{"title":"Energy Management for EV Charging Based on Solar Energy in an Industrial Microgrid","authors":"Murat Akil, Emrah Dokur, R. Bayindir","doi":"10.1109/ICRERA49962.2020.9242663","DOIUrl":null,"url":null,"abstract":"Today, energy is a strategic value and became a phenomenon that shows the level of development of countries. With the increase in energy consumption in many countries, the efficient use of resources in energy production has gained importance. Integration of renewable energy generation with EV has become one of the new trends for optimal use of Renewable Energy Resources (RES), meeting energy demand, improving grid stability and sustainability. In this paper, energy management of EV charging based on PV system for an Industrial Microgrid (IMG) is presented to provide EV load shaving service and optimize the cost of charging electrical energy. Using the travel behaviors of EVs, daily charging energy is investigated and Monte Carlo Simulation (MCS) based on statistical data is applied to determine driving time for EVs. By analyzing the battery charge properties of EVs, the initial state of charge (SOC) is calculated, and the total charge power and the charging time of EVs are obtained in the analysis. Using the data obtained from 673.42 kWp a solar power plant (SPP) named Harput-SPP, the analysis of 5,000 EV charge loads is developed in the model created on the MATLAB/Simulink software platform.","PeriodicalId":129367,"journal":{"name":"2020 9th International Conference on Renewable Energy Research and Application (ICRERA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 9th International Conference on Renewable Energy Research and Application (ICRERA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRERA49962.2020.9242663","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Today, energy is a strategic value and became a phenomenon that shows the level of development of countries. With the increase in energy consumption in many countries, the efficient use of resources in energy production has gained importance. Integration of renewable energy generation with EV has become one of the new trends for optimal use of Renewable Energy Resources (RES), meeting energy demand, improving grid stability and sustainability. In this paper, energy management of EV charging based on PV system for an Industrial Microgrid (IMG) is presented to provide EV load shaving service and optimize the cost of charging electrical energy. Using the travel behaviors of EVs, daily charging energy is investigated and Monte Carlo Simulation (MCS) based on statistical data is applied to determine driving time for EVs. By analyzing the battery charge properties of EVs, the initial state of charge (SOC) is calculated, and the total charge power and the charging time of EVs are obtained in the analysis. Using the data obtained from 673.42 kWp a solar power plant (SPP) named Harput-SPP, the analysis of 5,000 EV charge loads is developed in the model created on the MATLAB/Simulink software platform.
今天,能源已经成为一种战略价值,成为一种体现国家发展水平的现象。随着许多国家能源消耗的增加,能源生产中资源的有效利用变得越来越重要。可再生能源发电与电动汽车并网发电已成为优化利用可再生能源、满足能源需求、提高电网稳定性和可持续性的新趋势之一。本文提出了基于光伏系统的工业微电网电动汽车充电能量管理,为电动汽车提供减载服务,优化充电电能成本。利用电动汽车的行驶行为,研究了电动汽车的日充电能量,并采用基于统计数据的蒙特卡罗仿真(Monte Carlo Simulation, MCS)确定了电动汽车的行驶时间。通过对电动汽车电池充电特性的分析,计算出电动汽车的初始充电状态(SOC),并在分析中得到电动汽车的总充电功率和充电时间。利用673.42 kWp太阳能发电厂Harput-SPP的数据,在MATLAB/Simulink软件平台上建立模型,对5000辆电动汽车的充电负荷进行了分析。