Abstract
In the face of the broad political call for an “energy turnaround”, we are currently witnessing three essential trends with regard to energy infrastructure planning, energy generation and storage: from planned production towards fluctuating production on the basis of renewable energy sources, from centralized generation towards decentralized generation and from expensive energy carriers towards cost-free energy carriers. These changes necessitate considerable modifications of the energy infrastructure. Even though most of these modifications are inherently motivated by geospatial questions and challenges, the integration of energy system models and Geographic Information Systems (GIS) is still in its infancy. This paper analyzes the shortcomings of previous approaches in using GIS in renewable energy-related projects, extracts distinct challenges from these previous efforts and, finally, defines a set of core future research avenues for GIS-based energy infrastructure planning with a focus on the use of renewable energy. These future research avenues comprise the availability base data and their “geospatial awareness”, the development of a generic and unified data model, the usage of volunteered geographic information (VGI) and crowdsourced data in analysis processes, the integration of 3D building models and 3D data analysis, the incorporation of network topologies into GIS, the harmonization of the heterogeneous views on aggregation issues in the fields of energy and GIS, fine-grained energy demand estimation from freely-available data sources, decentralized storage facility planning, the investigation of GIS-based public participation mechanisms, the transition from purely structural to operational planning, data privacy aspects and, finally, the development of a new dynamic power market design.
Highlights
In the face of the broad political call for an ―energy turnaround‖, we are currently witnessing three essential trends with regard to energy infrastructure planning, renewable energy generation and storage: from planned production towards fluctuating production on the basis of renewable energy sources, from centralized generation towards decentralized generation and from expensive energy carriers towards cost-free renewable energy carriers [1]
We claim that it is not enough to consider space and time as additional parameters, but space and time need to be fully integrated into energy system modeling processes in order to better understand the spatio-temporal dynamics of, for instance, energy demand, availability and the effectiveness of conventional and renewable resources, capacity and load patterns of energy infrastructures, including decentralized energy storages, and, the return of investments and economic profitability
In the face of the broad political call for an ―energy turnaround‖, we are currently witnessing three essential trends with regard to energy infrastructure planning, renewable energy generation and storage: from planned production towards fluctuating production caused by renewable energy sources, from centralized generation towards decentralized generation and from expensive energy carriers towards cost-free renewable energy carriers
Summary
In the face of the broad political call for an ―energy turnaround‖, we are currently witnessing three essential trends with regard to energy infrastructure planning, renewable energy generation and storage: from planned production towards fluctuating production on the basis of renewable energy sources, from centralized generation towards decentralized generation and from expensive energy carriers towards cost-free renewable energy carriers [1]. Even though Geographic Information Systems (GIS) are slowly penetrating renewable energy research in highly specific and small-scale efforts and their potential for contributing geospatial analysis and visualization methods for awareness-building and decision support has been demonstrated in a number of projects, a broad integration of GIS and energy system models is still missing This is surprising, as the value of using GIS-based approaches for solving questions in the energy domain have been proven in a number of research projects, including renewable energy potential assessment [3,4,5,6,7], energy consumption modeling [8,9,10], planning specific energy infrastructure projects [11,12,13], building energy demand estimation [14,15,16], site planning for renewable energy power plants [17,18,19] or visual impact assessment [20,21,22,23].
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