Non convex economic load dispatch problem by Efficient Biogeography Based Optimization algorithm

In this paper a new Efficient Biogeography Based Optimization (EBBO) algorithm is discussed and it is applied to solve the non convex Economic Load Dispatch (ELD) problem for the minimization of fuel cost. This EBBO uses the concept of Particle Swarm Optimization (PSO), mutation of Differential Evolution (DE) and migration of Biogeography Based Optimization (BBO). The conventional PSO is improved by using the mutation operators of DE and migration of BBO. Thus, the EBBO method gives a global optimal solution to the ELD problem and it also improves the computational time in comparison to other optimization methods. The combined methodology is applied to test the performance of the test system consisting of 40 thermal units. Fuel cost function takes into account the valve-point loading effects. The simulation result shows that this method has the capability to generate the best solution with better convergence speed.