Nowadays, running out of fossil fuels and more attention to reduce environmental pollutions are essential factors for the growing use of electric vehicles (EVs). Owing to these factors, it is important to present a method, which schedules charging or discharging of EVs and simultaneously considers economic and environmental aspects of the problem. This study proposes a multi-objective optimisation programme for charging or discharging of EVs in a smart distribution system by taking advantage of advanced metering infrastructure and uses a ɛ-constraint method for minimising operational costs and (CO2) emissions. Simulating stochastic patterns of EV owner driving behaviour as well as considering different models and types of EVs with the help of trip planning algorithm are the main advantages of this study. Investigating the multi-objective problem in two cases shows the effectiveness and flexibility of this algorithm in real cases. Besides, vehicle-to-grid capability of EVs was also considered. This method was tested on a 33-bus distribution test system for over 24 h. As the results show, the total amount of scheduled power, the peak-to-valley difference of daily load, transmission power loss, CO2 emission, and the total operational cost are reduced by the trip planning programme and EV owner revenue is increased.
Method for EV charging in stochastic smart microgrid operation with fuel cell and renewable energy source (RES) units
IET Electrical Systems in Transportation ; 10 , 3 ; 249-258
2020-02-19
10 pages
Article (Journal)
Electronic Resource
English
EV owner driving behaviour , trip planning programme , constraint method , electric vehicle charging , power distribution economics , multiobjective optimisation programme , total operational cost , stochastic smart microgrid operation , air pollution , environmental pollutions , distributed power generation , CO<sub>2</sub> , charging discharging , time 24.0 hour , smart distribution system , battery powered vehicles , fuel cell vehicles , smart power grids , economic aspects , environmental aspects , optimisation , multiobjective problem , EV charging , fuel cell , 33-bus distribution test system , fossil fuels , power generation scheduling
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