Grey Wolf Optimizer for solving single objective functions optimal power flow
In power system, the optimal power flow (OPF) is one of the main significant issues that should be solved to achieve the optimal operation, planning, and energy management. Many stochastic optimization algorithms have been suggested to solve OPF problems. Grey wolf optimizer (GWO) is one of the meta...
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Published in | 2023 13th International Symposium on Advanced Topics in Electrical Engineering (ATEE) pp. 1 - 5 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
23.03.2023
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Subjects | |
Online Access | Get full text |
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Summary: | In power system, the optimal power flow (OPF) is one of the main significant issues that should be solved to achieve the optimal operation, planning, and energy management. Many stochastic optimization algorithms have been suggested to solve OPF problems. Grey wolf optimizer (GWO) is one of the metaheuristic techniques that have been recently applied in power systems. The main aim of this paper is to find optimal objective functions such as fuel cost of generators, emissions, active power losses, and voltage deviation at load bus. The control variables must be setting to obtain optimal objective function are active power of generators (except the swing bus generator), voltage magnitude at load bus, sources VAR compensations that are connected to transmission lines to compensate the reactive power on the network and tap changer setting at the transformers. To prove the superiority and efficiency of GWO in power system applications, IEEE 57-bus test power is the network that has been applied to it. The comparison results of objective functions confirmed the superiority of GWO in providing better solutions than the well-known methods reported in the literature. |
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ISSN: | 2159-3604 |
DOI: | 10.1109/ATEE58038.2023.10108149 |