Social welfare maximization for congestion management in multiutility market using improved PSO incorporating transmission loss cost allocation

Abstract

The objective of the present work is to investigate a decentralized optimal power flow decision-based congestion-free operational strategy in multiutility power markets that maximizes the social welfare. The effects of network losses incurred by various utilities on social welfare of the market have also been investigated. As a result, it can resolve the market disputes due to the problem of congestion and allocation of the additional cost of generation caused by transmission losses. The centralized optimal power flow decision-based strategy has also been adopted to address the problem. In this work, a new optimization method, interior point–initialized particle swarm optimization (IP-PSO) method, has been introduced to solve the mentioned problem. The method harnesses the benefits of both interior point method (IPM) and particle swarm optimization (PSO) method. To facilitate the faster optimal solution, results obtained using IPM has been used to initialize PSO solution. The proposed study has been performed on the modified IEEE-30 bus and modified IEEE-118 bus systems. The results show the effectiveness of decentralized optimal power flow decision-based strategy over centralized optimal power flow decision-based strategy using IPM, sequential quadratic programming, PSO, IP-initialized sequential quadratic programming, and IP-PSO methods. Copyright © 2018 John Wiley & Sons, Ltd.