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An Efficient Simulated Annealing Algorithm for Economic Load Dispatch Problems

An Efficient Simulated Annealing Algorithm for Economic Load Dispatch Problems

Journal from gdlhub / 2016-11-07 06:40:15
By : Hardiansyah Hardiansyah, Junaidi Junaidi, Yohannes MS Yohannes MS, Telkomnika
Created : 2013-03-01, with 1 files

Keyword : economic load dispatch, simulated annealing, quadratic programming, genetic algorithm, efficient, gobal optimization
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/880

Makalah ini menyajikan suatu algoritma simulated annealing (SA) yang efisien untuk penyelesaian masalah economic load dispatch (ELD) pada sistem tenaga listrik. Filosofi melibatkan pengenalan variabel keputusan baru melalui transformasi matematika secara bijaksana hubungan antara variabel keputusan dan pembangkitan optimal. Tujuan dari masalah ELD dalam pembangkit tenaga listrik adalah pemrograman khusus keluaran unit pembangkit sehingga dapat memenuhi kebutuhan beban dengan jumlah biaya operasional terendah yang memenuhi semua unit dan kendala persamaan dan pertidaksamaan sistem. Pendekatan optimisasi global terinspirasi oleh proses pendinginan termodinamika. Algoritma SA yang diusulkan disini diterapkan pada dua studi kasus, yang menganalisis sistem tenaga yang memiliki tiga dan enam unit pembangkit. Hasil yang diperoleh dengan pendekatan yang diusulkan dibandingkan dengan pemrograman kuadratik konvensional (QP) dan algoritma genetika (GA).

Description Alternative :

This paper presents an efficient simulated annealing (SA) algorithm with a single decision variable to solve the economic load dispatch (ELD) problems. The philosophy involves the introduction of a new decision variable through a prudent mathematical transformation of the relation between the decision variable and the optimal generations. The objectives of ELD problems in electric power generation is to programmed the devoted generating unit outputs so as to meet the mandatory load demand at lowest amount operating cost while satisfying all units and system equality and inequality constr aints. Global optimization approaches is inspired by annealing process of thermodynamics. The proposed SA algorithm presented here is applied to two case studies, which analyze power systems having three, and six generating units. The results determined by the proposed approach are compared to those found by conventional quadratic programming (QP) and genetic algorithm (GA).

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