Solving complex economic load dispatch problems using biogeography-based optimization

This paper presents an algorithm, biogeography-based optimization (BBO) to solve both convex and non-convex economic load dispatch (ELD) problems of thermal generators of a power system. The Proposed methodology easily takes care of solving non-convex economic dispatch problems considering different constraints such as transmission losses, ramp rate limits, multi-fuel options and prohibited operating zones. Biogeography deals with the geographical distribution of biological organisms. Mathematical models of biogeography describe how species migrate from one habitat to another, how species arise, and how species become extinct. BBO has features in common with other biology-based optimization methods, like genetic algorithms (GAs) and particle swarm optimization (PSO). Here, first it will be discussed how BBO can be used to solve ELD problems. This algorithm searches the global optimum mainly through two steps: migration and mutation. To show the advantages of the proposed algorithm, it has been applied to four different test systems for solving ELD problems. First, a 6-generator system along with ramp rate limits and prohibited operating zone. Second, considers 40 generators with valve-point loading. Third, considers 20-generator systems with simple quadratic cost function considering transmission loss and operating limit constraints. Last one is addressing both valve-point effects and multiple fuels in a 10-generator system. Comparing with the other existing techniques, the current proposal is found better than, or at least comparable to them considering the quality of the solution obtained. This method is considered to be a promising alternative approach for solving the ELD problems in practical power system.