Frederico Haasis, Oscar Solano, Daniel Dias, Bruno Borba
{"title":"基于个人充电状态优先级的停车场电动汽车智能充电控制","authors":"Frederico Haasis, Oscar Solano, Daniel Dias, Bruno Borba","doi":"10.1002/est2.70017","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>The integration of electric vehicles (EVs) into the power grid could pose challenges to power quality (PQ) depending on quantity of EVs and when they are connected. To mitigate these impacts without using drastic measures, such as disconnecting EVs, this study investigates centralized control strategies within parking facilities that prioritize EV charging based on individual State of Charge (SoC) levels. The study utilizes the IEEE 34 Bus system and conducts 3888 simulations for different scenarios to assess the impact of the quantity and placement of EVs in parking lots. The study applies the Monte Carlo method to compare the performance of different proposed controls: (i) limiting the charging current to a fixed level and (ii) varying the current based on the voltage droop step. Furthermore, Power Hardware-in-the-Loop (PHIL) simulations were carried out to validate the hierarchical control using the droop step control, demonstrating the best average performance in the previous scenarios. The findings indicated that the control responded within the expected timeframe and successfully addressed voltage sag issues, maintaining PQ in the distribution system in most cases, with its performance being influenced by the placement of parking lots in the network. Additionally, it was confirmed through quartiles that the classification based on SoC leads to a more balanced charging time for different SoC levels.</p>\n </div>","PeriodicalId":11765,"journal":{"name":"Energy Storage","volume":"6 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Electric Vehicle Smart-Charging Control for Parking Lots Based on Individual State of Charge Priority\",\"authors\":\"Frederico Haasis, Oscar Solano, Daniel Dias, Bruno Borba\",\"doi\":\"10.1002/est2.70017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>The integration of electric vehicles (EVs) into the power grid could pose challenges to power quality (PQ) depending on quantity of EVs and when they are connected. To mitigate these impacts without using drastic measures, such as disconnecting EVs, this study investigates centralized control strategies within parking facilities that prioritize EV charging based on individual State of Charge (SoC) levels. The study utilizes the IEEE 34 Bus system and conducts 3888 simulations for different scenarios to assess the impact of the quantity and placement of EVs in parking lots. The study applies the Monte Carlo method to compare the performance of different proposed controls: (i) limiting the charging current to a fixed level and (ii) varying the current based on the voltage droop step. Furthermore, Power Hardware-in-the-Loop (PHIL) simulations were carried out to validate the hierarchical control using the droop step control, demonstrating the best average performance in the previous scenarios. The findings indicated that the control responded within the expected timeframe and successfully addressed voltage sag issues, maintaining PQ in the distribution system in most cases, with its performance being influenced by the placement of parking lots in the network. Additionally, it was confirmed through quartiles that the classification based on SoC leads to a more balanced charging time for different SoC levels.</p>\\n </div>\",\"PeriodicalId\":11765,\"journal\":{\"name\":\"Energy Storage\",\"volume\":\"6 5\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Storage\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/est2.70017\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Storage","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/est2.70017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Electric Vehicle Smart-Charging Control for Parking Lots Based on Individual State of Charge Priority
The integration of electric vehicles (EVs) into the power grid could pose challenges to power quality (PQ) depending on quantity of EVs and when they are connected. To mitigate these impacts without using drastic measures, such as disconnecting EVs, this study investigates centralized control strategies within parking facilities that prioritize EV charging based on individual State of Charge (SoC) levels. The study utilizes the IEEE 34 Bus system and conducts 3888 simulations for different scenarios to assess the impact of the quantity and placement of EVs in parking lots. The study applies the Monte Carlo method to compare the performance of different proposed controls: (i) limiting the charging current to a fixed level and (ii) varying the current based on the voltage droop step. Furthermore, Power Hardware-in-the-Loop (PHIL) simulations were carried out to validate the hierarchical control using the droop step control, demonstrating the best average performance in the previous scenarios. The findings indicated that the control responded within the expected timeframe and successfully addressed voltage sag issues, maintaining PQ in the distribution system in most cases, with its performance being influenced by the placement of parking lots in the network. Additionally, it was confirmed through quartiles that the classification based on SoC leads to a more balanced charging time for different SoC levels.