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This paper discusses about ELD Problem is modelled by non-convex constrained based cost function. This paper discusses the noncovex cost function based ELD problem. Actually, these problems are not solvable using a convex optimization techniques. Normally convex-conventional techniques are not solvable to ELD problems. So there is a need for using a meta-heuristic optimization methods. So in order to solve the non-convex cost function problems, a new meta-heuristic optimization techniques are required. Out of all optimization techniques, Oppositional Teaching and Learning Based Optimization (OTLBO) is introduced to solve the ELD problems and which will give better promising results. In this paper, OTLBO algorithm is used to solve the load dispatch problems economically. to solutions economically with valve point loading effect. In this paper, Oppositional Teaching and Learning Based Optimization (OTLBO) compares with other standard standard algorithms like TLBO and lambda iteration method. The OTLBO feasibility and effectiveness is demonstrated on 6, 10, and 14 units test systems along with the other optimization algorithms. The Comparison results enhance the global best solution for economic load dispatch solutions.

OPPOSITIONAL TLBO ALGORITHM FOR OPTIMUM GENERATING SCHEDULING OF POWER SYSTEM NETWORK WITH VALVE POINT LOADING EFFECT