Wentao Xin , Zhenwei Lu , Zhe Yu , Zhaoxuan He , Hongjiang Pu, Bin Ye
{"title":"深圳电动汽车充电站集热器驱动优化:智能充电、可再生能源整合和储能协同发展","authors":"Wentao Xin , Zhenwei Lu , Zhe Yu , Zhaoxuan He , Hongjiang Pu, Bin Ye","doi":"10.1016/j.apenergy.2025.126345","DOIUrl":null,"url":null,"abstract":"<div><div>The widespread adoption of electric vehicles (EVs) presents substantial challenges such as increased peak loads, accelerated power infrastructure degradation and reduced economic efficiency. To address these issues, this study proposes an integrated multi-technology charging station model alongside an innovative analytical framework for assessing the comprehensive benefits of charging aggregators. The framework integrated a randomised load forecasting model with a smart charging strategy and was validated using real-world data obtained from 1682 charging stations, comprising 24,798 individual charging piles, in Shenzhen, China. Implementing the proposed charging station model, combined with Shenzhen's time-of-use tariff structure and an >80 % renewable energy penetration rate, reduced levelised cost of energy, carbon emissions and peak load by 0.38 Yuan per kWh. Furthermore, renewable energy contributes to a 44.01 % reduction in carbon emissions in the smart charging system, outperforming the 41.24 % reduction observed in the on-demand charging system. Additionally, smart charging and on-demand charging methods reduce peak loads by 30.03 % and 15.40 %, respectively. It is found that combining energy storage with smart charging effectively mitigates their negative effects on emissions and costs. Energy storage increased annual carbon emissions (from 1.402 Mt. to 1.688 Mt) in an on-demand charging scenario, whereas it decreased them in a smart charging scenario. Although the current uneven distribution and low utilisation rate of EV charging resources in Shenzhen have resulted in financial losses for charging aggregators, the anticipated rapid growth in charging demand and improved utilisation rates are expected to substantially enhance profitability. Overall, this study provides a theoretical foundation for the sustainable development of charging infrastructure, thereby enhancing grid stability and renewable energy integration.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"397 ","pages":"Article 126345"},"PeriodicalIF":11.0000,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Aggregator-driven optimisation of electric vehicle charging stations in Shenzhen: Synergising smart charging, renewable energy integration and energy storage\",\"authors\":\"Wentao Xin , Zhenwei Lu , Zhe Yu , Zhaoxuan He , Hongjiang Pu, Bin Ye\",\"doi\":\"10.1016/j.apenergy.2025.126345\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The widespread adoption of electric vehicles (EVs) presents substantial challenges such as increased peak loads, accelerated power infrastructure degradation and reduced economic efficiency. To address these issues, this study proposes an integrated multi-technology charging station model alongside an innovative analytical framework for assessing the comprehensive benefits of charging aggregators. The framework integrated a randomised load forecasting model with a smart charging strategy and was validated using real-world data obtained from 1682 charging stations, comprising 24,798 individual charging piles, in Shenzhen, China. Implementing the proposed charging station model, combined with Shenzhen's time-of-use tariff structure and an >80 % renewable energy penetration rate, reduced levelised cost of energy, carbon emissions and peak load by 0.38 Yuan per kWh. Furthermore, renewable energy contributes to a 44.01 % reduction in carbon emissions in the smart charging system, outperforming the 41.24 % reduction observed in the on-demand charging system. Additionally, smart charging and on-demand charging methods reduce peak loads by 30.03 % and 15.40 %, respectively. It is found that combining energy storage with smart charging effectively mitigates their negative effects on emissions and costs. Energy storage increased annual carbon emissions (from 1.402 Mt. to 1.688 Mt) in an on-demand charging scenario, whereas it decreased them in a smart charging scenario. Although the current uneven distribution and low utilisation rate of EV charging resources in Shenzhen have resulted in financial losses for charging aggregators, the anticipated rapid growth in charging demand and improved utilisation rates are expected to substantially enhance profitability. Overall, this study provides a theoretical foundation for the sustainable development of charging infrastructure, thereby enhancing grid stability and renewable energy integration.</div></div>\",\"PeriodicalId\":246,\"journal\":{\"name\":\"Applied Energy\",\"volume\":\"397 \",\"pages\":\"Article 126345\"},\"PeriodicalIF\":11.0000,\"publicationDate\":\"2025-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Energy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S030626192501075X\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Energy","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S030626192501075X","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Aggregator-driven optimisation of electric vehicle charging stations in Shenzhen: Synergising smart charging, renewable energy integration and energy storage
The widespread adoption of electric vehicles (EVs) presents substantial challenges such as increased peak loads, accelerated power infrastructure degradation and reduced economic efficiency. To address these issues, this study proposes an integrated multi-technology charging station model alongside an innovative analytical framework for assessing the comprehensive benefits of charging aggregators. The framework integrated a randomised load forecasting model with a smart charging strategy and was validated using real-world data obtained from 1682 charging stations, comprising 24,798 individual charging piles, in Shenzhen, China. Implementing the proposed charging station model, combined with Shenzhen's time-of-use tariff structure and an >80 % renewable energy penetration rate, reduced levelised cost of energy, carbon emissions and peak load by 0.38 Yuan per kWh. Furthermore, renewable energy contributes to a 44.01 % reduction in carbon emissions in the smart charging system, outperforming the 41.24 % reduction observed in the on-demand charging system. Additionally, smart charging and on-demand charging methods reduce peak loads by 30.03 % and 15.40 %, respectively. It is found that combining energy storage with smart charging effectively mitigates their negative effects on emissions and costs. Energy storage increased annual carbon emissions (from 1.402 Mt. to 1.688 Mt) in an on-demand charging scenario, whereas it decreased them in a smart charging scenario. Although the current uneven distribution and low utilisation rate of EV charging resources in Shenzhen have resulted in financial losses for charging aggregators, the anticipated rapid growth in charging demand and improved utilisation rates are expected to substantially enhance profitability. Overall, this study provides a theoretical foundation for the sustainable development of charging infrastructure, thereby enhancing grid stability and renewable energy integration.
期刊介绍:
Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.