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: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/5868/1/fkee-2014-hong-comparative_study.pdf http://umpir.ump.edu.my/id/eprint/5868/ |
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| Summary: | 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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