{'fraction_non_alphanumeric': 0.013980263157894737, 'fraction_numerical': 0.0, 'mean_word_length': 5.508021390374331, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Assessment of Solar Energy Generation Potential on Roof-tops using Image Processing

Favorable Indian climatic conditions have made solar energy a promising technology to meet ever-growing energy demands. However, the limited energy generated per square meter and excessive land use remain repulsive factors for deploying large solar plants in populated areas. Given land use limitations, the rooftops of elevated buildings become a convincing alternative for producing solar energy. The present research proposes an OpenCV changing colorspace technique for detecting and mapping the available area on the rooftop to install photovoltaic (PV) panels. The satellite and aerial images are used to approximate the appropriate rooftop area that can be utilized for installing the photovoltaic solar panel. The present study is carried out to assess the solar energy potential available at the rooftops of the Pandit Deendayal Energy University, situated in Raysan, Gandhinagar Gujarat. The present technique is scalable and can determine the rooftop solar energy potential at the city level. The present work’s outcome may serve as valuable input for policymakers and for investing in distributed energy infrastructures.