Evolutionary approach for solving economic dispatch in power system
B. Norasiqin, S. Rahimullah, Effirul Ikhwan Ramlan, Titik Khawa Abdul Rahman
Abstract
B. Norasiqin, S. Rahimullah, Effirul Ikhwan Ramlan, Titik Khawa Abdul Rahman
Abstract
The problem or economic dispatch has been forwarded and solved by numerous methods. This paper provides alternative methods to solve the problem. In this paper, evolutionary programming (EP) is used as one of the techniques to solve the problem of economic dispatch in power system. Log-normal Gaussian mutation or commonly known as metaEP, is used as the essential operator of generating the sufficient power in order to fulfill demand at a minimum cost. The proposed EP method provides a solution consisting suitable power generated of each generator and meeting the demand with minimum total cost. The study also investigates the differences of using standard EP against metaEP to solve the same problem. The comparisons between the both methods and GA solution to solve the problems are also highlighted in this paper. The study findings show that both EP methods perform better compared to GA in solving the economic dispatch problem. However, metaEP seems to be more robust in solving problems in a bigger search space compared to the original EP. The study conducted for the comparison is based on the solution and performance of each algorithm in solving the problem.
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The problem or economic dispatch has been forwarded and solved by numerous methods. This paper provides alternative methods to solve the problem. In this paper, evolutionary programming (EP) is used as one of the techniques to solve the problem of economic dispatch in power system. Log-normal Gaussian mutation or commonly known as metaEP, is used as the essential operator of generating the sufficient power in order to fulfill demand at a minimum cost. The proposed EP method provides a solution consisting suitable power generated of each generator and meeting the demand with minimum total cost. The study also investigates the differences of using standard EP against metaEP to solve the same problem. The comparisons between the both methods and GA solution to solve the problems are also highlighted in this paper. The study findings show that both EP methods perform better compared to GA in solving the economic dispatch problem. However, metaEP seems to be more robust in solving problems in a bigger search space compared to the original EP. The study conducted for the comparison is based on the solution and performance of each algorithm in solving the problem.
Key concepts: Economic dispatch, Mathematical optimization, Computer science, Evolutionary algorithm, Evolutionary programming, Genetic algorithm, Electric power system, Operator (biology)