Optimal step-function approximation of load duration curve using evolutionary programming (EP) / Eda Azuin Othman

This paper proposes Evolutionary Programming (EP) to determine optimal step-function approximation of load duration curve (LDC) at minimum error. The EP model optimally discretized a load duration curve based on Malaysia's hourly load data in year 2012 for three and six segments of discretized...

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Bibliographic Details
Main Author: Othman, Eda Azuin (Author)
Format: Book
Published: UiTM Press, 2014-06.
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100 1 0 |a Othman, Eda Azuin  |e author 
245 0 0 |a Optimal step-function approximation of load duration curve using evolutionary programming (EP) / Eda Azuin Othman 
260 |b UiTM Press,   |c 2014-06. 
500 |a https://ir.uitm.edu.my/id/eprint/62966/1/62966.pdf 
520 |a This paper proposes Evolutionary Programming (EP) to determine optimal step-function approximation of load duration curve (LDC) at minimum error. The EP model optimally discretized a load duration curve based on Malaysia's hourly load data in year 2012 for three and six segments of discretized LDC. The EP is developed using MatLab programming software. Results show that EP technique is able to provide optimum break points of discretized LDC at minimum error. In the analysis, it shows that the 6-step functions of LDC has a lower total error than the 3-step functions of LDC. The EP technique proposed in this paper is also compared with Dynamic Programming (DP) technique. Results show that EP provides a much shorter elapsed time than DP and have a lower total error for 3-step function of LDC. This EP-based model step function approximation of LDC is very useful for the power system planner to develop accurate generation expansion planning. 
546 |a en 
690 |a Evolutionary programming (Computer science). Genetic algorithms 
655 7 |a Article  |2 local 
655 7 |a PeerReviewed  |2 local 
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