A New Meta Heuristic Evolutionary Programming (NMEP) in Optimizing Economic Energy Dispatch

Abstract

Economic and efficient energy dispatch management is compulsory to address the growth in energy demand within a limited energy resources whereas maintaining the secure power system operation. Many researches were conducted to study and develop new tools to overcome the problems during Economic Dispatch (ED) implementation. Mainly, ED problems considered on the total cost minimization at the same time the obligation of social attentions have inclined in reducing the energy conservation and pollution emission produced by power plants. As a result, a new algorithm was developed not only in minimizing the total generation cost but with an addition on minimum total emission and less system losses as the individual objective function in ED. The proposed optimization algorithm, namely New Meta-Heuristic Evolutionary Programming (NMEP) algorithm is followed to Meta-Heuristic Evolutionary Programming (Meta-EP) approach with some modification where the cloning process embedded as a significant progress during the implementation. This approach is utilized specifically to solve the single objective function which considered as minimum total generation cost, less sum of polluted emission and also a reduced amount in power system losses. The comparison evaluation between the original Meta-EP is conducted in order to show the effectiveness of the identified NMEP to overcome the ED issues. As a result, the best answer of the corresponding individual objective functions produced through NMEP approach. The simulation is tested on standard IEEE 26 bus system using the MATLAB software programming.