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Multi-objective harmony search algorithm for optimal power flow problem
Published in
2011
Volume: 33
   
Issue: 3
Pages: 745 - 752
Abstract
This paper proposes a multi-objective harmony search (MOHS) algorithm for optimal power flow (OPF) problem. OPF problem is formulated as a non-linear constrained multi-objective optimization problem where different objectives and various constraints have been considered into the formulation. Fast elitist non-dominated sorting and crowding distance have been used to find and manage the Pareto optimal front. Finally, a fuzzy based mechanism has been used to select a compromise solution from the Pareto set. The proposed MOHS algorithm has been tested on IEEE 30 bus system with different objectives. Simulation results are also compared with fast non-dominated sorting genetic algorithm (NSGA-II) method. It is clear from the comparison that the proposed method is able to generate true and well distributed Pareto optimal solutions for OPF problem. © 2010 Elsevier Ltd. All rights reserved.
About the journal
JournalInternational Journal of Electrical Power and Energy Systems
ISSN01420615
Open AccessNo
Concepts (29)
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    Bus systems
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    COMPROMISE SOLUTIONS
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    CONSTRAINED MULTI-OBJECTIVE OPTIMIZATIONS
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    CROWDING DISTANCE
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    FUEL COST
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    Harmony search
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    HARMONY SEARCH ALGORITHM
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    HARMONY SEARCH ALGORITHMS
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    Multi objective
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    NON-DOMINATED SORTING
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    NON-DOMINATED SORTING GENETIC ALGORITHMS
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    Non-linear
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    NSGA-II
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    OPTIMAL POWER FLOW PROBLEM
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    OPTIMAL POWER FLOWS
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    PARETO SET
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    PARETO-OPTIMAL FRONT
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    Simulation result
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    VOLTAGE STABILITY ENHANCEMENT
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    WELL-DISTRIBUTED PARETO-OPTIMAL SOLUTIONS
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    ACOUSTIC GENERATORS
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    Composite structures
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    Constrained optimization
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    Costs
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    Electric load flow
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    Learning algorithms
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    Pareto principle
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    Voltage stabilizing circuits
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    Multiobjective optimization