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Optimal Micro-PMU Placement Using Mutual Information Theory in Distribution Networks

机译:在配送网络中使用互信息理论的最佳微量PMU放置

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摘要

Micro-phasor measurement unit (μPMU) is under fast development and becoming more and more important for application in future distribution networks. It is unrealistic and unaffordable to place all buses with μPMUs because of the high costs, leading to the necessity of determining optimal placement with minimal numbers of μPMUs in the distribution system. An optimal μPMU placement (OPP) based on the information entropy evaluation and node selection strategy (IENS) using greedy algorithm is presented in this paper. The uncertainties of distributed generations (DGs) and pseudo measurements are taken into consideration, and the two-point estimation method (2PEM) is utilized for solving stochastic state estimation problems. The set of buses selected by improved IENS, which can minimize the uncertainties of network and obtain system observability is considered as the optimal deployment of μPMUs. The proposed method utilizes the measurements of smart meters and pseudo measurements of load powers in the distribution systems to reduce the number of μPMUs and enhance the observability of the network. The results of the simulations prove the effectiveness of the proposed algorithm with the comparison of traditional topological methods for the OPP problem. The improved IENS method can obtain the optimal complete and incomplete μPMU placement in the distribution systems.
机译:微相量测量单元(μPMU)正在快速发展,并成为未来分销网络的应用越来越重要。这是不现实的,也是负担不起的地方,因为成本高与μPMUs所有公交车,导致确定与配电系统中μPMUs的最小的数字优化配置的必要性。基于使用贪婪算法的信息熵评估和节点选择策略(IENS)的最佳μPMU放置(OPP)呈现于本文。分布式发电(分布式电源)和伪测量值的不确定性考虑,并且这两个点估计方法(2PEM)被用于求解随机状态估计问题。该组由改进IENS选定公共汽车,这可以最小化网络的不确定性,将获得系统可观测被认为是μPMUs的优化配置。该方法利用了智能电表,并在配电系统负载功率伪测量的测量以减少μPMUs的数量,增强网络的可观测。模拟的结果证明了该算法为OPP问题的传统拓扑方法比较的有效性。的改进的方法IENS可以获得在分发系统的最佳完全和不完全μPMU放置。

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