Electricity system optimization models require information about the load, usually in the form of time series. Such information is available for some regions of the world on a country level and even a sub-national level (federal states, counties, or balancing areas of electric utilities). However, this data resolution might not be adequate for research questions where the desired model region is a city within the state, or an area that spans over parts of different states. In this study, we suggest an empirical method that uses GIS data to distribute the load spatially with a high resolution (15 arcsec x 15 arcsec), then aggregates it again based on the desired shape of the model regions. The method has been applied on five European countries for validation, yielding a relative error below 20% for the yearly electric load in most sub-regions.     «

Electricity system optimization models require information about the load, usually in the form of time series. Such information is available for some regions of the world on a country level and even a sub-national level (federal states, counties, or balancing areas of electric utilities). However, this data resolution might not be adequate for research questions where the desired model region is a city within the state, or an area that spans over parts of different states. In this study, we sugg...     »