Application of improved bat algorithm in optimal power flow problem

This paper proposes an improved bat algorithm to solve multi-objective optimal power flow problem (MOPF) based on the weighted method. The MOPF problem is formulated as a non-linear constrained optimization problem where two objective functions (minimization of fuel cost and emission) and various co...

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Bibliographic Details
Published in:Applied intelligence (Dordrecht, Netherlands) Netherlands), 2018-08, Vol.48 (8), p.2304-2314
Main Authors: Yuan, Yanbin, Wu, Xiaotao, Wang, Pengtao, Yuan, Xiaohui
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Computer Science
Computer simulation
Fuzzy set theory
Fuzzy sets
Machines
Manufacturing
Mechanical Engineering
Multiple objective analysis
Optimization
Power flow
Processes
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Summary:This paper proposes an improved bat algorithm to solve multi-objective optimal power flow problem (MOPF) based on the weighted method. The MOPF problem is formulated as a non-linear constrained optimization problem where two objective functions (minimization of fuel cost and emission) and various constraints are considered. After having found the Pareto solutions with the improved bat algorithm, the fuzzy set theory is used to find the compromise solution. Finally, the IEEE 57-bus system is applied to verify the performance of the proposed method for the MOPF problem. The results are compared with those obtained by the state-of-the-art optimization algorithms reported in literature. The simulation results demonstrate the superiority of the proposed method for solving the MOPF problem in terms of solution quality.
ISSN:0924-669X
1573-7497
DOI:10.1007/s10489-017-1081-2