Comparative Study of Economic Dispatch by Using Various Optimization Techniques

This paper presents various optimization techniques to solve the problem of Economic Dispatch (ED). The optimization techniques used in this paper to do the comparison are Quadratic Programming (QP), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Differenti...

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Main Authors: Hong, Mee Song, M. H., Sulaiman, Mohd Rusllim, Mohamed, Wong, Lo Ing
Format: Conference or Workshop Item
Language:English
Published: 2014
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/5868/1/fkee-2014-hong-comparative_study.pdf
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author Hong, Mee Song
M. H., Sulaiman
Mohd Rusllim, Mohamed
Wong, Lo Ing
author_facet Hong, Mee Song
M. H., Sulaiman
Mohd Rusllim, Mohamed
Wong, Lo Ing
author_sort Hong, Mee Song
collection UMP
description This paper presents various optimization techniques to solve the problem of Economic Dispatch (ED). The optimization techniques used in this paper to do the comparison are Quadratic Programming (QP), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Differential Evolution (DE) and Genetic Algorithm (GA). The objective of Economic Dispatch is to minimize the fuel cost at the same time to determine the optimum power generation. Optimization technique is used for ED so that the better convergence could be approached to solve the problem effectively as well as by considering the constraints. To do the comparison, the six generating unit system was used and the experimental results are compared. The experimental result indicates that the Differential Evolution is the most efficient technique compared to others in terms of fuel cost and total losses.
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spelling UMPir58682018-03-07T03:35:04Z http://umpir.ump.edu.my/id/eprint/5868/ Comparative Study of Economic Dispatch by Using Various Optimization Techniques Hong, Mee Song M. H., Sulaiman Mohd Rusllim, Mohamed Wong, Lo Ing TK Electrical engineering. Electronics Nuclear engineering This paper presents various optimization techniques to solve the problem of Economic Dispatch (ED). The optimization techniques used in this paper to do the comparison are Quadratic Programming (QP), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Differential Evolution (DE) and Genetic Algorithm (GA). The objective of Economic Dispatch is to minimize the fuel cost at the same time to determine the optimum power generation. Optimization technique is used for ED so that the better convergence could be approached to solve the problem effectively as well as by considering the constraints. To do the comparison, the six generating unit system was used and the experimental results are compared. The experimental result indicates that the Differential Evolution is the most efficient technique compared to others in terms of fuel cost and total losses. 2014 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/5868/1/fkee-2014-hong-comparative_study.pdf Hong, Mee Song and M. H., Sulaiman and Mohd Rusllim, Mohamed and Wong, Lo Ing (2014) Comparative Study of Economic Dispatch by Using Various Optimization Techniques. In: 2nd Power and Energy Conversion Symposium (PECS) 2014 , 12 May 2014 , UTeM Melaka. pp. 1-4.. (Unpublished)
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Hong, Mee Song
M. H., Sulaiman
Mohd Rusllim, Mohamed
Wong, Lo Ing
Comparative Study of Economic Dispatch by Using Various Optimization Techniques
title Comparative Study of Economic Dispatch by Using Various Optimization Techniques
title_full Comparative Study of Economic Dispatch by Using Various Optimization Techniques
title_fullStr Comparative Study of Economic Dispatch by Using Various Optimization Techniques
title_full_unstemmed Comparative Study of Economic Dispatch by Using Various Optimization Techniques
title_short Comparative Study of Economic Dispatch by Using Various Optimization Techniques
title_sort comparative study of economic dispatch by using various optimization techniques
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/5868/1/fkee-2014-hong-comparative_study.pdf
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