English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

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

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