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PVFARM

AI-powered solar farm design platform

Web-based AI platform for utility-scale solar design that automates layout generation, electrical, civil, and energy analysis. Handles projects up to 800MW DC with real-time multidisciplinary analysis.

Pricing
contact the vendor
Alternatives
Raven, Delve by Sidewalk Labs, TestFit
Who it's for
Civil Engineering
Not publicly specified raisedGrowth Stage
Founded 2021 · Not publicly specified (webinar case studies available on website)
Website → ← All Tools
WHY IT EXISTS

Why This Tool Exists

The Problem

Solar EPC teams spend weeks manually designing layouts, running electrical simulations, and civil analyses separately. Engineers evaluate 100+ layout options manually, delaying project timelines and increasing labor costs.

The Solution

PVFARM automates layout generation with AI algorithms that optimize for energy production and equipment constraints. Real-time integration of electrical, civil, and energy analysis allows teams to test multiple design iterations and optimize projects 10-20x faster.

USAGE

How You Use It

Delivery Method
SaaS
Integrations
Google EarthAWSPVsyst
Disciplines
Civil Engineering
Workflows
Data & Automation
Project Phases
Schematic Design, Design Development, Construction Documentation
Project Types
Infrastructure, Industrial
TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Site boundary/geometry, Project parameters
Optional:Custom PV modules, Custom inverters, 2D CAD drawings, PAN and OND files, Meteo data files
Formats:PAN files, OND files, DWG (2D CAD), Meteo files, Custom equipment specs
Output
What you get
Format:Optimized solar farm design with multidisciplinary analysis
Fields:Layout geometry with tracker placement, Energy production estimates (accounting for shading, bifaciality, irradiance), Electrical configuration (inverter sizing, string sizing), Civil engineering recommendations (grading, drainage), Equipment specifications and costs, Performance comparisons across design iterations
Algorithm
How it works
Model:Proprietary terrain-following optimization algorithm (specific ML techniques not publicly disclosed)
Accuracy:Not publicly specified
Privacy
How your data is protected
Retention:Project data retained as long as necessary for project delivery (specific duration not publicly specified)
Training:Not explicitly stated (not used for AI model training based on privacy policy review)
Compliance:GDPR compliant (rights to access, deletion, rectification available)
API
Integration
Endpoint:Contact vendor for API access
Method:Not publicly documented
USE CASES

Use Cases

  • ·Rapid utility-scale solar farm layout optimization
  • ·Multidisciplinary design evaluation (electrical, civil, energy)
  • ·Energy production forecasting and performance modeling
  • ·Equipment selection and integration for solar plants
  • ·Design iteration and what-if analysis for capital efficiency
PRICING

Pricing

Free
7-day trial with expert training sessions
Pro
Annual license (custom pricing by discipline: Layout Modelling, Civil, Energy, Repower, Electrical)
Enterprise
Contact for enterprise pricing
Sources & Research NotesResearch date: 2026-02-01
Data Sources (7)
Fields Checked (13)
problem, solution, deliveryMethod, integrations, disciplines, projectPhases, projectTypes, yearFounded, maturityStage, use-cases, input-output-specs, control-features, pricing-model
Not Found (9)
funding-amount, customer-names-and-count, soc2-compliance, api-documentation, algorithm-specifics, accuracy-metrics, data-training-policy, webhook-support, rate-limits
About this research: This record summarizes the cited sources and fields checked. A research date does not establish hands-on testing. Consult the original sources for current details and limitations.
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