Lambda Iteration and Genetic Algorithms Application to solve the Economic Load Dispatch Problem of Seven Nigerian Thermal Power Plants

Agber, Jonathan Uhaa, Anzaku Engla

Abstract


Economic load dispatch (ELD) is a method of earmarking the required load demand between the existing generations in power system and principally determining allocation of generators to each generation for various systems load levels. ELD is an essential component in power system planning and operation. ELD solutions are found by solving the conventional load flow equations, while at the same time ensuring that fuel costs are minimized. There are many methods developed for solving ELD problems, but this work is restricted to two, which are the Lambda Iteration Method (LIM) and the Genetic Algorithm (GA) modified with sorting algorithm. The main objective is to apply the two methods to solve ELD problems in power system networks by comparing the performance of GA method with that of LIM in terms of fuel cost efficiency. The usefulness of LIM and GA to solving economic dispatch problem is emphasized. Simulation results obtained on this network using GA and LIM verify their effectiveness in solving ELD problems. Lastly, GA and LIM approaches have been effectively applied to the harmonization of the Nigerian 32-bus system powered by seven thermal and three hydro generating units. The study shows that GA exhibits better results than LIM from both best possible generation allocations. The results obtained demonstrate that GA based method gave better solution in terms of fuel cost reduction, when compared with those obtained using LIM. By blending the probabilities of crossover and mutation, and the application of sorting techniques, computer usage time can be significantly reduced in the system with better fuel cost reduction.

Keywords: Economic load dispatch (ELD), genetic algorithm (GA), lambda iteration method (LIM), optimization, sorting algorithm.

DOI: 10.7176/JETP/11-4-04

Publication date: August  31st 2021


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ISSN (Paper)2224-3232 ISSN (Online)2225-0573

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