Multi-objective economic emission load dispatch using teacher-learning- based optimization technique

Abstract

In this paper, a new parameter-less diversity preservation approach to solve the non-linear multi-objective economic emission load dispatch (EED) problem is envisaged using Teacher-Learning Based Optimization (TLBO) method. The TLBO technique is totally parameter less and takes less computation time as compared to other optimization techniques for the determination of solutions in the Pareto-optimal front. The TLBO method is tested for EED problem on 6-generator test system (IEEE 30- bus) and the results obtained are compared with those obtained from Non-dominated Sorting Genetic Algorithm (NSGA). The simulation results confirm the computational advantage of the TLBO method.