Optimal allocation of measurement devices is a necessity in order to carry out state estimation of a distribution system. In this paper, the placement problem of power measurement devices is modeled using a multi‐objective method. The objectives of the problem are to minimize measurement devices' costs while increasing the accuracy of state estimation and improving the state estimation quality. Also, operational priorities are considered as another objective, which are based on power losses, lines' capacities, the number of lines connected to a specific line, and the change in lines' flows direction. A multi‐objective evolutionary algorithm based on decomposition (MOEA/D) is used to optimize the allocation of measurement devices within the problem of distribution system state estimation. The state estimation problem is optimized by particle swarm optimization (PSO) algorithm and the Monte Carlo simulation is used to develop some conditions within the network to guarantee the robustness of the proposed method. The method is tested by simulation results on an IEEE 33‐bus and IEEE 123‐bus radial network.

中文翻译：

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使用状态估计的配电系统中的测量设备分配：多目标方法

为了进行配电系统的状态估计，必须对测量设备进行最佳分配。在本文中，使用多目标方法对功率测量设备的放置问题进行了建模。该问题的目的是使测量设备的成本最小化，同时增加状态估计的准确性并提高状态估计的质量。同样，根据功率损耗，线路容量，连接到特定线路的线路数量以及线路流向的变化，将操作优先级视为另一个目标。在配电系统状态估计问题中，基于分解的多目标进化算法（MOEA / D）用于优化测量设备的分配。通过粒子群算法（PSO）对状态估计问题进行了优化，并通过蒙特卡罗模拟在网络中建立了一定的条件，以保证所提方法的鲁棒性。通过在IEEE 33总线和IEEE 123总线径向网络上的仿真结果测试了该方法。