GIS based Model to optimize possible self sustaining regions in the context of a renewable energy supply

During the last years an increasing energy demand, rising prices for fossil fuels, the challenge of meeting the objectives of the Kyoto protocol as well as a certain uncertainty of energy supply resulted in the two main aspects arising within the design of our future energy system, which are sustainability and security of supply. To meet these challenges, the paper presents a modelling approach that handles information on geographically disaggregated data of renewable energy potentials as well as geographically disaggregated information on energy demand structures. The comparison of the identified energy potentials of the modelling process to the relative energy consumption structure results in a “balance grid” that represents the energy excess or shortage in every cell of the grid. The balance grid is the basis for modelling self-sustaining regions and allows a differentiated geographical consideration of energy production and consumption potentials. Processing this information the model approach identifies optimized energy flows to balance all energy demand hot spots. This is applied for a special region of interest with the objective of finding one optimized setup for the whole prospected area. The final outcome of the model shows an ideally balanced energy flow structure for the whole examined region. In its simplest realization the energy flows only consider balanced flows for a full year timescale. Nevertheless these flows could also be treated on an arbitrary different timescale. Based on these outcomes a possible sub-regionalisation in terms of energetic independency within the considered region of interest can be identified. This is reflected by clustering the region of interest into single self sustaining sub regions. The model itself is a linear optimization model realised in the modelling language GAMS. There is an interface implemented to connect the model to common GIS software. In the current model all input and result data are administrated and visualised in ArcGIS.