Today’s Economic Dispatch (ED) solutions are featured with environmental obligations. Hence, the significant objective functions contribute to cost minimization, lower emission and less total system losses. As an alternative, New Meta Heuristic Evolutionary Programming (NMEP) technique was proposed to optimize the individual ED problem categorized as Single Objective Environmental Economic Dispatch (SOEELD), developed from an integration of original Meta Heuristic Evolutionary Programming (Meta-EP) with Artificial Immune System (AIS) with new arrangement in the mutation and cloning processes. The comparative analysis was conducted between the original Meta-EP and classical method of Hadi Saadat to verify the performance of NMEP method. Each particular objective function identified the best possible outcomes through the NMEP method. The simulations were conducted using MATLAB programming which tested both standard IEEE 26 and 57 bus systems.

The increment of Economic Dispatch (ED) problem is very distressing today. In view of countless of the researchers doing the research to minimize the ED problem day after day, the multi objective New Meta Heuristic Evolutionary Programming (NMEP) techniques are proposed to optimize the multi objective function in ED problem called as Multi Objective Environmental Economic Dispatch (MOEED). The techniques mimic the original Meta Heuristic Evolutionary Programming (Meta-EP) and merge with Artificial Immune System (AIS) with some improvement in Gaussian mutation process and cloning process. The NMEP produced two objective function result simultaneously by exercising the weighted sum method. In order to justify the result, the comparison between the NMEP and Meta-EP techniques is conducted with difference case number of alpha. Therefore, the outcome of the simulation shows the NMEP approach is better than Meta-EP in the both case numbers of alpha. The simulation is operated using MATLAB simulation based on standard IEEE 26 bus system in the laboratory.

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