由聚合商驱动的深圳电动汽车充电站优化：协同智能充电、可再生能源整合与储能

Abstract 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.