Solution of nonconvex and nonsmooth economic dispatch by a new Adaptive Real Coded Genetic Algorithm

This paper proposes a novel Adaptive Real Coded Genetic Algorithm (ARCGA) to solve the nonconvex and nonsmooth economic dispatch (ED) problem considering valve loading effects and multiple fuel source options. Considering valve effects and multiple fuel options change ED into nonlinear, nonconvex and nonsmooth optimization problem with multiple minima. These characteristics challenge analytical and heuristic methods in finding optimal solution in reasonable time. The proposed ARCGA technique is composed of new genetic operators including arithmetic-average-bound crossover (AABX) and B-Spline wavelet mutation (BWM). Moreover, to enhance the computational efficiency of the suggested solution method, an adaptation process is also included in the ARCGA. To show the superiority of the ARCGA, it is compared with several most recently published methods proposed to solve the ED problem.