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Differential evolutionary algorithm for optimal reactive power dispatch
Published in
2008
Volume: 30
   
Issue: 8
Pages: 435 - 441
Abstract
This paper presents differential evolutionary algorithm for optimal dispatch for reactive power and voltage control in power system operation studies. The problem is formulated as a mixed integer, nonlinear optimization problem taking into account both continuous and discrete control variables. The optimal setting of control variables such as generator voltages, tap positions of tap changing transformers and the number of shunt reactive compensation devices to be switched for real power loss minimization in the transmission system are determined. In the proposed method, the inequality operational constraints were handled by "penalty parameterless" approach. This helps in avoiding the time-consuming trial and error process for fixing the penalty parameter and makes the process system independent. The algorithm was tested on standard IEEE 14,30,57 and 118-Bus systems and the results compared with conventional method. © 2008 Elsevier Ltd. All rights reserved.
About the journal
JournalInternational Journal of Electrical Power and Energy Systems
ISSN01420615
Open AccessNo
Concepts (36)
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    Electric generators
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    Electric network analysis
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    Electric potential
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    Electric power factor
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    Electric power systems
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    Electric power transmission
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    Integer programming
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    Nonlinear programming
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    Optimization
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    Power transformers
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    Power transmission
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    Reactive power
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    Standards
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    Voltage regulators
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    Bus systems
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    Control variables
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    Conventional methods
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    Differential evolution
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    Discrete control
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    Evolutionary computation
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    Loss minimization
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    MIXED INTEGERS
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    NON-LINEAR OPTIMIZATION PROBLEMS
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    O PTIMAL SETTING
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    Operational constraints
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    OPTIMAL DISPATCHING
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    Optimal power flow
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    OPTIMAL REACTIVE POWER DISPATCH
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    Penalty function
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    POWER SYSTEM OPERATIONS
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    PROCESS SYSTEMS
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    Reactive compensation
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    REAL POWER LOSS
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    Transmission systems
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    TRIAL-AND-ERROR PROCESSES
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    Evolutionary algorithms