Spatially resolved generation profiles for building, land and water-bound PV: a case study of four Dutch energy transition scenarios

Alongside a transition from steerable and centralized traditional electricity generation to intermittent and more decentralized renewable electricity generation from solar panels and wind turbines, Dutch energy transition scenarios project a widespread deployment of heat pumps and electric vehicles towards 2050. While clearly contributing to the decarbonization of the Dutch energy system, these developments impose challenges regarding electricity supply-demand mismatch and grid congestion. Spatially resolved electricity demand and supply profiles are required to gain a better insight into where and when such problems are likely to occur within the different scenarios. The present paper focuses on Dutch solar energy supply and features the construction of geodatabases of scenario-specific, spatially resolved electricity generation profiles for building, land and water-bound PV. Country-level PV capacities are geographically distributed based on spatial variance in roof PV potential and availability of suitable land and water use areas. Corresponding electricity generation profiles are constructed using historical meteorological measurements, a diffuse fraction model and a anisotropic transposition model. Empirically found performance ratio profiles are applied to account for a multitude of performance loss factors, including shading, dust and inverter efficiency. In 2050, building-bound capacity is projected to show only limited overlap with both land-bound and water-bound PV capacity. On the other hand, regions with considerable water-bound PV capacity also tend to show considerable land-bound PV capacity. Compared to the present-day situation, yearly country-level PV electricity generation is projected to be a factor 18.5, 15.7, or 7.7 higher in 2050 when respectively following the Regional, National or International Steering scenarios

Urban environment and solar PV performance : The case of the Netherlands

The modern urban landscape creates numerous challenges for the deployment of solar Photovoltaic (PV) technology. The large structures that dominate the skyline of every city create compactness, which, in turn, limits the available rooftop area and creates unpredicted shading patterns. The majority of research today relies on modern applications such as geographical information system (GIS) software to evaluate urban morphology; however, this approach is computationally intensive and therefore it is usually limited to a small geographical area. In this paper, we approach this issue from another perspective, utilizing the enormous amount of high resolution PV yield data that is available for the Netherlands. Our results not only correlate performance losses with urban compactness indicators, but they also reveal a significant seasonality effect that can reach 15% in some cases

Urban environment and solar PV performance : The case of the Netherlands

The modern urban landscape creates numerous challenges for the deployment of solar Photovoltaic (PV) technology. The large structures that dominate the skyline of every city create compactness, which, in turn, limits the available rooftop area and creates unpredicted shading patterns. The majority of research today relies on modern applications such as geographical information system (GIS) software to evaluate urban morphology; however, this approach is computationally intensive and therefore it is usually limited to a small geographical area. In this paper, we approach this issue from another perspective, utilizing the enormous amount of high resolution PV yield data that is available for the Netherlands. Our results not only correlate performance losses with urban compactness indicators, but they also reveal a significant seasonality effect that can reach 15% in some cases

Urban environment and solar PV performance: The case of the Netherlands

The modern urban landscape creates numerous challenges for the deployment of solar Photovoltaic (PV) technology. The large structures that dominate the skyline of every city create compactness, which, in turn, limits the available rooftop area and creates unpredicted shading patterns. The majority of research today relies on modern applications such as geographical information system (GIS) software to evaluate urban morphology; however, this approach is computationally intensive and therefore it is usually limited to a small geographical area. In this paper, we approach this issue from another perspective, utilizing the enormous amount of high resolution PV yield data that is available for the Netherlands. Our results not only correlate performance losses with urban compactness indicators, but they also reveal a significant seasonality effect that can reach 15% in some cases