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Sequential quadratic programming based differential evolution algorithm for optimal power flow problem
Published in
2011
Volume: 5
   
Issue: 11
Pages: 1149 - 1154
Abstract
This study proposes a hybrid algorithm combining sequential quadratic programming (SQP) and differential evolution (DE) algorithm for solving the optimal power flow (OPF) problem. In this hybrid method, SQP is used to generate an individual, which is a member of an initial population, for DE algorithm. Having generated an individual by SQP, which will be nearer to the optimal solution, DE algorithm can reach the optimal solution more effectively than the classical evolutionary algorithms can. The proposed method has been used to solve the OPF problem on the standard IEEE 30- and IEEE 118-bus test systems to validate the effectiveness. Two different objectives, namely fuel cost considering valve-point effects and the transmission line losses, have been considered. The simulation results obtained from the proposed hybrid method reveal that this algorithm gives better solution for the problem having more non-convexity. © 2011 The Institution of Engineering and Technology.
About the journal
JournalIET Generation, Transmission and Distribution
ISSN17518687
Open AccessNo
Concepts (20)
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    DE ALGORITHMS
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    DIFFERENTIAL EVOLUTION ALGORITHMS
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    FUEL COST
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    Hybrid algorithms
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    Hybrid method
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    INITIAL POPULATION
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    NONCONVEXITY
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    OPTIMAL POWER FLOW PROBLEM
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    Optimal solutions
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    SEQUENTIAL QUADRATIC PROGRAMMING
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    Simulation result
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    Test systems
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    TRANSMISSION LINE LOSS
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    VALVE POINT EFFECTS
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    ACOUSTIC GENERATORS
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    Electric load flow
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    Optimal systems
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    Optimization
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    Quadratic programming
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    Evolutionary algorithms