نتایج جستجو برای: v2g
تعداد نتایج: 463 فیلتر نتایج به سال:
This work proposes a differential evolution algorithm to control vehicle-to-grid (V2G) system based on photovoltaic generation and energy cost curves, constraints associated with the power converters’ operation, battery charging strategy, initial budgets. The is designed trade off batteries’ state of charge profits gained from selling grid. To achieve this balance, fuzzy controller employed act...
Vehicle-to-grid (V2G) networks have been emerged as a new technology in the smart grid (SG). These allow two-way flow of energy-trading between electric vehicles (EVs) and charging stations (CSs) SG. EVs are regarded one most effective tools to reduce energy demands. It will bring great impact on our society human life. Thus, during trading CSs, various security, privacy challenges occur V2G ne...
With the development of EVs (Electric Vehicles) and rapidly developing policies on low carbon environmental protection, electric power systems natural gas become increasingly larger. Under these circumstances, V2G (Vehicle-to-grid) coordinated operation an integrated electricity–gas distribution system (IEGDS), considering CO2 emissions, can play a part together in process energy conservation. ...
Abstract The increasing number of DC loads, such as electric vehicles (EVs), has resulted in micro-grid undergoing difficulty satisfying the various demands loads. study develops a multi-objective capacity optimization allocation model for hybrid on bases users’ satisfaction and orderly charging/discharging EVs. proposed aims to reduce cost AC/DC improve satisfaction. Particle swarm algorithm i...
In order to meet the increasing demand for electricity maintain electric vehicles (EVs) worldwide, this paper aims improve our understanding of impact load on power grid generated by charging and discharging vehicles. The rapid development vehicle (EV) industry offers new economic environmental benefits, such as mitigating global warming reducing carbon dioxide. On other hand, however, we will ...
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