Thesis Conclusion
The main goal of this thesis was to utilize the GIS approach to model the potential of solar rooftop PV in the urban area, which will support the initial process in designing a proper solar photovoltaic system. There were objectives to be fulfilled to achieve the goal of the thesis. The first objective was to identify a GIS-based algorithm to model the solar PV potential. It included the literature review and extensive research on the available algorithms. According to the literature, some algorithms are widely used in estimating solar PV potential. One of them is the r.sun module. The r.sun module was finally selected as the algorithm for the modelling process.
The study area focuses on the Morumbi district, Sao Paulo, Brazil. All datasets that used in this thesis were entirely derived from open-data sources. The first stage of the modelling process was to generate a DSM from point cloud data, then calculate solar radiation of the surface. The solar radiation is based on the r.sun module that incorporates topographic and atmospheric parameters in its algorithm. It is proved to effectively address the complicacy in identifying solar energy potential from photovoltaic installation in the study area, specifically at the building level. Unlike conducting an in-situ measurement, this model is more cost-efficient as it could cover a much larger area for prediction. Finally, the result is visualized within an integrated spatial data infrastructure.
The result provides an insight that by running a GIS-based model, the abundance of the solar PV potential in Morumbi could be identified. In regards to solar intensity, the comparison of daily average solar radiation in Morumbi is with the solar radiation value from other regions in the world with equivalent latitude could be identified. Through the result, the monthly average trends of solar radiation could also be identified. The percentage of suitable buildings for the solar PV installation is high, reaches 92% of the whole building in the study area. Additional analyses on calculating PV capacity, installation cost, CO2 emission savings, and assessment of the panel inclination adjustment impact were also carried out. The finding obtained from the assessment on the impact of the panel inclination adjustment was that seasonal trends of the sun position and topographical features such as aspect and slope was highly determined by the amount of solar radiation receives by the surface.
It can be concluded that the aim and objectives of this thesis were accomplished. The result of the model could provide the information that the GIS-based algorithm is robust for determining solar radiation in the study area . The entire modelling workflow can be applied to solve a similar task in other study areas. Nonetheless, there are still places for further enhancement in this study. To increase the prediction accuracy, the comprehensiveness of input datasets obviously determines the quality of the model output. More advanced visualization and putting more effort into the interoperability aspect of the spatial data infrastructure should also be considered to ensure the information is well-perceived by the targeted user.
