A team of solar energy experts from India’s Manipal Institute of Technology and Quantum Research and Centre of Excellence is leveraging advanced computing and historical meteorological data to enhance solar farm site assessments. Their research, published in Nature, employs machine learning to simulate weather patterns and predict solar irradiance, delivering precise energy estimates and financial viability. This innovative approach is crucial as solar energy adoption increases globally, amidst rising electricity demand and the shift from fossil fuels. Notable case studies from the Philippines and Mongolia highlight regional opportunities and challenges in solar energy production. The research emphasizes that traditional planning methods may overlook significant long-term climate impacts. Additionally, advancements like bifacial solar panels and real-time data analytics could optimize performance further. This study points towards a sustainable, solar-driven future, where strategic data use can transform global energy landscapes. For homeowners, solar solutions can reduce bills significantly, with various financial options available.
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