Power system spatial analysis and visualization using geographic information system (GIS)

A framework for regional smart energy planning using volunteered geographic information

“…On the other hand, a big challenge in many GIS applications is how much data can be visualized at once without overloading the web application. The simulation of transmission lines may not be an issue for current GIS software (Abdulrahman and Radman, 2020). Nevertheless, for distribution grids, the energy paths are quite detailed, because the structure of the grid goes from building to building.…”

“…Due to the absence of real data on distribution grids, there is a need to try different routing algorithms to determine which is the most realistic one, and to deliver reliable results that may or may not be applied to real grid data. This should be possible as the use of GIS for the modeling and simulation of different aspects of energy systems is widespread (Alhamwi et al, 2017). Nevertheless, from the knowledge of the authors, current open-source tools for energy system simulation and optimization are not entirely integrated into GIS.…”

“…OSM data can be downloaded from the OSM database, or another al-ternative is to involve a smaller data set size to download an extract for a specific country or region using Geofabrik. Alhamwi et al (2017) already showed that the quality and availability of OSM data are sufficient for scientific requirements and comparable to commercial geodata (Alhamwi et al, 2017, p. 5). The advantage of using OSM data compared to commercial geodata and other collaborative mapping platforms is that OSM is a completely free open-source database available to everyone (Valdes et al, 2018).…”

“…Following the prevalidation data approach of Valdes et al (2018) and Alhamwi (2017), to identify the location of different electricity consumers, OSM data are enriched and processed together with local energy consumption statistics to establish annual consumption profiles on an hourly basis for each of the locations. Figure 2 shows how the number of OSM data decreases by about 30 000 after the prevalidation methodology of Valdes et al (2018) in a case study in Lower Bavaria.…”

“…Based on previous applications and following Schiefelbein et al (2019) and Alhamwi et al (2017), this paper presents an approach to the planning of smart energy systems from a GIS perspective that emphasizes the geographical dimension of the task. The main objective of our approach is to design electricity networks with the simulation of multiple energy systems.…”