Binary whale optimization algorithm: a new metaheuristic approach for profit-based unit commitment problems in competitive electricity markets

This article presents a metaheuristic approach, the binary whale optimization algorithm (BWOA), to solve complex, constrained, non-convex, binary-nature profit-based unit commitment (PBUC) optimization problems of a price-taking generation company (GenCo) in the electricity market. To simulate the b...

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Veröffentlicht in:Engineering optimization Jg. 51; H. 3; S. 369 - 389
Hauptverfasser: Reddy K., Srikanth, Panwar, Lokesh, Panigrahi, B. K., Kumar, Rajesh
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Abingdon Taylor & Francis 04.03.2019
Taylor & Francis Ltd
Schlagworte:
Algorithms
Binary optimization
binary whale optimization
Computer simulation
electricity market
Electricity pricing
Heuristic methods
Markets
meta-heuristic optimization
Optimization
Optimization algorithms
Position (location)
profit-based unit commitment
System effectiveness
Transfer functions
Unit commitment
ISSN:0305-215X, 1029-0273
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Zusammenfassung:This article presents a metaheuristic approach, the binary whale optimization algorithm (BWOA), to solve complex, constrained, non-convex, binary-nature profit-based unit commitment (PBUC) optimization problems of a price-taking generation company (GenCo) in the electricity market. To simulate the binary-nature PBUC problem, the continuous, real-value whale position/location is mapped into binary search space through various transfer functions. This article introduces three variants of BWOA using tangential hyperbolic, inverse tangent (arctan) and sigmoidal transfer functions. The effectiveness of the BWOA approaches is examined in test systems with different market mechanisms, i.e. an energy-only market, and energy and reserve market participation with different reserve payment methods. The simulation results are presented, discussed and compared with other existing approaches. The convergence characteristics, solution quality and consistency of the results across different BWOA variants are discussed. The superiority and statistical significance of the proposed approaches with respect to existing approaches is also presented.
Bibliographie:ObjectType-Article-1
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ISSN:0305-215X
1029-0273
DOI:10.1080/0305215X.2018.1463527