GIS-based open-source methodology using LiDAR digital surface models

Описание: GIS-based open-source methodology using LiDAR digital surface models for estimating rooftop solar energy potential
OERC Symposium 2025
Speaker: Shreyas Rama
University of Canterbury & Rewiring Aotearoa

Rooftop solar energy presents a compelling choice for households and businesses in the form of cost savings due to less reliance on grid electricity which continues to rise each year. Less reliance on the electricity grid and more emphasis on localised solar installations helps to protect households against grid outages from increases in extreme weather events.

In this research, we aim to use open-source technology and the permissive MIT license as a way to involve members from the solar energy community to contribute and build upon a national solar energy estimation model, as well as provide transparency to the solution and a way for people to replicate results in different regions locally and globally.

The model utilises LiDAR digital surface models at a 1m resolution to account for factors such as shading from vegetations and topology, as well as to calculate rooftop slope and aspect. The GIS tool GRASS and its various modules are accessed via Python scripts to enhance automation and provide a standard interface to programmatically perform GIS operations.

Model validation involves using MetService Weather Research and Forecasting and ground-truth numbers from household solar panel installations to understand how clear-sky estimates from the model might compare to measured solar radiation numbers and subsequent generated solar energy for households.

Outputs from the methodology include a region-based analysis to help councils and businesses understand the potential energy generation and present a compelling economic argument for rooftop solar.