Application of Multi-Objective Teaching-Learning-BasedAlgorithm to an Economic Load Dispatch Problem withIncommensurable Objectives

摘要

In this paper, a multiobjective teaching-learning-based optimization algorithm with non-domination based sorting is applied to solve the environ-mental/economic dispatch (EED) problem containing the incommensurable ob-jectives of best economic dispatch and least emission dispatch. The address of the environmental concerns that arise in the present day due to the operation of fossil fuel fired electric generators and global warming requires the transforma-tion of the classical single objective economic load dispatch problem into mul-tiobjective environmental/economic dispatch problem. In the work presented a test system of forty units is taken with fuel cost and emission as two conflicting objectives to be optimized simultaneously. The mathematical model used con-siders practical upper and lower bounds applicable to the generators. The valve point loading of the generator is mimicked in the modeling to accommodate a more realistic system. The simulation result reveals that the proposed approach is a competitive one to the current existing methods for finding the best optimal pareto front of two conflicting objectives and has the better robustness.