Renewable energy siting
Sun, wind and land as data: irradiance and wind resource, yield models, exclusion masks, terrain shading, grid distance and suitability maps.
A solar or wind resource map is the most persuasive layer in any energy study and the least decisive one. Across a 35 km region around Toledo, PV yield varies by 2.1%; the housing setback alone moves the buildable land from 907 to 311 km². The resource chooses the country and the season. The rules, the terrain and the grid choose the field.
The numbers on the way are easy to get wrong by a round factor. Irradiance is a rate and irradiation a total, and one weather endpoint returns W/m² while its daily sum comes back in MJ/m². Hourly values are labelled at the start, the middle or the end of the hour. Wind at 10 m is not wind at the hub, and energy read off the power curve at the mean speed is wrong in both directions. A buffer of 500 in a geographic CRS is 500 degrees.
The concepts below settle what irradiance, capacity factor, the wind resource, siting constraints, the horizon and power density measure; the how-to guides download real irradiance and wind, model yield, move wind to hub height, build an exclusion mask, compute horizons and grid distance, and rank sites; and the fixes are the five ways these estimates go wrong without looking wrong.
🧭 Start with the concepts
The ideas the how-to guides below assume you already have.
⚙️ Then do the task
Step-by-step walkthroughs with code you can copy and adapt.
- How to Download Solar Irradiance Data in Python
- How to Model PV Output with pvlib
- How to Find the Optimal Tilt and Orientation for Solar Panels
- How to Estimate Wind Speed at Hub Height in Python
- How to Estimate Wind Energy with a Weibull Distribution
- How to Build a Siting Exclusion Mask in Python
Show every how-to guide in this topic
- How to Compute a Horizon Profile from a DEM in Python
- How to Measure Distance to the Grid for Renewable Siting
- How to Build a Solar Suitability Map in Python
- How to Calculate Each State's Electricity Generation Mix in Python
- How to Calculate Capacity Factors of Real Power Plants from EIA Data
- How to Analyse Power Plant Retirements and Planned Closures
- How to Track New Generating Capacity: Planned Solar, Batteries and Gas
- How to Analyse Monthly Electricity Generation by Fuel in Python
🔧 When it breaks
The errors this topic produces, with the cause explained rather than just the command.
Learning paths through this topic
A curated route rather than a list — the guides in the order that builds on itself.
Related topics
Subjects that keep coming up alongside this one, most overlap first.