Govinda Upadhyay
About Govinda Upadhyay
Govinda Upadhyay is the CEO and Co-Founder of SmartHelio, a company dedicated to enhancing the sustainability of solar assets through advanced technology and research.
Govinda Upadhyay CEO & Co-Founder
Govinda Upadhyay is the CEO and Co-Founder of SmartHelio, a company dedicated to making solar assets truly sustainable by enhancing their lifespan and reducing operational costs. He co-founded SmartHelio with the vision of integrating advanced technologies to optimize solar energy systems globally.
Govinda Upadhyay Education and Expertise
Govinda Upadhyay holds a background in physics and climate change research. His expertise includes leveraging physics-informed AI models to address the predictive limitations of traditional AI and physics-based approaches. His work innovatively combines physical principles with machine learning to deliver accurate analyses with minimal data requirements.
SmartHelio and Renewable Energy Initiatives
Govinda Upadhyay co-founded SmartHelio to drive sustainability in solar energy by increasing asset lifespan and reducing operational costs. SmartHelio's advanced pattern recognition technology emerged from 15 years of Swiss R&D. Their algorithms have been successfully tested and validated on real solar PV data sets. SmartHelio empowers solar installations to digitalize and automate operations, ensuring efficient energy production.
Climate Risk Assessment and Forecasting Tools
One of Govinda Upadhyay's notable contributions is the development of a Climate Risk Assessment tool that forecasts long-term solar GHI and wind speed using over 100 variables. SmartHelio employs advanced deep/machine learning algorithms to provide comprehensive solar irradiance forecasts globally, achieving over 98% accuracy by analyzing historical GHI data and considering factors like climate change, microclimate attributes, and human factors.
Govinda Upadhyay's Expertise in Fault Detection and Solar Engineering
Govinda Upadhyay has significant experience in solar engineering and asset management. He has developed physics-based fault detection algorithms that benefit from decades of R&D and field experience in solar energy systems. His work integrates AI/ML for precise and rapid fault diagnosis, identifying fault patterns in voltage, current, and temperature data, which enhances the efficiency of solar installations.