Site-specific modeling, not a flat derate
Trees, adjacent structures and roof geometry get modeled against actual sun-path data for the site, replacing a generic shading percentage that either overstates or understates real production.
Services
Shading & Production Analytics
Yield modeling that accounts for real shading obstructions, so a production estimate holds up against actual site conditions.
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Shading & Production Analytics
Get shading and production analytics that model real site obstructions, not a flat derate. Engineering services for accurate solar production estimates.
Site-specific shading and production modeling
Feeds directly into string and inverter design
Shading results inform how strings get grouped and whether module-level power electronics make sense for a given roof, rather than sitting in a separate report nobody references during design.
Deliverables built for financing and warranty conversations
Production estimates come with the documentation a financing partner or a performance-guarantee conversation actually asks for.
Production numbers and string design that hold
Quote a production number that holds up
Modeled shading data replaces a generic derate, so year-one production estimates match what the system actually delivers.
Design strings around real shading patterns
String grouping and MLPE decisions get made with actual shading data, not a guess.
FAQs
Why does a flat shading derate underestimate or overestimate real production?
A flat derate applies one loss percentage across the whole array, but real shading is uneven, it changes by hour and season and hits specific rows and modules differently. That can overstate output where a fixed derate is too generous, or understate it where obstructions are minor. Site-specific modeling captures the actual pattern, which is why it holds up against measured production far better.
What tools are used to model site-specific shading?
Site-specific shading is modeled with tools that build a 3D representation of the array and surrounding obstructions and simulate the sun's path across the year, using inputs from a site survey, drone or lidar capture, or on-site horizon measurements. Common industry platforms handle the yield simulation from that geometry. The output is an hourly production estimate that reflects real obstructions rather than an assumed loss.
Does shading analysis affect string design and inverter sizing?
Yes, and that is much of its value. Knowing which modules shade and when guides how strings are grouped, whether module-level electronics help, and how the array is sized to the inverter's MPPT windows. Feeding real shading patterns into the electrical design reduces mismatch losses and produces a system that performs closer to the modeled number.