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AI USE CASE
Energy consumption forecasting & optimisation
Forecast energy demand and shift loads to cut bills and emissions.
What it is
A forecasting model combined with optimisation predicts hourly site-level energy demand and recommends when to run heavy loads, charge batteries or buy from spot markets. Typical savings: 8–15% of energy bills plus measurable Scope-2 reductions.
Data you need
Smart-meter data at 15-min granularity for 12+ months.
Required systems
- data warehouse
Why it works
- Close the loop with BMS/EMS controls
- Re-baseline after every major HVAC change
How this goes wrong
- Recommendations not connected to actual control systems
- Forecast drift after equipment changes
When NOT to do this
Skip if your annual energy bill is under €100K — savings won't cover the project.
Vendors to consider
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