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According to the ascending worldwide energy consumption records and limitations of fossil energy sources, it is important to exploit more sustainable resources. Photovoltaic (PV) solar energy is one of the most promising renewable energy sources. Based on International Energy Agency (IEA) analysis, 20–25% of the world electricity supply will be PV-based by 2050. Generating electricity from PV panels installed on buildings’ surfaces provides safe and silent options for onsite distributed power generation, and reduces energy transmission losses. Regarding the high volume of buildings in the urban area, a primary step for implementing a PV system is assessing the solar radiation potential on the building’s surfaces and excluding the unfeasible surfaces for harvesting the solar power considering the shadow effects and obstructions. A detailed and updated geometry model of the building is another important requirement. Various studies investigated the usage of light detection and ranging (LiDAR) technology to evaluate solar potential on rooftops and facades. However, these studies did not fully capture small objects on rooftops, such as chimneys, dormers, and air conditioning systems. In addition, architectural details of building facades (e.g., windows and balconies) are mostly ignored. On the other hand, building information models (BIM) provide valuable data about the design of buildings. Combining the captured point cloud with BIM is a complementary approach to improve the building model. Considering the obtained information about the buildings, this study is going to develop the optimization module at two levels. First, optimizing PV panels’ location on buildings’ surfaces to maximize solar radiation, and then optimizing the size, number, and layout of the PV panels to maximize the panel capacity and to achieve the maximum energy generation.
Salimzadeh et al. (2017) studied this question.