计及电动汽车充电需求的城市配电网多场景低碳优化调度研究

Multi-scenario low-carbon optimization scheduling study for urban distribution networks considering electric vehicle charging demand high proportion of photovoltaic and energy storage integration

【目的】随着光伏、储能、电动汽车负荷在配电网中占比不断增加,高比例新能源的波动性与不确定性给配电网低碳运行带来了巨大挑战。为了有效地减少配电网的碳排放量,【方法】提出了一种考虑电动汽车负荷充电需求的配电网低碳经济优化调度方法。首先给出了基于动态碳排放因子的配电网负荷侧碳排放量计算方法,并针对居民用户、商业用户场景,构建城市配电网多场景下的电动汽车负荷充电模型,并将电动汽车负荷充电状态作为决策变量,以调度成本和碳排放量最小为目标,对配电网进行优化调度。通过在改进IEEE-33节点配电网中进行算例分析【结果】以夏季典型日为例,在可协调SOC调度模式下,居民负荷调度成本和碳排放量相比于无序SOC调度模式分别降低了8.06%、13.92%,商业负荷调度成本和碳排放量相比于无序SOC调度模式分别降低了4.31%、4.87%。【结论】结果表明,针对不同的用户场景,对电动汽车充电负荷采用可协调SOC的充电调度方法,可以有效减小配电网的调度成本,降低配电网的碳排放量。

[Objective]With the increasing proportion of photovoltaics,energy storage,and electric vehicle loads in the distribution grid,the fluctuation and uncertainty of high-proportion renewable energy pose significant challenges to the low-carbon operation of the distribution network.In order to effectively reduce the carbon emissions of the distribution network,[Methods]This paper proposes a low-carbon economic optimization scheduling method for distribution networks that takes into account the charging demands of electric vehicle(EV)loads.Initially,a method for calculating the carbon emissions of the distribution network load side is provided based on dynamic carbon emission factors.For residential and commercial user scenarios,charging models for electric vehicle loads are developed under various urban distribution network scenarios.The charging status of electric vehicle loads is taken as a decision variable,and the optimization scheduling of the distribution network is performed with the objective of minimizing scheduling costs and carbon emissions.Case studies are conducted on an improved IEEE-33 node distribution network to analyze the effectiveness of the proposed method,[Results]Taking a typical summer day as an example,under the coordinated State of Charge(SOC)scheduling mode,the scheduling costs and carbon emissions of residential loads are reduced by 8.06%and 13.92%,respectively,compared to the uncoordinated SOC scheduling mode.Similarly,the scheduling costs and carbon emissions of commercial loads are reduced by 4.31%and 4.87%,respectively,compared to the uncoordinated SOC scheduling mode.[Conclusion]The result indicate that,for different user scenarios,employing a coordinated State of Charge(SOC)charging scheduling method for electric vehicle charging loads can effectively reduce the scheduling costs of the distribution network and decrease the carbon emissions of the distribution network.