TransitionZero launches open access solar asset mapper for grid planning

Climate analytics non-profit TransitionZero has launched Solar Asset Mapper (TZ-SAM), an open-access global dataset of commercial- and utility-scale solar facilities that can be integrated into systems models for electricity grid operations and planning.

The dataset, which utilitises satellite imagery and machine learning, is the first to be made available at this level of granularity, identifying small- and medium-sized solar assets at scale, according to TransitionZero in a release.

The database can be integrated into system models for electricity grid operations and planning, supporting more effective forecasting by filling gaps in traditional methods of solar asset reporting.

Citing IEA data, TransitionZero states that solar power is the fastest-growing power generation technology in history – in 2023, the world added almost 400GW of solar capacity, equivalent to installing more than 192 football fields of solar panels every hour.

Thus, to effectively manage this ongoing solar deployment, accurate and current facility-level data is essential. It enables the management of intermittency, facilitates grid planning, and allows for the assessment of trade-offs with biodiversity, conservation and land protection priorities.

Until now, they add, datasets of solar generating capacity have not been able to fully meet the changing needs of grid planners. Datasets are country-level, don’t adequately differentiate between large- and small-scale facilities, and struggle to keep up with the rapid pace of solar expansion.

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The TZ-SAM Q1 2024 dataset contains the location and shape of 63,616 assets, along with estimated capacities, an at least threefold increase in gigawatt capacity for facilities under 5MW compared to public and commercial alternatives. It estimates the construction date for over 80% of these assets and contains over 19,100km2 of solar farms across 183 countries, with a total estimated capacity of 711GW.

TransitionZero developed algorithms using earth observation and machine learning to accurately identify the capacity, land area, and age of every large solar facility worldwide, in addition to a large number of small and medium-sized assets.

TransitionZero says they will release regular updates to the TZ-SAM data set. Later this year, TZ-SAM will be integrated into Model Builder, a software platform that offers users an end-to-end service for capacity expansion and unit dispatch modelling.

Commenting in a release, Matt Gray, co-founder and CEO of TransitionZero, said: “To prevent poor decision-making resulting from ‘junk-in, junk-out’ modelling, utilising accurate and current geospatial data is essential. We’re excited to announce the availability of this innovative dataset and eagerly anticipate its integration into our software platform, Model Builder, later this year.”

Added Diren Kocakuşak, research analyst for Global Energy Monitor: “Keeping tabs on the global solar build-out requires all hands on deck. At Global Energy Monitor, we compile a project-by-project, ground-up inventory of solar installations for scientists, policymakers and the public.

“But as progress quickens towards the global goal of tripling renewables, providing complete and accurate data on the growing number of smaller-scale projects across the globe is increasingly difficult. TransitionZero’s Solar Asset Mapper addresses this challenge by rounding out the solar picture with geometries, locations and capacity estimates.”

TZ-SAM’s methodology builds on a University of Oxford methodology and inventory and uses the European Space Agency’s (ESA) Sentinel-2 dataset, combined with the OpenStreetMap (OSM) dataset for training labels.

Originally published on powerengineeringint.com