Constrained Laplacian Biogeography-Based Optimization for Economic Load Dispatch Problems

Increasing price and lack of availability of fuels are the reason for the economic use of power. Economic load dispatch (ELD) problem is widely studied problem in electrical engineering, wherein the optimal output of units of generators is to be determined so on meet the specified load demand with minimal cost of fuel and emission. The complexity of the problem occurs due to various limitations. In this paper, four models of ELD problems based on different objective functions and constraints are considered. These four test problems are solved using a new variant of nature-inspired optimization technique, namely, Laplacian biogeography-based optimization algorithm. Optimal results obtained by this algorithm are then compared with its other counterparts like sine cosine algorithm, grey wolf optimization, and particle swarm optimization. While comparing with the previous results recorded, constrained LX-BBO proves its superiority over other traditional and nature-inspired optimization techniques. Due to the simplicity of LX-BBO and fewer parameters to control, it is easier to apply for real-life problems. The statistical tests are incorporated to strengthen the claim. Further algorithm complexity of the proposed algorithm is also tested.