This study presents a multi-objective based on a hybrid methodology to apply the problem of economic emission dispatch that is incorporated with hydro, thermal and wind power units. The hybrid method is the combinatio...
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This study presents a multi-objective based on a hybrid methodology to apply the problem of economic emission dispatch that is incorporated with hydro, thermal and wind power units. The hybrid method is the combination of both the modified quantum-behaviour lightning search algorithm (MQLSA) and artificial intelligence technique with the help of PSNN. To determine the optimal amounts of the generated powers from the thermal, wind farms and hydro units, the proposed approach is introduced by minimising the cost of generation and the emission level simultaneously. MQLSA is utilised to generate the optimal combination of thermal power with the objective of the minimum error function to minimise the fuel and emission cost of the system with wind speed factor. To capture the optimised wind power with the objective of minimum speed factor, the PSO-artificial neural network technique is utilised. The algorithm is integrated with the feasible solution constraint handling techniques. To validate the effectiveness of the proposed method, the six and ten generating thermal system with wind power is studied. The proposed hybrid technique is implemented in MATLAB/Simulink platform and the simulation result demonstrates the superiority of the proposed method compared to the various existing techniques.
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