Modified Teaching-Learning-Based Optimization for Combined Heat and Power Economic Dispatch

Abstract

AbstractThis paper develops and suggests modified teaching-learning-based optimization to solve non-smooth non-convex combined heat and power economic dispatch (CHPED) problem. The valve-point loading and forbidden working regions of conventional thermal generator are taken into account. Modified teaching–learning-based optimization (MTLBO) introduces Gaussian random variables in the ‘Teacher phase’ and ‘Learner phase’ which perks up search efficiency and assurances a high probability of acquiring the global optimum without considerably impairing the convergence speed and the simplicity of the structure of teaching-learning-based optimization (TLBO). The efficacy of the suggested MTLBO technique has been confirmed on three test systems and 15 benchmark functions. Test results of the suggested technique have been matched up to those achieved by other evolutionary techniques. It has been observed from the comparison that the suggested MTLBO technique has the ability to endow with superior solution.