基于拉格朗日松弛技术的复杂有源配电网分布式状态估计
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摘要
为了提高复杂有源配电网状态估计问题的计算速度,提出了一种基于拉格朗日松弛技术的复杂有源配电网分布式状态估计方法。建立了复杂有源配电网分区模型,该模型从复杂有源配电网的量测配置情况和分布式并行计算效率角度出发,综合考虑了分区后各子区域的计算速度与精度,利用拉格朗日松弛技术将分区问题中的约束条件吸收到目标函数中,降低了分区模型的求解难度。通过网络解耦技术使各子区域相对独立,可在分布式并行环境下求解该网络的状态估计问题。各子区域选取指数型目标函数状态估计模型,该模型能够自动排除不良数据影响,在保证结果精度的同时有效减小了所求问题的系统规模和雅可比矩阵阶数,提高了状态估计算法效率。仿真算例结果表明,所提方法可实现对复杂有源配电网的合理分区,有效提高了状态估计的计算速度。
Due to the slow calculation speed of state estimation in complex active distribution network, a distributed state estimation of complex active distribution network based on Lagrange relaxation technique is proposed. A partition model of complex active distribution network is established, in which the measurement configuration of complex active distribution network and distributed parallel computing efficiency are analyzed. The calculation speed and accuracy of each sub-region after partition are also considered. By using the Lagrange relaxation technique, the constraint conditions are absorbed into the objective function, which can reduce the difficulty of solving the partition model. The state estimation problem of the network can be solved in a distributed parallel environment by using the network decoupling method. The state estimation of each sub-region is carried out by using the state estimation method with exponential objective function which can automatically exclude bad data effects, which effectively reduces the system size and Jacobi matrix order of the problem, and improves the efficiency of the state estimation algorithm while ensuring the accuracy of the results. Simulation results show that the proposed method can achieve reasonable partition in a complex active distribution network, and the calculation speed of the state estimation is largely improved.
Due to the slow calculation speed of state estimation in complex active distribution network, a distributed state estimation of complex active distribution network based on Lagrange relaxation technique is proposed. A partition model of complex active distribution network is established, in which the measurement configuration of complex active distribution network and distributed parallel computing efficiency are analyzed. The calculation speed and accuracy of each sub-region after partition are also considered. By using the Lagrange relaxation technique, the constraint conditions are absorbed into the objective function, which can reduce the difficulty of solving the partition model. The state estimation problem of the network can be solved in a distributed parallel environment by using the network decoupling method. The state estimation of each sub-region is carried out by using the state estimation method with exponential objective function which can automatically exclude bad data effects, which effectively reduces the system size and Jacobi matrix order of the problem, and improves the efficiency of the state estimation algorithm while ensuring the accuracy of the results. Simulation results show that the proposed method can achieve reasonable partition in a complex active distribution network, and the calculation speed of the state estimation is largely improved.
引文
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[17]吕涛,唐巍,丛鹏伟,等.分布式电源与配电网架多目标协调规划[J].电力系统自动化,2013,37(21):139-145.LüTao,TANG Wei,CONG Pengwei,et al.Multi-objective coordinated planning of distribution network incorporating distributed generators[J].Automation of Electric Power Systems,2013,37(21):139-145.
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[23]郭烨,张伯明,吴文传.指数型目标函数电力系统抗差状态估计的解法与性能分析[J].中国电机工程学报,2011,31(7):89-95.GUO Ye,ZHANG Boming,WU Wenchuan.Solution and performance analysis to a robust state estimation method with exponential objective function[J].Proceedings of the CSEE,2011,31(7):89-95.
[2]巨云涛,林毅,王晶,等.考虑分布式电源详细模型的配电网多相状态估计[J].电力系统保护与控制,2016,44(23):147-152.JU Yuntao,LIN Yi,WANG Jing,et al.Multi-phase distribution state estimation considering detailed models of distributed generators[J].Power System Protection and Control,2016,44(23):147-152.
[3]曾博,杨煦,张建华.考虑可再生能源跨区域消纳的主动配电网多目标优化调度[J].电工技术学报,2016,31(22):148-158.ZENG Bo,YANG Xu,ZHANG Jianhua.Multi-objective optimization for active distribution network scheduling considering renewable energy harvesting across regions[J].Transactions of China Electrotechnical Society,2016,31(22):148-158.
[4]徐创学,刘鲁清,谢云明,等.基于实时数据的风力发电机组性能在线评价[J].热力发电,2015,44(4):88-91.XU Chuangxue,LIU Luqing,XIE Yunming,et al.Real-time data based online evaluation of output performance for wind turbine units[J].Thermal Power Generation,2015,44(4):88-91.
[5]胡玥,徐钢,段栋伟,等.碳减排技术发展现状[J].热力发电,2017,46(2):1-6.HU Yue,XU Gang,DUAN Dongwei,et al.Current situation and performance comparison of carbon capture technologies[J].Thermal Power Generation,2017,46(2):1-6.
[6]张跃,杨汾艳,曾杰,等.主动配电网的分布式电源优化规划方案研究[J].电力系统保护与控制,2015,43(15):67-72.ZHANG Yue,YANG Fenyan,ZENG Jie,et al.Research of distributed generation optimization planning for active distributed network[J].Power System Protection and Control,2015,43(15):67-72.
