Generation expansion optimal planning using composite particle swarm optimization algorithm

The generation expansion planning is a complex, mixed integer and nonlinear programming problem. This paper presents an improved composite particle swarm optimization(CPSO) approach developed to solve the of an all-thermal power system. The problem is focused on the optimal mix of generation units in a given target year with the constrained consideration of certain thermal units committed during peaking periods. The problem formulation thus requires considering the technical limits of the thermal unit outputs due to the large difference between the daily peak-load and valley-load demands. Results from a practical case study show that the methodology is feasible and efficient in solving such mixed integer, constrained nonlinear generation expansion problem. Compared with the existing optimal planning method, the search time of the C-PSO method is shorter and the result is close to the ideal solution, simultaneously.