SmartHelio, a Switzerland-based solar software developer, is launching its artificial intelligence (AI) powered Suite, which can achieve up to 98.5% accuracy in Global Horizontal Irradiance (GHI)/wind resources forecasting and 95% in failure prediction, de-risking solar investments for both future photovoltaic (PV) plants and brownfield acquisitions.
The Suite includes SmartHelio’s predictive Autopilot solution, which delivers predictive analytics capabilities, and the Climate Risk Assessment (CRA) tool, which leverages meteorological data and climatic events to help investors and solar plant owners make informed investment decisions.
Customers using SmartHelio’s AI-powered Suite can see how climate change will impact the future performance of their PV plants and how they can take future evolutions into account in today’s decisions. The solution includes a sophisticated component selection feature, allowing operators flexibility in choosing their solutions to ensure the most effective components are used for solar installations, ensuring compatibility, safety, and cost-efficiency. By optimizing resource allocation, SmartHelio’s solution helps operators reduce costs and improve overall system performance without relying on a single solution or provider.
SmartHelio will unveil its AI-powered Suite at RE+ 2024, taking place September 9-12 in Anaheim, California.
“The management of PV plants is fraught with inefficiencies, primarily due to fragmented data and outdated reporting methods that delay decision-making and expose investors to significant financial risks. Addressing these challenges is crucial for improving performance and profitability in the industry,” said Govinda Upadhyay, CEO of SmartHelio. “Many tools offer market performance enhancements, but plants using SmartHelio’s AI-powered solution have seen as much as a sixfold return on investment.”
The CRA tool integrates socio-economic data such as urbanization trends (deforestation and aerosol concentration) and other microclimatic factors. It forecasts solar irradiance and wind speed for a given solar farm by processing over 100 variables, including historical and real-time weather data and forecasts, local environmental factors like proximity to a lake, ocean, desert, or mountain, global climatic indices like El Nino/La Nina, dipoles, or air, land, and ocean temperature increases, and human factors like pollution and urbanization for a particular area.
The Autopilot platform provides recommendations for future development and for operating the plants at the highest capacity with the lowest costs, enabling operators and owners to prevent downtime and reduce costs of operations/replacement by 80%.
This content is protected by copyright and may not be reused. If you want to cooperate with us and would like to reuse some of our content, please contact: editors@pv-magazine.com.
By submitting this form you agree to pv magazine using your data for the purposes of publishing your comment.
Your personal data will only be disclosed or otherwise transmitted to third parties for the purposes of spam filtering or if this is necessary for technical maintenance of the website. Any other transfer to third parties will not take place unless this is justified on the basis of applicable data protection regulations or if pv magazine is legally obliged to do so.
You may revoke this consent at any time with effect for the future, in which case your personal data will be deleted immediately. Otherwise, your data will be deleted if pv magazine has processed your request or the purpose of data storage is fulfilled.
Further information on data privacy can be found in our Data Protection Policy.