Fracsun, a leading provider of solar soiling loss monitoring solutions, today announced the launch of its groundbreaking AI-powered soiling loss modeling tool (CLEO). This advanced solution enables the entire solar development sector to fine-tune their production models and improve energy yield assumptions.
Developed by Fracsun’s team of industry experts, the new model integrates precise local ground-based soiling loss measurements, detailed weather data, and machine learning algorithms to deliver accurate, localized simulated annual soiling losses. Unlike static, generalized approaches, this dynamic model accounts for evolving factors such as fine particulate matter (PM2.5 and PM10) concentrations, nitrate and sulfate levels, seasonal trends, and the impacts of wind and precipitation.
“Our goal is to empower solar production modelers with the tools they need to continuously improve performance modeling and maximize returns,” said [CEO name], CEO of Fracsun. “By generating a Typical Meteorological Year (TMY) for daily soiling loss data, our model provides granular, site-specific simulations of soiling losses, enabling users to refine their production models and plan future maintenance schedules accordingly.”
Fracsun’s solution builds upon its extensive network of soiling monitoring stations, deployed across 27 countries and representing over 12 GW of installed solar capacity. Through machine learning, the model continuously learns from this growing dataset, incorporating new parameters like module tilt and weather forecasts to deliver increasingly precise results.
“Soiling is a dynamic, site-specific challenge that can significantly impact solar asset performance over time,” Mattheis continued. “With the CLEO AI-powered model, our customers can now proactively manage this issue, optimizing maintenance plans and production forecasts to maximize their return on investment.”
Fracsun has developed the industry’s most accurate and reliable soiling loss monitoring station, along with the software needed to support it. This portal allows users to monitor solar assets for soiling loss and drive operational efficiency through actionable data and forecasting. Through years of experience collecting and analyzing soiling loss data, the team is now focused on utilizing this dataset to aid project development teams and banks in de-risking solar projects at the earliest stages of conception.
If you are interested in being part of Fracsun’s Beta test group for their new CLEO AI Soiling Loss Model, you will receive the following benefits:
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Early Access:
Be among the first to explore and utilize our advanced simulation tool, allowing you to gain valuable insights into the impact of soiling loss on solar energy production in your specific location.*
Run Simulations:
During the early access period, you will be able to conduct up to 5 simulations to analyze the effects of soiling on your solar energy system.*
Provide Feedback:
Your participation in the beta test will enable you to share your valuable feedback and insights, which will directly contribute to the enhancement and improvement of the FracsunAI Soiling Loss Engine.For more information, please visit the Fracsun website at [website address].
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