Improved particle swarm optimisation for multi-objective optimal power flow considering the cost, loss, emission and voltage stability index


The study presents an improved particle swarm optimisation (IPSO) method for the multi-objective optimal power flow (OPF) drawback. The proposed multi-objective OPF considers the cost, loss, voltage stability and emission impacts as the objective functions. A fuzzy call-based mechanism is used to pick the simplest compromise resolution of Pareto set obtained by the proposed algorithm. Furthermore, to improve the standard of the solution, particularly to avoid being trapped in native optima, this study presents an IPSO that profits from chaos queues and self-adaptive ideas to regulate the particle swarm optimisation (PSO) parameters. Additionally, a brand new mutation is applied to increase the search ability of the proposed algorithm. The thirty-bus IEEE test system is presented to Illustrate the appliance of the proposed drawback. The obtained results are compared with those in the literatures and the prevalence of the proposed approach over other methods is demonstrated.

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