Articles | Volume 54
https://doi.org/10.5194/adgeo-54-179-2020
https://doi.org/10.5194/adgeo-54-179-2020
10 Dec 2020
 | 10 Dec 2020

A framework for regional smart energy planning using volunteered geographic information

Javier Valdes, Sebastian Wöllmann, Andreas Weber, Grégoire Klaus, Christina Sigl, Matthias Prem, Robert Bauer, and Roland Zink

Cited articles

Abbasabadi, N. and Ashayeri, M.: Urban energy use modeling methods and tools: A review and an outlook, Build. Environ., 161, 106270, https://doi.org/10.1016/j.buildenv.2019.106270, 2019. 
Abdulrahman, I. and Radman, G.: Power system spatial analysis and visualization using geographic information system (GIS), Spat. Inf. Res., 28, 101–112, https://doi.org/10.1007/s41324-019-00276-y, 2020. 
Alhamwi, A., Medjroubi, W., Vogt, T., and Agert, C.: GIS-based urban energy systems models and tools: Introducing a model for the optimisation of flexibilisation technologies in urban areas, Appl. Energ., 191, 1–9, https://doi.org/10.1016/j.apenergy.2017.01.048, 2017. 
Alhamwi, A., Medjroubi, W., Vogt, T., and Agert, C: Development of a GIS-based platform for the allocation and optimisation of distributed storage in urban energy systems, Appl. Energ., 251, 113360, https://doi.org/10.1016/j.apenergy.2019.113360, 2019. 
Amme, J., Pleßmann, G., Buhler, J., Hulk, L., Kotter, E., and Schwaegerl, P.: The eGo grid model: An open-source and open-data based synthetic medium-voltage grid model for distribution power supply systems, J. Phys. Conf. Ser., 977, 012007, https://doi.org/10.1016/j.ejor.2018.01.036, 2018. 
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Short summary
This study presents a framework for regional smart energy planning for the optimal location and sizing of small hybrid systems. By using an optimization model – in combination with weather data – various local energy systems are simulated using the Calliope and PyPSA energy system simulation tools. The optimization and simulation models are fed with GIS data from different volunteered geographic information projects, including OpenStreetMap.