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Energies 2016, 9(9), 682; doi:10.3390/en9090682

Energy Link Optimization in a Wireless Power Transfer Grid under Energy Autonomy Based on the Improved Genetic Algorithm

1
State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing 400044, China
2
College of Automation, Chongqing University, Chongqing 400044, China
3
Department of Engineering, The University of Auckland, Auckland 1142, New Zealand
*
Author to whom correspondence should be addressed.
Academic Editor: William Holderbaum
Received: 28 March 2016 / Revised: 31 July 2016 / Accepted: 18 August 2016 / Published: 26 August 2016
(This article belongs to the Special Issue Control of Energy Storage)
View Full-Text   |   Download PDF [956 KB, uploaded 26 August 2016]   |  

Abstract

In this paper, an optimization method is proposed for the energy link in a wireless power transfer grid, which is a regional smart microgrid comprised of distributed devices equipped with wireless power transfer technology in a certain area. The relevant optimization model of the energy link is established by considering the wireless power transfer characteristics and the grid characteristics brought in by the device repeaters. Then, a concentration adaptive genetic algorithm (CAGA) is proposed to optimize the energy link. The algorithm avoided the unification trend by introducing the concentration mechanism and a new crossover method named forward order crossover, as well as the adaptive parameter mechanism, which are utilized together to keep the diversity of the optimization solution groups. The results show that CAGA is feasible and competitive for the energy link optimization in different situations. This proposed algorithm performs better than its counterparts in the global convergence ability and the algorithm robustness. View Full-Text
Keywords: wireless power transfer; wireless power transfer grid; energy link; genetic algorithm wireless power transfer; wireless power transfer grid; energy link; genetic algorithm
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Zhao, Z.; Sun, Y.; Hu, A.P.; Dai, X.; Tang, C. Energy Link Optimization in a Wireless Power Transfer Grid under Energy Autonomy Based on the Improved Genetic Algorithm. Energies 2016, 9, 682.

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