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Energy & Utilities

14% Reduction in Energy Waste for a National Utility Provider

-14%
energy over-provisioning
96.4%
forecasting accuracy
$29M
annual cost savings
+31%
emissions tracking accuracy
Challenge

A national utility operator was over-provisioning grid capacity by 14-22% due to inaccurate demand forecasting. Manual scheduling created $35M/year in preventable energy waste.

Solution

We deployed a demand forecasting and grid optimization model combining weather data, historical consumption, industrial calendar events, and real-time IoT telemetry from 2,000+ grid nodes.

Technologies Applied
Time-series MLWeather API IntegrationIoT TelemetryOptimization AlgorithmsSCADA
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