Unit commitment by biogeography based optimization method

This paper proposes the application of biogeography-based optimization (BBO) to the unit commitment (UC) problem of power systems operation. Biogeography is the study of the geographical distribution of biological organisms. BBO has features in common with other biology-based optimization methods, such as genetic algorithms (GA) and particle swarm optimization (PSO). Hence BBO is applicable to many of the same types of problems that GA and PSO are used for. The proposed method has a simple procedure to find a near optimal solution for the non-smooth and non-convex problems mainly through two steps: migration and mutation. Unit commitment (UC) problem is mainly finding the minimum cost schedule to a set of generators by turning each one either on or off over a given time horizon to meet the demand load and satisfy different operational constraints. There are many constraints in unit commitment problem such as spinning reserve, minimum up/down, crew, must run and fuel constraints. BBO will be applied to solve the unit commitment problem and results will be compared with others heuristic methods presented in literatures.