• Energy Research

Geographic information system (GIS) based tools have become popular for solar photovoltaic (PV) potential estimations, especially in urban areas. There are readily available tools for the mapping and estimation of solar irradiation that give results with the click of a button. Although these tools capture the complexities of the urban environment, they often miss the more important atmospheric parameters that determine the irradiation and potential estimations. Therefore, validation of these models is necessary for accurate potential energy yield and capacity estimations. This paper demonstrates the calibration and validation of the solar radiation model developed by Fu and Rich, employed within ArcGIS, with a focus on the input atmospheric parameters, diffusivity and transmissivity for the Netherlands. In addition, factors affecting the model’s performance with respect to the resolution of the input data were studied. Data were calibrated using ground measurements from Royal Netherlands Meteorological Institute (KNMI) stations in the Netherlands and validated with the station data from Cabauw. The results show that the default model values of diffusivity and transmissivity lead to substantial underestimation or overestimation of solar insolation. In addition, this paper also shows that calibration can be performed at different time scales depending on the purpose and spatial resolution of the input data.

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.

This paper presents the results of the analyses of operational performance of small-sized residential PV systems, connected to the grid, in the Netherlands and some other European countries over three consecutive years. Web scraping techniques were employed to collect detailed yield data at high time resolution (5–15 min) from a large number (31,844) of systems with 741 MWp of total capacity, delivering data continuously for at least one year. Annual system yield data was compared from small and medium-sized installations. Cartography and spatial analysis techniques in a geographic information system (GIS) were used to visualize yield and performance ratio, which greatly facilitates the assessment of performance for geographically scattered systems. Variations in yield and performance ratios over the years were observed with higher values in 2015 due to higher irradiation values. The potential of specific yield and performance maps lies in the updating of monitoring databases, quality control of data, and availability of irradiation data. The automatic generation of performance maps could be a trend in future mapping.

To raise awareness on the importance of monitoring photovoltaic (PV) systems in the Netherlands, a public campaign was organised in three consecutive years. During 1 week in the spring of 2014, 2015, and 2016, as part of the Dutch Solar Days, participants were asked to measure or determine the amount of energy generated by their PV systems. All in all over 8000 participants were recruited via social media and a national television show. This study analyses the variation of weekly yield and performance ratio (PR) of the systems of the participants for 3 years. On average, for each year, a PR was found of 0.74 with a left-skewed distribution, indicating that most systems perform well. Further analysis was made, which showed the ineffectiveness of an undersized inverter in low radiation conditions. It was also found that the performance difference between mono- and multicrystalline silicon panels was small, and that micro-inverters are effective in reaching high performance for PV systems that suffer from shading. Generally, this work demonstrated the usefulness of citizen science approaches in PV system performance analysis.

The Postal Code Rose policy is part of the 2013 Dutch Energy Agreement of the Social and Economic Council of the Netherlands, introduced to support sustainable energy growth. This paper presents a case of the Dutch Postal code Rose policy by developing a method combining geographical information systems (GIS) and multicriteria decision analysis (MCDA), which allows determining the solar photovoltaic potential when fully applying this policy. As case study, the city of Apeldoorn in the Gelderland province of the Netherlands was selected. The research evaluates the technical potential of the city and then applies it to the Postal code Rose framework by using social criteria. The social criteria comprise of the most important factors that play a role in the adoption of solar PV. The results showed that by fully applying the Post Code Rose policy ~77% of the total electricity demand of Apeldoorn could be covered by solar PV.