考虑分布式光伏和电动汽车接入的配电网空间负荷预测方法

针对大规模分布式光伏和电动汽车接入配电网对空间负荷预测影响的问题,提出一种考虑远景年屋顶分布式光伏饱和安装、大规模电动汽车参与V2G的城市配电网空间负荷预测方法。区分不同小区,依据相应的容积率和可利用率系数计算屋顶光伏饱和安装面积,结合历史辐射值数据计算光伏出力。基于改进型停车生成率模型预测停车需求,结合日行驶里程、停车特性和充放电策略,建立电动汽车V2G负荷预测模型,利用蒙特卡罗仿真得出V2G负荷时空分布情况。采用改进型负荷密度指标法,实现对考虑时序的配电网传统日负荷的预测。以某规划区为例,预测结果表明:屋顶分布式光伏和电动汽车V2G对配电网空间负荷预测结果影响较大,且对不同小区负荷影响的程度不同。

Space load forecasting of distribution network considering distributed PV and electric vehicle access

Aiming at the problem of large-scale distributed photovoltaic and electric vehicle access distribution network impacting spatial load forecasting, this paper proposes a spatial load forecasting method for urban distribution network with large-scale electric vehicles participating in V2G considering the long-term roof distributed photovoltaic saturation installation and large-scale electric vehicles. It differentiates different communities, calculates the saturated installation area of the roof photovoltaic according to the corresponding floor area ratio and availability coefficient, and calculates the output of the photovoltaic by combining the historical radiation value data. Based on the improved parking generation rate model to predict the parking demand, and combined with the daily driving mileage, parking characteristics and charging and discharging strategy, the V2G load forecasting model of electric vehicle is established, and the Monte Carlo simulation is used to obtain the spatial and temporal distribution of V2G load. The improved load density index method is used to predict the traditional daily load of the distribution network considering the timing. Taking a planning area as an example, the prediction results show that the roof distributed PV and electric vehicle V2G have a great influence on the spatial load forecasting results of the distribution network, and the degree of impact on the load of different communities is different. This work is supported by National Natural Science Foundation of China (No. 51577058).