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European Energy Operator
The Situation
A European renewable energy company operates a growing network of off-grid solar sites equipped with battery storage and diesel generator backup systems. The operational mandate was clear: reduce fuel consumption, minimize carbon footprint, and improve cost efficiency. The internal capability to execute on that mandate through predictive AI was not there.
Gensets were running beyond necessity because the team could not forecast when solar and battery capacity would be sufficient. Third-party forecasting data existed but the team lacked the engineering skills to integrate it. Hiring specialist AI talent locally would have been slow, expensive, and disproportionate for a focused use case.
What We Did
One Primero augmented the client's operations team with dedicated AI and data science engineers working alongside existing operations engineers. The focus was on extending the team rather than replacing it.
The team integrated third-party forecasting data into the client's site infrastructure, built and validated AI and machine learning models to predict daily energy production per site, and designed automated daily site reconfiguration logic to optimize how gensets and batteries were deployed. Knowledge transfer was built into the engagement from the start.
What Followed
Optimized genset usage drove a 20% reduction in operational costs. The carbon footprint reduction was measurable and attributable, improving ESG ratings. The internal team gained capability through knowledge transfer, reducing long-term dependency on external resource.
The approach was approved for rollout across 200 additional off-grid sites.
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