Solar energy developers and planners can explore how future climatic conditions will impact the performance of photovoltaic (PV) systems with an artificial intelligence (AI)-powered tool from SmartHelio. The platform includes a predictive Autopilot solution from the Switzerland-based solar software developer, which delivers predictive analytics capabilities, and a climate risk assessment (CRA) tool, which leverages meteorological data and climatic events to help solar energy developers make informed investment decisions.

The AI-powered solution provides up to 98.5% accuracy in global horizontal irradiance and wind resource forecasting, along with 95% accuracy in failure prediction. The Autopilot platform provides recommendations for future development and for operating the PV plants at the highest capacity with the lowest costs, enabling operators and owners to prevent downtime and reduce costs of operations/replacement by 80%.

The CRA component integrates socio-economic data such as urbanization trends (deforestation, aerosol concentration) and other microclimatic factors. Solar irradiance and wind speed are predicted 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.

SmartHelio maintains that users can rely on these tools to lower costs, increase efficiency and boost revenue in their solar operations to overcome inefficiencies, improve decision-making and ensure investors avoid financial risks by optimizing resource allocation. The predictive solution uses time-series data (current and voltage), even in an unstandardized format, to feed its physics-based algorithms and predict failures such as inverter downtime and tracker dysfunction.

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