Center for Energy and Environmental Policy Research, Beijing Institute of Technology
School of Management, Beijing Institute of Technology
Big Data Center of State Grid Corporation of China

针对电动汽车无序充电成本高、负荷波动大和间接碳排放高等问题,结合电碳排放因子和分时电价建立了电动汽车有序充电多目标优化调度模型。模型综合用户充电成本、电网负荷方差、充电碳排放量作为目标函数,设置变压器容量约束、电池充电量灵活荷电状态(SOC)需求约束、充电速率约束等约束条件,提出了电动汽车在居民小区、单位园区、公共停车场、高速服务区等多场景下有序充电优化调度策略。通过对比各个充电场景下四季典型日的优化调度结果,发现基于充电功率实时调整、分时电价引入和灵活SOC需求构建的有序充电策略与同情景下电动汽车无序充电相比,在节约用户成本、维持电网稳定性和降低充电碳排放方面均表现出明显的优越性。研究发现在供电公司执行有序充电优化调度策略时,居民小区情景的最优充电时间是0:00到8:00,单位园区情景是6:00到10:00和12:00到21:00,公共停车场情景是10:00到18:00,高速服务区情景是8:00到10:00和12:00到16:00,此时能够同时达到降低用户充电成本、平抑负荷波动以及降低充电碳排放的优化效果。

For the problems of high cost, large load fluctuation and indirect carbon emission caused by the disordered charging of electric vehicles, this research combines the electric carbon emission factor and time-of-use electricity price to design an optimization scheme for carbon emission reduction of electric vehicles (EVs). This paper jointly establishes a multi-objective optimization model for orderly charging with EV users’ charging cost, grid load variance and carbon emissions from charging as theobjective functions, setting constraints such as transformer capacity constraints, flexible state-of-charge (SOC) demand constraints for battery charging and charging rate constraints. Finally, we researched the orderly charging scheduling and optimization strategy for EVs in multiple scenarios such as residential quarter, business park, public parking lot and high-speed service area. By comparing the optimized scheduling results of typical days in four seasons under each charging scenario, it is found that the orderly charging scheduling strategy based on real-time adjustment of charging power, introduction of time-of-use electricity price and flexible SOC demand in this paper shows excellent superiority in terms of saving users’ cost, maintaining the stability of the power grid and reducing the carbon consumption compared with the disordered charging of EVs under the same scenario. The research also found that when the power supply company implements the defined orderly charging scheduling strategy, optimal charging times vary by scenarios: 0:00-8:00 for residential areas, 6:00-10:00 and 12:00-21:00 for business parks, 10:00-18:00 for public parking lots, and 8:00-10:00 and 12:00-16:00 for highway service areas. These strategies simultaneously reduce EV charging costs, smooth load fluctuations and decrease charging-related carbon emissions.

陈建民, 王洁, 陈士翀, 赵伟刚. 计及碳减排的电动汽车充电多目标优化调度. 煤炭经济研究. 2024, 44(10): 111-122

CHEN Jianmin, WANG Jie , CHEN Shichong , ZHAO Weigang. Multi-objective optimal scheduling of electric vehicle charging considering carbon emission reduction. Coal Economic Research. 2024, 44(10): 111-122