Abstract：In order to comprehensively achieve monitoring and diagnosis of the power quality disturbance events in the smart grid as well as consider the optimization of system costs and the interconnection of distributed generators, this paper analyzes the deficiencies of the existing optimal allocation methods for the power quality (PQ) monitors. The model and steps of the binary particle swarm optimization (BPSO) are improved, and a new evaluation function is constructed. Considering the entirely observable network in the domain of the node voltage sag and the completeness of the current information, a novel allocation method based on improved particle swarm optimization is proposed. The improved BPSO is used to iterate the optimal allocation of PQ monitoring sites. Thus the system optimization between the performance and the costs is achieved. Finally, the simulations are carried out using four kinds of distribution networks. The results show that, with fast convergence and good applicability, the proposed algorithm can effectively achieve the diagnosis and optimal allocation of the PQ monitoring sites at a low cost.
[1] MBarr J, Majumder R. Integration of distributed generation in the Volt/VAR management system for active distribution networks[J]. IEEE Transactions on Smart Grid, 2015, 6(2): 576-586. [2] 刘蓓, 汪沨, 陈春, 等. 和声算法在含DG配电网故障定位中的应用[J]. 电工技术学报, 2013, 28(5): 280-286. Liu Bei, Wang Feng, Chen Chun, et al. Harmony search algorithm for solving fault location in distri- bution networks with DG[J]. Transactions of China Electrotechnical Society, 2013, 28(5): 280-286. [3] Chenine M, Ullberg J, Nordstrom L, et al. A framework for wide-area monitoring and control systems interoperability and cybersecurity analysis[J]. IEEE Transactions on Power Delivery, 2014, 29(2): 633-641. [4] Won D, Chung I, Kim J, et al. A new algorithm to locate power-quality event source with improved realization of distributed monitoring scheme[J]. IEEE Transactions on Power Delivery, 2006, 21(3): 1641- 1647. [5] Won D, Ahn S, Chung I, et al. A new algorithm to find the optimal numbers and locations of power quality monitors[C]//IEEE Russia Power Tech, 2005: 1-7. [6] 翁国庆, 张有兵. 网络化电能质量监测与分析系统的设计[J]. 电力系统自动化, 2008, 32(15): 79-83. Weng Guoqing, Zhang Youbing. Design of a networked power quality monitoring and analysis system[J]. Automation of Electric Power Systems, 2008, 32(15): 79-83. [7] 周超, 田立军. 基于粒子群优化算法的电压暂降监测点优化配置[J]. 电工技术学报, 2014, 29(4): 181- 187. Zhou Chao, Tian Lijun. An optimum allocation method of voltage sag monitoring nodes based on particle swarm optimization algorithm[J]. Transa- ctions of China Electrotechnical Society, 2014, 29(4): 181-187. [8] Ali S, Wu K, Weston K,et al. A machine learning approach to meter placement for power quality estimation in smart grid[J]. IEEE Transactions on Smart Grid, 2015, 6(6): 542-547. [9] 唐亚迪, 徐永海, 洪旺松. 基于模糊控制模型的电压暂降监测装置优化配置[J]. 电力自动化设备, 2015, 35(8): 1-7. Tang Yadi, Xu Yonghai, Hong Wangsong. Allocation optimization based on fuzzy control model for voltage-sag monitors[J]. Electric Power Automation Equipment, 2015, 35(8): 1-7. [10] 徐志超, 杨玲君, 李晓明. 基于聚类改进S变换与直接支持向量机的电能质量扰动识别[J]. 电力自动化设备, 2015, 35(7): 50-58, 73. Xu Zhichao, Yang Lingjun, Li Xiaoming. Power quality disturbance identification based on clustering- modified S-transform and direct support vector machine[J]. Electric Power Automation Equipment, 2015, 35(7): 50-58, 73. [11] 黄飞腾, 翁国庆, 王强. 带分布式电源的配电网电能质量扰动源定位[J]. 电力系统自动化, 2015, 39(9): 150-155. Huang Feiteng, Weng Guoqing, Wang Qiang. Location of power quality disturbance source on distribution network with distributed generation[J]. Automation of Electric Power Systems, 2015, 39(9): 150-155. [12] Ganguly S. Multi-objective planning for reactive power compensation of radial distribution networks with unified power quality conditioner allocation using particle swarm optimization[J]. IEEE Transa- ctions on Power System, 2014, 29(4): 1801-1810. [13] 王曦, 李兴源, 赵睿. 基于相对增益和改进粒子群算法的PSS与直流调制协调策略[J]. 中国电机工程学报, 2014, 34(34): 6177-6184. Wang Xi, Li Xingyuan, Zhao Rui. Coordination strategy of PSS and DCM based on relative gain and improved PSO[J]. Proceedings of the CSEE, 2014, 34(34): 6177-6184. [14] Shen M, Zhan Z, Chen W, et al. Bi-velocity discrete particle swarm optimization and its application to multicast routing problem in communication net- works[J]. IEEE Transactions on Industrial Electronics, 2014, 61(12): 7141-7151. [15] Ibrahim A A, Mohamed A, Shareef H, et al. A new approach for optimal power quality monitor place- ment in power system considering system topology[J]. Przeglad Elektrotechniczny, 2012, 88(9a): 272-276. [16] IEEE PES distribution system analysis sub- committee's distribution test feeder working group[OL]. http://ewh.ieee.org/soc/pes/dsacom/testfeeders/index. html.
2017, Vol. 32 
