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Comparative Study between Genetic Algorithms and Iterative Optimization for Economic Dispatch of Practical Power System
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DOI: https://doi.org/10.15866/iree.v13i2.13870
Abstract
This paper presents a genetic approach for solving the economic dispatch problem in power systems. The cost functions are newly and precisely developed for some power plants operating currently in Jordan using curve fitting. The developed cost models are introduced to a modern genetic algorithm tool for the purpose of generation scheduling. The feasibility of the proposed method is demonstrated and compared with the lambda iterative method in terms of the solution quality and computation efficiency. MATLAB software scripts in cooperative manner with graphical user interface (GUI) is used for the proposed methods. Different models of cost curve fitting of the thermal units are considered. The study is done initially for a three power plants and then it has been extended for four plants. The simulation results show that the proposed GA method was capable of obtaining accurate solutions in ED problems. It is finally deduced that the approach can be promising proposal for improvement of economy in energy sector in Jordan by fuel cost minimization with demand satisfaction and generation constraints.
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References
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