Spatiotemporal modelling for integrated spatial and energy planning

Abstract

The transformation of the energy system to a renewable one is crucial to enable sustainable development for mankind. The integration of high shares of renewable energy sources (RES) in the energy matrix is, however, a major challenge due to the low energy density per area unit and the stochastic temporal patterns in which RES are available. Distributed generation for energy supply becomes necessary to overcome this challenge, but it sets new pressures on the use of space. To optimize the use of space, spatial planning and energy planning have to be integrated, and suitable tools to support this integrated planning process are fundamental. Spatiotemporal modelling of RES is an emerging research field that aims at supporting and improving the planning process of energy systems with high shares of RES. This paper contributes to this field by reviewing latest developments and proposing models and tools for planning distributed energy systems for municipalities. The models provide estimations of the potentials of fluctuating RES technologies and energy demand in high spatiotemporal resolutions, and the planning tools serve to configure energy systems of multiple technologies that are customized for the local energy demand. Case studies that test the spatiotemporal models and their transferability were evaluated to determine the advantages of using these instead of merely spatial models for planning municipality-wide RES-based energy systems. Spatiotemporal models allow a more detailed estimation of RES potentials and serve to find not only optimal locations but also optimal sizes for individual RES plants. While the potential of variable RES based on yearly energy generation values can be considerably larger than the energy demand, only a fraction of it can be deployed without compromising the quality and reliability of the local energy supply system. Furthermore, when spatiotemporal models are used, it can be seen that technological diversity is beneficial for the supply quality. Similarly, the advantages and limits of the deployment of storage systems and of combinations of RES-based technologies to cover the local demand were determined and evaluated. Finally, the results from the analyses provide sufficient information to define road maps of installations deployment to achieve desired RES penetration objectives.

An integrated GIS and robust optimization framework for solar PV plant planning scenarios at utility scale

“…One common challenge when coping with spatiotemporal analysis of RE sources is the need for high computational capacities [9]. We have handled this issue by favoring a procedural approach where the GIS model reduces the search space passed on to optimization.…”

“…Scenario outputs corroborate what we previously noted about the significant constraints the territory is subject to. While the permissive strategy resulted in 133 candidates covering about 30 km 2 , intermediate and restrictive gave either few (9) or no candidates at all. In the general case, each resulting set would feed the optimization and produce as many distinct optimal solutions left at the discretion of the decision and policy makers.…”

“…Our analysis has hence focused on optimizing the distribution of those facilities throughout the territory. To be as close as possible to reality, most of the energy system models currently provide analysis at hourly time scale [9]. In this study, we have therefore followed the same pattern for simulation and optimization of the given PV facilities.…”

“…Today, strategic energy planning relies on system modeling tools with a strong growths of systems involving spatiotemporal modeling at different scales and with different objectives and study purposes [9]. In the case of identifying suitable sites for intermittent RE sources (solar, wind) parks, which we are interested in, there is a focus on local scale study approaches summarized below.…”

“…Similarly but at a municipal scale, Ramirez-Camargo and Stoeglehner [9] present a spatio-temporal GIS model for RE planning, including solar PV. Potential sites are selected based on rooftop areas also, that have been previously identified and classified according to PV usage.…”