Hybrid Differential Evolution Particle Swarm Optimization Algorithm for Reactive Power Optimization

Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal solutions. In this paper, swarm and evolutionary algorithm have been applied for reactive power optimization. The objective of this nonlinear optimi...

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Published in:2010 Asia-Pacific Power and Energy Engineering Conference pp. 1 - 4
Main Authors: Shouzheng Wang, Lixin Ma, Dashuai Sun
Format: Conference Proceeding
Language:English
Published: IEEE 01.03.2010
Subjects:
Hybrid power systems
Linear programming
Niobium
Particle swarm optimization
Power generation
Power system simulation
Quadratic programming
Reactive power
Sun
Voltage
ISBN:1424448123, 9781424448128
ISSN:2157-4839
Online Access:Get full text
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Abstract Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal solutions. In this paper, swarm and evolutionary algorithm have been applied for reactive power optimization. The objective of this nonlinear optimization is minimization of system losses and improvement of voltage profiles in a power system. A hybrid differential evolution particle swarm optimization algorithm is presented to obtain the global optimum. The proposed algorithm is implemented on the IEEE 14-bus system. To validate the effectiveness of the algorithm, the simulation results are compared with other optimization algorithms'. It is shown that the approach developed is feasible and efficient.
AbstractList Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal solutions. In this paper, swarm and evolutionary algorithm have been applied for reactive power optimization. The objective of this nonlinear optimization is minimization of system losses and improvement of voltage profiles in a power system. A hybrid differential evolution particle swarm optimization algorithm is presented to obtain the global optimum. The proposed algorithm is implemented on the IEEE 14-bus system. To validate the effectiveness of the algorithm, the simulation results are compared with other optimization algorithms'. It is shown that the approach developed is feasible and efficient.
Author Shouzheng Wang
Dashuai Sun
Lixin Ma
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  surname: Shouzheng Wang
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  surname: Lixin Ma
  fullname: Lixin Ma
  email: ma_eeepsi@usst.edu.cn
  organization: Dept. of Electr. Eng., Univ. of Shanghai for Sci. & Tech., Shanghai, China
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  surname: Dashuai Sun
  fullname: Dashuai Sun
  organization: Dept. of Electr. Eng., Univ. of Shanghai for Sci. & Tech., Shanghai, China
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Snippet Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal...
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StartPage 1
SubjectTerms Hybrid power systems
Linear programming
Niobium
Particle swarm optimization
Power generation
Power system simulation
Quadratic programming
Reactive power
Sun
Voltage
Title Hybrid Differential Evolution Particle Swarm Optimization Algorithm for Reactive Power Optimization
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