Optimal power flow solutions for power system operations using moth-flame optimization algorithm
This article proposes a recent novel metaheuristic optimization technique: Moth-Flame Optimizer (MFO) to solve one of the most important problems in the power system namely Optimal power flow (OPF). Three objective functions will be solved simultaneously: minimizing fuel cost, transmission loss, and...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Springer Singapore
2020
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/31645/1/Optimal%20Power%20Flow%20Solutions%20for%20Power%20System%20Operations%20Using%20Moth-Flame%20Optimization%20Algorithm.pdf http://umpir.ump.edu.my/id/eprint/31645/ https://link.springer.com/chapter/10.1007/978-981-15-5281-6_15 https://doi.org/10.1007/978-981-15- 5281-6_15 |
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| Summary: | This article proposes a recent novel metaheuristic optimization technique: Moth-Flame Optimizer (MFO) to solve one of the most important problems in the power system namely Optimal power flow (OPF). Three objective functions will be solved simultaneously: minimizing fuel cost, transmission loss, and voltage deviation minimization using a weighted factor. To show the effectiveness of proposed MFO in solving the mentioned problem, the IEEE 30-bus test system will be used. Then the obtained result from the MFO algorithm is compared with other selected well-known algorithms. The comparison proves that MFO gives better results compared to the other compared algorithms. MFO gives a reduction of 14.50% compared to 13.38 and 14.15% for artificial bee colony (ABC) and Improved Grey Wolf Optimizer (IGWO) respectively |
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