Multi-Objective Reactive Power Optimization Based on Refined Chaos Particle Swarm Optimization Algorithm

In order to reduce the active network loss, increase the power quality and voltage static stability of power system, an index function of multi-objective reactive power optimization is established. Then, an improved adaptive chaotic particle swarm optimization algorithm is proposed to solve the prob...

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Vydáno v:Applied Mechanics and Materials Ročník 494-495; číslo Current Development of Mechanical Engineering and Energy; s. 1857 - 1860
Hlavní autoři: Ai, Ying, Zhang, Dan Hong, Su, Yi Xin, Peng, Yao, Nie, Hong Wei
Médium: Journal Article
Jazyk:angličtina
Vydáno: Zurich Trans Tech Publications Ltd 06.02.2014
Témata:
Algorithms
Chaos theory
Convergence
Fitness
Multiple objective analysis
Optimization
Reactive power
Swarm intelligence
Cube Map
Reactive Power Optimization
Dynamic Inertia Weight
Particle Swarm Optimization Algorithm
ISBN:3038350036, 9783038350033
ISSN:1660-9336, 1662-7482, 1662-7482
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Shrnutí:In order to reduce the active network loss, increase the power quality and voltage static stability of power system, an index function of multi-objective reactive power optimization is established. Then, an improved adaptive chaotic particle swarm optimization algorithm is proposed to solve the problem. Through the using of cubic chaotic mapping, the particle population is initialized to enhance the diversity of its value; In the optimization process, poor fitness particles are updated with chaos disturbance, and their inertia weight are adjusted dynamically with particles fitness value so as to avoid local convergence. Simulation of IEEE 30 bus system shows that the proposed algorithm for reactive power optimization can avoid premature convergence effectively, and converge to optimal solution rapidly.
Bibliografie:Selected, peer reviewed papers from the 2013 International Symposium on Vehicle, Mechanical, and Electrical Engineering (ISVMEE 2013), December 21-22, 2013, Taiwan, China
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ISBN:3038350036
9783038350033
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.494-495.1857