Energy Generation

Predict solar panel soiling and optimizing wash schedule for solar farms

Predict solar farm soiling loss at any location in the US using Fracsun's soiling loss database and the App Orchid platform to incorporate historical weather patterns, particulate matter and other data sources.

95 % accurate

Soiling Prediction

Upto 50% savings

On costs associated with washing solar panels.

Soiling loss globally costs 3 to 5 billion dollars of lost revenue every year according to the IEA-PVPS. Fracsun has developed the industry's most accurate and reliable soiling loss monitoring station as well as 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 its years of experience collecting and analyzing soiling loss data in over 22 countries, the team is now setting its sights on utilizing this data set to aid project development teams and banks to de-risk solar projects at the very earliest stages of conception. Learn more about Fracsun's hardware and software solutions at

Fracsun's soiling stations empower solar operators to clean on a financially optimized schedule, only doing so when absolutely necessary. Measuring soiling loss was something that evaded the solar industry for years. Fracsun's soiling station enabled both quantifying this loss value while launching a global database for the solar industry. The Fracsun database is now collecting data on over 7GW of solar assets in 22 countries. Utilizing this data in the planning stages of a project will enable more accurate production modeling and O&M budget planning, removing a major component of uncertainty in project bankability.


The new product developed by Fracsun leveraging the App Orchid platform will enable users to predict soiling loss with a simple query to the database. Utilizing the Fracsun soiling loss database integrated with AO's Knowledge Graphs and Data Fabric to incorporate historical weather patterns, particulate matter and other sources of relevant data, all in conjunction with the powerful App Orchid AI platform, the team is building a probabilistic modeling and decision engine that can predict soiling loss at any location in the US.


  • Project Developers will find this tool useful when running production reports to determine a modeled plant's expected soiling loss. Eliminating this unknown upfront in the development phase will ensure projects hit production targets.
  • O&M teams will utilize Fracsun's new AI tool to better understand operating costs, improve scheduling with vendors to minimize unforeseen conflicts and to generate optimized cleaning schedules.
  • Origination teams can even use this new product to understand regions that are best suited for development with minimal impacts due to soiling loss.