Wind Farm Micrositing & Layout Optimizer
Optimize turbine placement to maximize wind farm energy yield and minimize losses
What You Can Do
You can model how turbine positioning affects wake losses, capacity factor, and annual energy production (AEP) across your site. Claude helps you incorporate terrain complexity, prevailing wind direction, no-go zones, and spacing constraints into defensible micrositing recommendations that balance energy yield against environmental and regulatory requirements.
Features
Calculate wind speed deficits and energy penalties from turbine-to-turbine wake interactions based on spacing and prevailing wind direction
Model how ridge lines, valleys, and topographic features affect wind acceleration and optimal turbine positioning
Automatically incorporate no-go zones (wetlands, bird migration routes, property boundaries) into layout generation
Compare competing layout options and quantify AEP improvements from alternative micrositing strategies
Evaluate fixed vs. floating platform spacing constraints and seabed bathymetry impacts on turbine positioning
Generate micrositing justification reports with assumptions, trade-off analysis, and stakeholder-ready technical narratives
Apply industry spacing guidelines (typically 3–5 rotor diameters perpendicular to wind, 8–10 parallel) and flag constraint violations
Model how layout adjustments to protect sensitive habitats or minimize bird/bat risk affect energy yield
Example Output
Example 1: Greenfield Layout Optimization
Input: 2×2 km site with 10 m/s mean wind speed from NW, wetland exclusion zone, property setback requirements
Output:
- Recommended 12-turbine layout with 3.5 MW units positioned to avoid wake alignment
- Wake loss estimate: 8.2% (vs. 15.1% for grid pattern alternative)
- AEP improvement: +47 GWh/year (6.3% higher capacity factor)
- Constraint compliance: All turbines >500 m from wetlands, >100 m from property lines
Example 2: Offshore Platform Spacing
Input: Floating platform layout, 400 m water depth, 100 MW capacity, monopile foundation conflicts
Output:
- 25-turbine offshore grid with 600 m spacing (NW-SE alignment with dominant wind)
- Platform availability: 97% (reduced maintenance conflicts)
- Wake-adjusted capacity factor: 42.3% (vs. 38% for denser spacing)
- Foundation drive-time analysis: 14 days faster installation vs. compact layout
Example 3: Environmental Mitigation Layout
Input: Raptor migration corridor, spring flight path restrictions, 50 MW site
- Alternative A (12 turbines, standard spacing): 3 turbines in high-risk zone, AEP 185 GWh
- Alternative B (11 turbines, staggered rows): 0 turbines in high-risk zone, AEP 178 GWh
- Trade-off: 3.9% AEP reduction vs. eliminated avian collision risk
What's Included
- SKILL.md: Complete wind farm micrositing methodology and decision framework
- Site Data Template: Spreadsheet for inputting terrain elevation, wind speed profiles, and constraint boundaries
- Wake Loss Calculator: Reference formulae and Python snippet for Jensen/Larsen wake models
- Layout Checklist: Pre-design validation steps (wind rose analysis, exclusion zone mapping, spacing compliance)
- Micrositing Report Outline: Technical narrative structure for permitting authorities and stakeholder review
Who It's For
- Wind Farm Engineers — Micrositing and layout design for onshore and offshore projects
- Renewable Energy Developers — Feasibility and pre-design analysis for utility-scale projects
- Environmental Consultants — Trade-off analysis between energy yield and habitat protection
- Permitting/Regulatory Specialists — Documentation of layout decisions and constraint compliance
- Energy Modeling Analysts — Capacity factor forecasting and AEP optimization support
Best For
- Greenfield wind site layout concept development (pre-feasibility through detailed design)
- Wake loss modeling and turbine spacing optimization based on terrain and wind direction
- Environmental constraint mapping (no-go zones, bird/bat mitigation corridors)
- Capacity factor comparison between competing layout alternatives
- Permitting documentation and stakeholder justification of micrositing decisions
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