A Brazilian company that builds solar farms throughout the country improved and automated the process of identifying the best available land parcels for farm construction. An optimum land parcel is flat, with little or no wetlands, showing minimum incline, and accessible to local infrastructure.
A lot of time is spent navigating the complex data and systems involved in determining how qualified a land parcel is for a solar farm. Varied factors like solar irradiance, relief, economic aspects, local policy and flooding risk need to be considered.
RapidCanvas worked with solar farm developers to develop a viable solution.
Determine key data points and sources for parcel identification.
Create an algorithm to create ranked parcels list and an opportunity matrix for promising parcels
Update the qualification criteria used to generate qualified land parcels
Create a pipeline of qualified land parcel leads that can be quickly evaluated
Through this process, the best available parcels for solar farm construction are located and a rank-ordered list of these parcels are generated.
A Latin American renewable energy company optimized its maintenance schedules and reduced its risks and costs, extending the useful life of each turbine
A Brazilian company that builds solar farms identified the most optimum land parcels for new farm development to be evaluated quickly and efficiently.
A European telecommunications company leveraged ML to predict RLF caused by weather conditions and maintain consistent, reliable 5G service.