Allocation of annual electricity consumption and power generation capacities across multiple voltage levels in a high spatial resolution
Allocation of annual electricity consumption and power generation capacities across multiple voltage levels in a high spatial resolution
复制标题
以高空间分辨率分配多个电压等级的年用电量和发电量
DOI：
--
复制
发表时间：
2017
期刊：
影响因子：
--
通讯作者：
E. Kötter
中科院分区：
文献类型：
--
作者：
L. Hülk;Lukas Wienholt;Ilka Cussmann;U. Müller;C. Matke;E. Kötter
电力系统正处于转型期。可再生能源发电的不断扩大，导致电网不同电压水平的能量流动在空间和时间上发生变化。在消费方面，预计需求模式将发生变化。高空间分辨率数据的有限性阻碍了独立和透明的评估。有鉴于此，open_eGo研究项目正在开发以电网和开放科学原则为重点的方法。在这项工作中，电力需求和发电量分配到相应的电压等级和网络节点。通过将城市边界数据与Voronoi单元相结合，我们为每个变电站创建了集水区。在需求方面，OpenStreetMap数据用于绘制不同需求部门的地图。我们表明，一个一致的数据集，可以在一个高的空间分辨率，使用地理数据处理。我们的研究结果适用于德国，但该方法可以采用到其他国家或地区，有足够的开放数据。
The electrical energy system is in transition. There is continuing expansion of renewable generation, which causes a spatial and temporal shift of energy flows at different voltage levels of the power grid. On the consumption side, demand patterns are expected to change. The limited availability of data with high spatial resolution hinders independent and transparent assessments. In view of this, the research project open_eGo is developing methods focusing on electricity networks and open-science principles. In this work, electricity demand and power generation are allocated to their corresponding voltage levels and network nodes. By combining data on municipal boundaries with Voronoi cells we created catchment areas for each substation. On the demand side, OpenStreetMap data is used for mapping different demand sectors. We show that a consistent data set can be produced in a high spatial resolution using geographical data processing. Our results apply to Germany but the methodology can be adopted to other countries or regions where sufficient open data is available.
影响因子：
9
作者：
Schaber, Katrin;Steinke, Florian;Hamacher, Thomas
通讯作者：
Hamacher, Thomas