[7]范士雄,蒲天骄,刘广一,等.主动配电网中分布式发电系统接入技术及其进展[J].电工技术学报,2016,31(增刊2):92-101.FAN Shixiong,PU Tianjiao,LIU Guangyi,et al.Technologies and its trends of grid integration of distributed generation in active distribution network[J].Transactions of China Electrotechnical Society,2016,31(S2):92-101.
[8]李滨,杜孟远,祝云,等.基于准实时数据的智能配电网状态估计[J].电工技术学报,2016,31(1):34-44.LI Bin,DU Mengyuan,ZHU Yun,et al.A state estimator for smart distribution networks with quasi-real Time data[J].Transactions of China Electrotechnical Society,2016,31(1):34-44.
[9]巨云涛,吴文传,程学启,等.基于多源信息的配电网电流匹配状态估计[J].电力系统自动化,2012,36(16):53-57.JU Yuntao,WU Wenchuan,CHENG Xueqi,et al.Multisource information based on current matching state estimation for distribution network[J].Automation of Electric Power Systems,2012,36(16):53-57.
[10]黄伟,庞琳,曹彬,等.基于分区解耦的配电网状态估计的分布式并行计算[J].电力系统保护与控制,2014,42(15):45-51.HUANG Wei,PANG Lin,CAO Bin,et al.Parallel and distributed computing for an area-decoupled state estimation method for distribution systems[J].Power System Protection and Control,2014,42(15):45-51.
[11]刘明,周双喜,邓佑满,等.配电系统状态估计区域解耦算法[J].电力系统自动化,2005,29(6):79-83.LIU Ming,ZHOU Shuangxi,DENG Youman,et al.An area-decoupled state estimation method for distribution systems[J].Automation of Electric Power Systems,2005,29(6):79-83.
[12]卫志农,陈胜,孙国强,等.含多类型分布式电源的主动配电网分布式三相状态估计[J].电力系统自动化,2015,39(9):68-74.WEI Zhinong,CHEN Sheng,SUN Guoqiang,et al.Distributed three-phase state estimation for active distribution network integrated with different types of distributed generators[J].Automation of Electric Power Systems,2015,39(9):68-74.
[13]高明,徐青山,齐锐,等.一种配电网状态估计实用快速算法[J].广东电力,2015,28(2):101-106.GAO Ming,XU Qingshan,QI Rui,et al.Practical fast algorithm for state estimation on power distribution network[J].Guangdong Electric Power,2015,28(2):101-106.
[14]侯雨伸,白雪峰,郭志忠.计及AMI的配网分层状态估计及伪量测计算[J].电力系统及其自动化学报,2014,26(8):71-76.HOU Yushen,BAI Xuefeng,GUO Zhizhong.Layered method for distribution system state estimation and pseudo measurement calculation considering AMI[J].Proceedings of the CSU-EPSA,2014,26(8):71-76.
[15]栾文鹏.高级量测体系[J].南方电网技术,2009,3(2):6-10.LUAN Wenpeng.Advanced metering infrastructure[J].Southern Power System Technology,2009,3(2):6-10.
[16]黄知超,谢霞,王斌.结合模糊综合评判与决策的电力系统状态估计[J].电力系统保护与控制,2015,43(7):65-69.HUANG Zhichao,XIE Xia,WANG Bin.Power system state estimation combined with fuzzy comprehensive evaluation and decision-making[J].Power System Protection and Control,2015,43(7):65-69.
[17]吕涛,唐巍,丛鹏伟,等.分布式电源与配电网架多目标协调规划[J].电力系统自动化,2013,37(21):139-145.LüTao,TANG Wei,CONG Pengwei,et al.Multi-objective coordinated planning of distribution network incorporating distributed generators[J].Automation of Electric Power Systems,2013,37(21):139-145.
[18]刘科研,盛万兴,刘永梅.一种基于层次化聚类自动分区的分布式并行潮流计算方法,中国:CN103326351A[P].2013-09-25.
[19]VAN DEN BERGH F,ENGELBRECHT A P.A cooperative approach to particle swarm optimization[J].IEEE Transactions on Evolutionary Computation,2004,8(3):1-15.
[20]赵洪三,田甜.基于自适应无迹卡尔曼滤波的电力系统动态状态估计[J].电网技术,2014,38(1):3790-3794.ZHAO Hongsan,TIAN Tian.Dynamic state estimation for power system based on an adaptive unscented Kalman filter[J].Power System Technology,2014,38(1):3790-3794.
[21]KENNEDY J,EBERHART R.Particle swarm optimization[C]//IEEE International Conference on Proceedings.Perth,WA:IEEE,1995:1942-1948.
[22]吴文传,郭烨,张伯明.指数型目标函数电力系统抗差状态估计[J].中国电机工程学报,2011,31(4):67-71.WU Wenchuan,GUO Ye,ZHANG Boming.A robust state estimation method with exponential objective function[J].Proceedings of the CSEE,2011,31(4):67-71.
[23]郭烨,张伯明,吴文传.指数型目标函数电力系统抗差状态估计的解法与性能分析[J].中国电机工程学报,2011,31(7):89-95.GUO Ye,ZHANG Boming,WU Wenchuan.Solution and performance analysis to a robust state estimation method with exponential objective function[J].Proceedings of the CSEE,2011,31(7):89-95.