<p>This paper work present one of the latest meta heuristic optimization approaches named whale optimization algorithm as a new algorithm developed to solve the economic dispatch problem. The execution of the utilized algorithm is analyzed using standard test system of IEEE 30 bus system. The proposed algorithm delivered optimum or near optimum solutions. Fuel cost and emission costs are considered together to get better result for economic dispatch. The analysis shows good convergence property for WOA and provides better results in comparison with PSO. The achieved results in this study using the above-mentioned algorithm have been compared with obtained results using other intelligent methods such as particle swarm Optimization. The overall performance of this algorithm collates with early proven optimization methodology, Particle Swarm Optimization (PSO). The minimum cost for the generation of units is obtained for the standard bus system.</p>
This paper highlight the use of latest whale optimisation meta heuristic algorithm for solving economic dispatch problem efficiently. This is used to solve the combined economic and emission dispatch problems for standard three generators system and 30 bus IEEE system. The whale optimisation algorithm was found to provide optimum results with easy convergence in comparison with other algorithms like PSO algorithm. Fuel cost and emission costs are combined to derive better result for economic dispatch. For checking the effectiveness of the algorithm, the results obtained using the same are compared with the results of particle swarm optimisation (PSO) and analysed the same against minimum generation cost and easy convergence. The results are found to be excellent for the systems considered.
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