Modified Bacterial Foraging Algorithm Applied to Economic Dispatch Problem and Comparison with other Solutions

This paper presents a newly developed optimization approach involving a modified bacterial foraging algorithm (MBFA) applied for the solution of the Economic Dispatch (ED) problem with generator constraints and transmission losses with conventional smooth, nonsmooth cost function with valve point effect. The application of numerical methods and heuristic methods for solving ED problem is presented. The numerical algorithm involves the selection of minimum and maximum incremental fuel costs (lambda values) and then the evaluation of optimal lambda is done by root finding techniques at required power demand. These algorithms have been tested on several systems with various generating units. Simulation results were compared in terms of solution quality, convergence characteristics and computation efficiency with conventional methods such as lambda iterative method, heuristic methods such as genetic algorithm and meta-heuristic methods such as modified bacterial foraging algorithm and MPSO. For further comparison ED problem has been implemented with Matlab optimization toolbox and power system toolbox

Keywords:

Economic Dispatch (ED) , Nonsmooth Optimization , modified Bacterial Foraging Algorithm (MBFA) , Root Finding Techniques , Modified Particle Swarm Optimization (MPSO) , Genetic Algorithm (GA