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首页> 外文期刊>Electrical Systems in Transportation, IET >Method for EV charging in stochastic smart microgrid operation with fuel cell and renewable energy source (RES) units
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Method for EV charging in stochastic smart microgrid operation with fuel cell and renewable energy source (RES) units

机译:具有燃料电池和可再生能源(RES)单元的随机智能微电网运行中的EV充电方法

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摘要

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 ae-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, CO(2)emission, and the total operational cost are reduced by the trip planning programme and EV owner revenue is increased.
机译:如今,无化石燃料耗尽,更加注重减少环境污染是越来越多的电动汽车(EVS)的重要因素。由于这些因素,重要的是提出一种方法,该方法调度EVS的收费或放电并同时考虑问题的经济和环境方面。本研究提出了一种通过利用先进的计量基础设施来在智能分配系统中充电或放电的多目标优化计划,并使用AE限制方法以最小化运营成本和(CO2)排放。在旅行规划算法的帮助下,考虑不同型号和电源类型的考虑不同型号和类型的电视机,是这项研究的主要优势。调查两种情况下的多目标问题显示了该算法在实际情况下的有效性和灵活性。此外,还考虑了EVS的车辆对网格能力。在33柱分布测试系统上测试该方法超过24小时。随着结果表明,预定功率的总量,日常负荷,传输功率损耗,CO(2)排放的峰值谷差异,以及旅行计划计划和EV业主收入减少了总运营成本增加。

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