TOPSIS Aided Multiobjective Artificial Vulture Optimization Algorithm to Solve Combined Power and Economic Emission Dispatch

This study presents the implementation of a powerful multiobjective artificial vulture optimization algorithm to address the complex combined economic emission dispatch and combined electricity and heat economic emission dispatch challenges. The aim is to optimize the operation of cogeneration plants in the power system economically while minimizing the environmental effects related to thermal power plants. On a 30-bus power system, the algorithm's performance is assessed while taking into account transmission power losses, feasible operating zone, ramp restrictions, and the valve-point effects. The most feasible Pareto optimum solution is determined using an a posteriori multiobjective optimization framework and the technique of order of preference by resemblance to the ideal solution approach. Three distinct cases are examined, each with the goal of fulfilling the unique demands of various industries. This is accomplished by adjusting the weight given to the criterion. The MOAVOA algorithm showcases superior performance with a remarkable reduction in emission and fuel costs, which are 0.0467 tons per hour and 106.064 dollars per hour, respectively.