Open AccessMeasurement devices allocation in distribution system using state estimation: A multi‐objective approach
Author(s) -
Hassannejad Marzouni Alireza,
Zakariazadeh Alireza,
Siano Pierluigi
Publication year - 2020
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/2050-7038.12469
Subject(s) - particle swarm optimization , robustness (evolution) , monte carlo method , computer science , mathematical optimization , electric power system , power (physics) , algorithm , mathematics , biochemistry , chemistry , statistics , physics , quantum mechanics , gene
Summary 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.