The influence of geodata and regional economics on energy modelling
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To shift energy supply from centralized fossil fuel-based of today to decentralized, environmentally friendly, renewable energy-based an energy transition is required. One of the issues that needs to be addressed to enable this transition is to make accurate and reliable information available to consumers and producers, containing both detailed models as well as detailed data. The aim of this study is to investigate the influence of the use of geodata and the neighbourhood scale on the accuracy of energy modelling (modelling of the energy potential, economic evaluation and CO2-reduction potential) compared to individual household-scale modelling using average data, for the case study Amsterdam Nieuw-West in the Netherlands. Firstly, the energy potential for the case study has been modelled for three scenarios; first using only national averages, second using geodata, and third using both geodata and the neighbourhood approach. Secondly, an economic analysis has been done for all three scenarios. Finally, the avoided CO2-emissions that is expected after implementing the renewable energy solutions has been modelled for all three scenarios. A significant difference between the three scenarios can be observed. By comparing scenario 1 and 2 it can be concluded that the use of geographic data has a significant influence of the results of energy potential, economic and emission models. For instance, the insulation potential in scenario 2 is 33% less than in scenario 1. Furthermore, the neighbourhood approach also has a similar impact on these models, as can be concluded from comparing scenario 2 and 3. For instance, the photovoltaic potential in scenario 3 is 70% more than in scenario 3. Yet, which of these three scenarios is the most accurate can only be determined by researching the actual energy potential in the case study.