Abstract The present work proposes a multiobjective approach for optimal allocation of metering devices in Electrical Distribution Systems. The proposed approach seeks to obtain solutions that represent attractive investment options for utilities, while providing good performance for State Estimation (SE) when processing measurements from the allocated meters. The requirements of low investment costs and good SE performance are conflicting ones. In this paper, the Pareto multiobjective method, associated with the Modified Monkey Search (MMS) metaheuristic, is employed to obtain concurrent candidate solutions for optimal allocation of smart meters and phasor measurement units. The proposed method, called MMS-Pareto, is employed along with an efficient tool for SE in distribution networks, known as Enhanced Optimal Power Flow. The proposed method is assessed using benchmark systems of the literature, as well as a real Brazilian utility network, being adopted practical and updated costs for the meter devices. Comparisons with a weighted mono-objective approach are presented and the obtained results show that the MMS-Pareto can lead to good trade-off solutions, useful for system planners. Moreover, comparisons with the results obtained when employing other metaheuristics are presented.

中文翻译：

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在配电系统中放置仪表的成本效益多目标方法

摘要 目前的工作提出了一种用于配电系统中计量设备优化配置的多目标方法。提议的方法寻求获得代表公用事业有吸引力的投资选择的解决方案，同时在处理来自分配的仪表的测量时为状态估计 (SE) 提供良好的性能。低投资成本和良好 SE 性能的要求是相互矛盾的。在本文中，帕累托多目标方法与修正猴子搜索 (MMS) 元启发式相关联，用于获得智能电表和相量测量单元优化分配的并发候选解决方案。所提出的方法称为 MMS-Pareto，与配电网络中 SE 的有效工具（称为增强型最优潮流）一起使用。所提出的方法是使用文献的基准系统以及真实的巴西公用事业网络进行评估的，该网络正在为仪表设备采用实用和更新的成本。提出了与加权单目标方法的比较，所得结果表明 MMS-Pareto 可以产生良好的权衡解决方案，对系统规划人员有用。此外，还提供了与采用其他元启发式方法时获得的结果的比较。