PVmCharge

One obstacle to the electrification of private transport is the limited number of charging points in public spaces, particularly for people without a private parking space. One option is to use integrated photovoltaic systems directly to charge electric vehicles. This can be achieved through vehicle-integrated photovoltaics or through integrated photovoltaics in public car parks.

As part of the PVmCharge project, a forecasting tool is to be developed that can precisely predict irradiation conditions for any public car park. Two time horizons are targeted: on the one hand, daily forecasts to optimise the choice of individual parking spaces for vehicles with integrated photovoltaics. On the other hand, long-term yield forecasts for car park locations will be developed. This will create a suitable basis for investment decisions by companies and local authorities regarding urban photovoltaics, as well as for yield estimates for the concept of mobile photovoltaic-powered charging stations.

Using existing data (e.g. weather data, building layout, topography), the irradiation conditions, including potential moving shadows, are to be calculated for any car park location. This is carried out using AI methods, in particular fuzzy classification, which also processes fuzzy input variables. Furthermore, measurements of irradiance, radiation homogeneity and shadow movement are to be carried out at selected car parks in the Central German region; the results will serve as a supplementary database and to validate the chosen approach.