Renewable Grid Siting Insight
Open-source platform for mapping wind and solar siting constraints, helping developers and public agencies quickly identify viable renewable energy sites.
The Problem
“Renewable site selection is slowed by fragmented geospatial constraints and inconsistent screening methods”
Organizations face these key challenges:
Constraint data is spread across many agencies and formats
Manual GIS overlay workflows are slow and hard to maintain
Different teams apply different exclusion rules and buffers
Policy and permitting constraints are buried in unstructured documents
Impact When Solved
The Shift
Human Does
- •Collect constraint datasets from agencies and public sources
- •Normalize map layers and apply exclusion and buffer rules
- •Review static maps and compare candidate areas manually
- •Interpret permitting and policy documents for siting constraints
Automation
- •No meaningful AI support in the legacy workflow
Human Does
- •Set screening objectives, rule thresholds, and jurisdiction priorities
- •Review AI-generated constraint interpretations and approve rule sets
- •Resolve exceptions, disputed data, and community-sensitive cases
AI Handles
- •Ingest, classify, and standardize geospatial constraint datasets
- •Extract siting constraints from policy and permitting documents with citations
- •Detect stale, inconsistent, or low-quality layers and flag issues
- •Generate suitability maps, ranked candidate areas, and scenario comparisons
Operating Intelligence
How it works
AI runs the first three steps autonomously.
Humans own every decision.
The system gets smarter each cycle.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Assemble Context
Step 2
Analyze
Step 3
Recommend
Step 4
Human Decision
Step 5
Execute
Step 6
Feedback
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.
The Loop
6 steps
Assemble Context
Combine the relevant records, signals, and constraints.
Analyze
Evaluate options, risk, and likely outcomes.
Recommend
Present a ranked recommendation with supporting rationale.
Human Decision
A human accepts, edits, or rejects the recommendation.
Authority gates · 1
The system must not approve final candidate areas without review by a renewable development planner or public agency siting reviewer [S1].
Why this step is human
The decision carries real-world consequences that require professional judgment and accountability.
Execute
Carry out the approved action in the operating workflow.
Feedback
Outcome data improves future recommendations.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in Renewable Grid Siting Insight implementations:
Key Players
Companies actively working on Renewable Grid Siting Insight solutions: