Modified particle swarm optimization for economic-emission load dispatch of power system operation
This paper proposes a modified particle swarm optimization considering time-varying acceleration coefficients for the economic-emission load dispatch (EELD) problem. The new adaptive parameter is introduced to update the particle movements through the modification of the velocity equation of the cla...
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| Main Authors: | , , , |
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| Format: | Article |
| Published: |
Scientific and technological Research Council Turkey (TUBITAK)
2015
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.3906/elk-1307-204 http://dx.doi.org/10.3906/elk-1307-204 http://eprints.uthm.edu.my/7689/1/mohd_noor_abdullah_U.pdf |
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| Summary: | This paper proposes a modified particle swarm optimization considering time-varying acceleration coefficients
for the economic-emission load dispatch (EELD) problem. The new adaptive parameter is introduced to update the
particle movements through the modification of the velocity equation of the classical particle swarm optimization (PSO)
algorithm. The idea is to enhance the performance and robustness of classical PSO. The price penalty factor method is
used to transform the multiobjective EELD problem into a single-objective problem. Then the weighted sum method is
applied for finding the Pareto front solution. The best compromise solution for this problem is determined based on the
fuzzy ranking approach. The IEEE 30-bus system has been used to validate the effectiveness of the proposed algorithm.
It was found that the proposed algorithm can provide better results in terms of best fuel cost, best emissions, convergence
characteristics, and robustness compared to the reported results using other optimization algorithms. |
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