Multi‐objective hybrid estimation of distribution algorithm‐interior point method‐based meter placement for active distribution state estimation

Abstract

This study proposes a new multi-objective hybrid estimation of distribution algorithm (EDA)-interior point method (IPM) algorithm to obtain the optimal location of measuring devices for state estimation (SE) in active distribution networks. The objective functions to be minimised are, the total network configuration cost, the average relative percentage error of bus voltage magnitude and angle estimates. As the objectives are conflicting in nature, a multi-objective Pareto-based non-dominated sorting EDA has been proposed in this study. Moreover, due to poor exploitation capability of the EDA, it is hybridised with IPM to improve its local searching ability in the search space. The hybridisation of EDA and IPM brings a higher degree of balance between the exploration and exploitation capability of the algorithm during the search process. Furthermore, the loads and generators are treated as stochastic variable and the impact of different type of distributed generations on SE performance has also been investigated. The efficiency of the proposed algorithm is tested on PG&E 69-bus system and Indian 85-bus radial distribution network. The obtained results are compared with conventional EDA, particle swarm optimisation, non-dominated sorting genetic algorithm and also with existing techniques in the literature such as dynamic programming and ordinal optimisation algorithm.