In this article, a methodology based in Voronoi decomposition is proposed to spatially aggregate small-scale solar generation. The locations of relevant electrical infrastructure are used to manage the uncertainty on locating solar photovoltaic installations. The known coordinates of step-down high- to medium-voltage electrical substations (i.e. bulk supply points) are used to divide the territory and find multiple representative locations where solar resource can be assessed. Modelling solar photovoltaic generation from global solar radiation observations permits the estimation of power output and degradation factor due to age for the entire small-scale photovoltaic fleet. The results are validated against multiple solar installations across the region of study (Northern Ireland, UK) and show a relatively low root mean square error with monthly values ranging from 0.036 to 0.123 kW/kWp. The proposed method is scalable to larger and smaller geographical areas and transferable to other categories of solar photovoltaic installations. This methodology can serve as a basis for multiple applications, such as solar generation forecasting. System operators could utilise this method to improve knowledge of when, where and in what amount additional resources would be required to manage solar penetration in favour of a robust, low-carbon and efficient power network.

中文翻译：

---

使用Voronoi分解的小规模光伏发电的空间聚集

在本文中，提出了一种基于Voronoi分解的方法，用于空间聚集小规模的太阳能发电。相关电气基础设施的位置用于管理定位太阳能光伏设备的不确定性。降压高中压变电站（即大批供电点）的已知坐标用于划分区域并找到可以评估太阳能的多个代表性位置。根据全球太阳辐射观测结果对太阳能光伏发电进行建模，可以估算整个小型光伏发电船队的发电量和由于老化而导致的退化因子。该结果针对研究区域内的多个太阳能装置进行了验证（北爱尔兰，英国），并且显示出相对较低的均方根误差，月均值范围为0.036至0.123 kW / kWp。所提出的方法可扩展到更大和更小的地理区域，并且可转移到其他类别的太阳能光伏装置。这种方法可以作为多种应用的基础，例如太阳能发电预测。系统运营商可以利用这种方法来了解何时，何地以及以何种数量需要额外的资源来管理太阳能的渗透，从而建立一个健壮，低碳和高效的电力网络。例如太阳能发电量预测。系统运营商可以利用这种方法来了解何时，何地以及以何种数量需要额外的资源来管理太阳能的渗透，从而建立一个健壮，低碳，高效的电力网络。例如太阳能发电量预测。系统运营商可以利用这种方法来了解何时，何地以及以何种数量需要额外的资源来管理太阳能的渗透，从而建立一个健壮，低碳，高效的电力网络。