控制的微电网多时间尺度协调优化调度[J].电力系统自动化,2016,40(18):7-14+55.XIAO Hao,PEI Wei,KONG Li.Multi-time scale coordinated optimal dispatch of microgrid based on model predictive control[J].Automation of Electric Power Systems,2016,40(18):7-14+55.
[2]赵月辉,彭钰莹,顾全,等.含分布式能源的主动配电网实时拓扑追踪[J].电力大数据,2018,21(06):44-50.ZHAO Yuehui,PENG Yuying,GU Quan,et al.Real-timetopology tracing for active power distribution network with distributed energy[J].Power Systems and Big Data,2018,21(06):44-50.
[3]钟清,张文峰,周佳威,等.主动配电网分层分布控制策略及实现[J].电网技术,2015,39(06):1511-1517.ZHONG Qing,ZHANG Wenfeng,ZHOU Jiawei,et al.Hierarchical and distributed control strategy for active distribution network&its implementation[J].Power System Technology,2015,39(06):1511-1517.
[4]张嵩,刘洋,许芳,侯喆瑞.配电网中大数据的挖掘应用[J].电力大数据,2018,21(02):8-12.ZHANG Song,LIU Yang,XU Fang,et al.Application of big data mining in power distribution network[J].Power Systems and Big Data,2018,21(02):8-12.
[5]杨凤生,熊波,蔡广林,等.基于数据分析的配电网故障数据特征变量提取[J].电力大数据,2018,21(03):22-26.YANG Fengsheng,XIONG Bo,CAI Guanglin,et al.Characteristic variable extraction of fault data in distribution feeder based on data analysis[J].Power Systems and Big Data,2018,21(03):22-26.
[6]冒国龙,李君卫.面向供电可靠性的配电自动化建设研究[J].电力大数据,2018,21(02):54-60.MAO Guolong,LI Junwei.Research on distribution automation construction for power supply reliability[J].Power Systems and Big Data,2018,21(02):54-60.
[7]白新雷,郭力萍,王凯.基于多目标优化的配电网负荷转移路径研究[J].电网与清洁能源,2013,29(12):11-15.BAI Xinlei,GUO Liping,WANG Kai.Research on distribution network load transferring path based on multi-objective optimization[J].Power System and Clean Energy,2013,29(12):11-15.
[8]郭力,刘文建,焦冰琦,等.独立微网系统的多目标优化规划设计方法[J].中国电机工程学报,2014,34(04):524-536.GUO Li,LIU Wenjian,JIAO Bingqi,et al.Multi-objective optimal planning design method forstand-alone microgrid system[J].Proceedings of the CSEE,2014,34(04):524-536
[9]MORADI M H,ESKANDARI M,MAHDI HOSSEINIAN S.Operational strategy optimization in an optimal sized smart microgrid[J].Smart Grid,IEEE Transactions on,2015,6(03):1087-1095.
[10]马草原,孙展展,尹志超,等.基于双重混合粒子群算法的配电网重构[J].电工技术学报,2016,31(11):120-128.MA Caoyuan,SUN Zhanzhan,YIN Zhichao,et al.Reconfiguration of distribution network based on double hybrid particle swarm algorithm[J].Transactions of China Electrotechnical Society,2016,31(11):120-128.
[11]李佩杰,陆镛,白晓清,等.基于交替方向乘子法的动态经济调度分散式优化[J].中国电机工程学报,2015,35(10):2428-2435.LI Peijie,LU Yong,BAI Xiaoqing,et al.Decentralized optimization for dynamic economic dispatch based on alternating direction method of multipliers[J].Proceedings of the CSEE,2015,35(10):2428-2435.
[12]于文鹏,刘东,翁嘉明.含分布式电源的配电网供电恢复模型及改进贪婪算法[J].电力系统自动化,2013,47(24):23-30.YU Wenpeng,LIU Dong,WENG Ximing.A power restoring model for distribution network containing distributed generators and improved greedy algorithm[J].Automation of Electric Power Systems,2013,47(24):23-30.
[13]HUAJIE DING,ZECHUN HU,YONGHUA SONG.Rolling optimization of wind farm and energy storage system in electricity markets[J].IEEETransactions on Power Systems,2015,30(05):2676-2684.
[14]WEI ZHU,ZHONGPING JIANG.Event-based leader-following consensus of multi-agent systems with input time delay[J].IEEE Transactions on Automatic control,2015,60(05):1362-1367.
[15]BAO YUQING,LI YANG,WANG BEIBEI,et al.Demand response for frequency control of multi-area power system[J].Journal of Modern Power Systems and Clean Energy,2017,5(01):20-29.
[16]肖浩,裴玮,孔力.基于模型预测控制的微电网多时间尺度协调优化调度[J].电力系统自动化,2016,40(18):7-14+55.XIAO Hao,PEI Wei,KONG Li.Multi-time scale coordinated optimal dispatch of microgrid based on model predictive control[J].Automation of Electric Power Systems,2016,40(18):7-14+55.