Combination of Stochastic Methods for Solving ELD Problem of Thermal Power Generation System

Abstract

This chapter reports a hybrid optimization technique, a combination of stochastic methods – particle swarm optimization (PSO) and ant colony optimization (ACO), which is applied to find economic dispatch schedule and minimum generation cost for convex and non-convex power generation system simulated in MATLAB. A 40-generator system is considered here with combinations of valve point loading, ramp rate limit, and prohibited operating zone. The output is also noted when transmission loss is taken into consideration. The results are found better than those of many other hybrid methods. Considering the quality of the solution obtained and nature of convergence, PSO-ACO may be accepted as a good alternative for solving ELD problems of varying complexity. Though PSO has been extensively used in ELD problems for its flexibility, robustness, and fast convergence, it often produces suboptimal solution due to its premature convergence. ACO, on the other hand, known for its good global exploration feature, imparts better balance between local and global search when combined with PSO.