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Optimal Reactive Power Dispatch Using Chaotic Bat Algorithm

delete2020-01-01
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OA
AI
S
Sylvère Mugemanyi
Z
Zhaoyang Qu *
F
François Xavier Rugema
Y
Yunchang Dong
C
Christophe Bananeza
王
王磊 (Lei Wang)
DOI:10.1109/ACCESS.2020.2982988delete
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摘要

摘要

En 中文
In this paper, the chaotic bat algorithm (CBA) is applied to solve the optimal reactive power dispatch (ORPD) problem taking into account small-scale, medium-scale and large-scale power systems. ORPD plays a key role in the power system operation and control. The ORPD problem is formulated as a mixed integer nonlinear programming problem, comprising both continuous and discrete control variables. The most outstanding benefit of the bat algorithm (BA) is its good convergence for optimal solutions. The BA, however, together with other metaheuristics, often gets stuck into local optima and in order to cope with this shortcoming, the use of the CBA is proposed in this paper. The CBA results from introducing the chaotic sequences into the standard BA to enhance its global search ability. The CBA is utilized to find the optimal settings of generator bus voltages, tap setting transformers and shunt reactive power sources. Three objective functions such as minimization of active power loss, total voltage deviations and voltage stability index are considered in this study. The effectiveness of the CBA technique is demonstrated for standard IEEE 14-bus, IEEE 39 New England bus, IEEE 57-bus, IEEE 118-bus and IEEE 300-bus test systems. The results yielded by the CBA are compared with other algorithms available in the literature. Simulation results reveal the effectiveness and robustness of the CBA for solving the ORPD problem.
Keyword:
Power system stability
Optimization
Indexes
Reactive power
Stability criteria
Search problems
Heuristic algorithms
Chaotic bat algorithm
optimal reactive power dispatch
chaotic sequences
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期刊

IEEE Access 封面图
IEEE Access
IF:
3.6
论文数:
9.8W
被引数:
29.4W

机构

H
Hohai University
学者数:
2.3W
论文数: 1.8W
被引数: 2.1W
N
northeast electric power university
学者数:
5.8K
论文数: 3.3K
被引数: 1
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