Modelling City Scale Spatio-temporal Solar Energy Generation and Electric Vehicle Charging Load

This study presents a model for estimatingbuilding-applied photovoltaic (PV) energy yield and electric ve- hicle (EV) charging temporally over time and spatially on a city scale. The model enables transient assessment of the synergy between EV and PV, thus is called the EV-PV Synergy Model. Spatio-temporal data on solar irradiance is used in combination with Light Detection and Ranging (LiDAR) data to generate realistic spatio-temporal solar power generation profiles. The spatio-temporal EV charging profiles are produced with a stochastic Markov chain model trained on a large Swedish data set of travel patterns combined with OpenStreetMap (OSM) for deterministically identifying parking spaces in cities. The modelled estimates of solar power generation andEV charging are combined to determine the magnitude and correlation between PV power generation and EV charging over time on city scale for Uppsala, Sweden. Two months (January and July) were simulated to represent Sweden’s climate extremes. The EV penetration level was assumed to be 100% and all the roofs with yearly irradiation higher than 1000 kWh/m2 were assumed to have PV panels. The results showed that, even in January with the lowestsolar power generation and maximum EV load, there can be a positive net-generation (defined as the integration of PV generation minus EV charging load over time) in some locations within the city. Central locations exhibited a positive temporal correlation between EV charging load and PV generation. Negative temporal correlations were observed in the outskirts of the city, where typically night time home-charging was prevalent. In the highest PV power generation month (July) the solar generation was 16 times higher than the EV charging load. Spatially, the net-generation was positive in almost the entire city. However, the time-series correlation between the EV charging load and the PV generation reached more extreme positive and negative values in comparison with January. This was a result of the higher variability in irradiance during July in comparison with January. In summary, we find that there is a favorable synergy of EV-PV technology within the city center with assumptions of workplace charging behaviors for both winter and summer months. An unfavorable synergy with suburban areas where typically nighttime charging behaviors negatively correlate to PV generation. This suggests that distributed PV should be targeted around city center/workplace EV charging stations