Experiments with hybrid Bernstein global optimization algorithm for the OPF problem in power systems
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Authors
Maciejowski, JM
Patil, Bhagyesh V
Sampath, LPMI
Krishnan, Ashok
Ling, KV
Gooi, HB
Publication Date
2019Journal Title
Engineering Optimization
ISSN
1029-0273
Publisher
Taylor & Francis
Type
Article
Metadata
Show full item recordCitation
Maciejowski, J., Patil, B. V., Sampath, L., Krishnan, A., Ling, K., & Gooi, H. (2019). Experiments with hybrid Bernstein global optimization algorithm for the OPF problem in power systems. Engineering Optimization https://doi.org/10.1080/0305215X.2018.1521399
Abstract
This paper presents an algorithm based on the Bernstein form of polynomials for solving the optimal power flow (OPF) problem in electrical power networks. The proposed algorithm combines local and global optimization methods and is therefore referred to as a `hybrid'
Bernstein algorithm in the context of this work. The proposed algorithm is a branch-and-bound (B&B) procedure wherein a local search method is used to obtain a good upper bound on the global minimum at each branching node. Subsequently, the Bernstein form of polynomials is used to obtain a lower bound on the global minimum. The performance of the proposed algorithm is compared with the previously reported Bernstein algorithm
to demonstrate its effi cacy in terms of the chosen performance metrics. Furthermore, the proposed algorithm is tested by solving the OPF problem for several benchmark IEEE power system examples and its performance is compared with generic global optimization solvers such as BARON and COUENNE. The test results demonstrate that the algorithm HBBB
delivers satisfactory performance in terms of solution optimality.
Keywords
Bernstein polynomials, global optimization, power system, optimal power flow, non-convex problem
Sponsorship
This research is supported by the National Research Foundation, Prime Ministers Office, Singapore, under its CREATE programme.
Funder references
National Research Foundation Singapore (via Cambridge Centre for Advanced Research and Education in Singapore (CARES)) (unknown)
Identifiers
External DOI: https://doi.org/10.1080/0305215X.2018.1521399
This record's URL: https://www.repository.cam.ac.uk/handle/1810/279877
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