Design and implementation of a GIS calculation and investment analysis system for rooftop PV projects

Abstract

Under the goal of carbon peaking and carbon neutrality, China's energy structure is gradually transitioning from fossil energy dominated to clean energy. Solar energy is the most promising clean resource, and building rooftops are important carriers for distributed PV construction, and their quantity is directly related to the construction potential of distributed PV. Therefore, monitoring and analyzing the spatial distribution of buildings and available rooftop areas are of great value for the planning and construction of distributed PV. This study takes information of relevant rooftop PV projects as data source, these projects use deep learning technology to extract building rooftops in some countries and regions, and obtain building rooftop area after vectorization, and then calculate solar PV potential and investment potential by combining relevant PV and financial indicators. Based on the multi-layer application architecture of distributed component technology and the modular design of each function, this paper constructs a carbon-neutral building rooftop solar potential GIS calculation and investment analysis system to more accurately assess the regional renewable energy potential, provide decision support for government authorities and industry enterprises to better formulate renewable energy development indicators and planning, and help renewable energy planning to be better implemented. The system will provide decision support for government authorities and industry enterprises to better formulate renewable energy development indicators and plans, and help renewable energy planning to better implement.