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Application of Multi-Objective Evolutionary Optimization Algorithms to Reactive Power Planning Problem

Abstract

This paper presents a new approach to treat reactive power (VAr) planning problem using multi-objective evolutionary algorithms. Specifically, Strength Pareto Evolutionary Algorithm (SPEA) and Multi-Objective Particle Swarm Optimization (MOPSO) approaches have been developed and successfully applied. The overall problem is formulated as a nonlinear constrained multi-objective optimization problem. Minimizing the total incurred cost and maximizing the amount of Available Transfer Capability (ATC) are defined as the main objective functions. The proposed approaches have been successfully tested on IEEE 14 bus system. As a result a wide set of optimal solutions known as Pareto set is obtained and encouraging results show the superiority of the proposed approaches and confirm their potential to solve such a large scale multi-objective optimization problem

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