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An intelligent θ-modified bat algorithm to solve the non-convex economic dispatch problem considering practical constraints

Kavousi-Fard, Abdollah and Khosravi, Abbas 2016, An intelligent θ-modified bat algorithm to solve the non-convex economic dispatch problem considering practical constraints, International journal of electrical power and energy systems, vol. 82, pp. 189-196, doi: 10.1016/j.ijepes.2016.03.017.

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Title An intelligent θ-modified bat algorithm to solve the non-convex economic dispatch problem considering practical constraints
Author(s) Kavousi-Fard, Abdollah
Khosravi, AbbasORCID iD for Khosravi, Abbas orcid.org/0000-0001-6927-0744
Journal name International journal of electrical power and energy systems
Volume number 82
Start page 189
End page 196
Total pages 8
Publisher Elsevier
Place of publication London, Eng.
Publication date 2016-11
ISSN 0142-0615
1879-3517
Keyword(s) non-convex
economic dispatch
θ-modified bat algorithm
self-adaptive modification mechanism
nonlinear constrained optimization
Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
theta-Modified Bat Algorithm
PARTICLE SWARM OPTIMIZATION
DIFFERENTIAL EVOLUTION ALGORITHM
IMPROVED GENETIC ALGORITHM
LOAD DISPATCH
COST-FUNCTIONS
ELECTRIC VEHICLES
WAVELET MUTATION
NONSMOOTH
EMISSION
RECONFIGURATION
Summary This paper proposes a practical formulation for the non-convex economic dispatch problem to consider multi-fuel options, ramp rate limits, valve loading effect, prohibited operating zones and spinning reserve. A new optimization algorithm based on the θ-bat algorithm (θ-BA) is suggested to solve the problem. The θ-BA converts the Cartesian search space into the polar coordinates such that more search ability would be achieved. According to the complex, nonlinear, and constrained nature of the problem, a new self-adaptive modification method is proposed. The proposed modified θ-BA (θ-MBA) is constructed based on the roulette wheel mechanism to effectively increase the convergence of the algorithm. The high ability and satisfying performance of the proposed optimization method is examined on IEEE 15-unit, 40-unit and 100-unit test systems.
Language eng
DOI 10.1016/j.ijepes.2016.03.017
Field of Research 0906 Electrical And Electronic Engineering
Socio Economic Objective 0 Not Applicable
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2016, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30093228

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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