Reactive Power Planning using Evolutionary Algorithms

This paper proposes an application of Evolutionary Algorithms (EAs) such as Differential Evolution (DE), Evolutionary Programming (EP), Real coded Genetic Algorithm (RGA), Covariance Matrix Adaptation Evolution Strategy (CMAES) and Particle Swarm Optimization (PSO) to Reactive Power Planning (RPP) problem. RPP is a non-smooth and non-differentiable optimization problem for a multiobjective function. Three loading conditions (Normal load, 1.25% and 1.5% of normal load) have been considered. The IEEE 30 bus system is used to validate the effectiveness of the Evolutionary Algorithms. Simulation results shows that, the DE algorithm gives better results compared to other algorithms for all the loading conditions and it can be better suited for the multi objective RPP problem.