Abstract
This paper presents the development and comparative application of recently developed evolutionary-based Memetic Algorithm (MA) along with its variants/hybrid methods for solving single objective Optimal Power Flow (OPF) problem. Two different variants based on single and double local search MA methods are implemented to solve single objective OPF problem. The MA algorithm is also hybridized with Differential Evolution (DE) to solve the OPF problem. The simulation studies are carried out on a standard IEEE 30-bus test system to demonstrate the effectiveness of the developed methods. The simulation results are compared with the existing methods available in the literature. The performance of the best variant/hybrid method is also tested for solution of single objective OPF problem by considering load uncertainty.
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