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.
Highlights
Wireless power transfer (WPT) technology has widely attracted attention from research institutions and companies all over the world
The wireless power transfer grid (WPTG) consists of battery-powered device nodes
The variable-length encoding mechanism is adopted for the energy link solution encoding
Summary
Wireless power transfer (WPT) technology has widely attracted attention from research institutions and companies all over the world. With the increase of the system operation frequency, the relevant electromagnetic interference (EMI) problem, which is common in high frequency applications, becomes worse in the WPT system Another alternative should be proposed to enhance the power transfer performance. To achieve the power transfer process within a multi-device system, a regional smart microgrid [18,19] named the wireless power transfer grid (WPTG) [20,21] has been proposed recently It contributes to ensuring real-time energy supplies and energy load balance during the power transfer process. This energy grid is comprised of battery-powered device nodes. The energy link optimization in WPTG under energy autonomy will be presented with the consideration of power transfer and grid characteristics.
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