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Optimal meter placement algorithm for state estimation in power distribution networks

机译：配电网状态估计的最佳电表放置算法

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This paper proposes an algorithm to allocate meters in distribution networks to increase the accuracy of the state estimation. This algorithm considers three new issues in the meter placement problem: correlated measurements, multiple load levels and accuracy evaluation of state estimation without using Monte Carlo Simulation (MCS), that is, based on analytical approach. The objective function used in the meters placement problem is associated with the maximization of the accuracy of the state estimator. This objective function is optimized considering constraints for the maximum number of meters that can be installed and for the accuracy of the state estimator. The optimization problem is solved with the binary particle swarm algorithm. The tests results indicated that the meter placement obtained with the proposed algorithm is very accurate for all levels of the load curve. For example, it has been shown that the accuracy of state estimation is four times better when the correlation in power measurements is included in the model. In addition, the computational cost of estimating the accuracy of the state estimate based on the proposed analytical approach is about 47 times lower than that associated with MCS. (C) 2017 Elsevier B.V. All rights reserved.
机译：本文提出了一种在配电网中分配电表的算法，以提高状态估计的准确性。该算法考虑了电表放置问题中的三个新问题：相关的测量，多个负载水平以及不使用蒙特卡罗模拟（MCS）即基于分析方法的状态估计的准确性评估。电表放置问题中使用的目标函数与状态估计器精度的最大化相关。考虑到最大可安装仪表的限制和状态估计器的精度，对该目标函数进行了优化。用二进制粒子群算法解决了优化问题。测试结果表明，使用该算法获得的电表位置对于所有负载曲线水平都非常准确。例如，已经表明，当模型中包含功率测量的相关性时，状态估计的精度将提高四倍。另外，基于所提出的分析方法估计状态估计的准确性的计算成本比与MCS关联的计算成本低约47倍。 （C）2017 Elsevier B.V.保留所有权利。

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