Advanced Metering Infrastructure (AMI) Analytics

AMI analytics leverage interval data from smart meters to extract insights on load shapes, voltage quality, theft detection, and customer program performance. Utilities apply machine learning to identify feeders approaching thermal limits, to target demand response recruitment, and to validate non-wires alternative savings.

The analytics stack typically ingests raw meter reads, weather feeds, and customer metadata into data lakes that support dashboards, forecasting tools, and API feeds for DER aggregators. Privacy and cybersecurity controls ensure customer data is handled according to regulatory requirements.

AMI analytics underpin new tariff designs like time-of-use and critical peak pricing by revealing how different customer classes respond to price signals. They also provide measurement and verification for energy efficiency programs and distributed storage portfolios.

Investors rely on AMI-derived evidence when financing behind-the-meter assets, because it provides auditable baselines and performance tracking. Policymakers evaluate AMI analytics maturity when approving cost recovery for grid modernization.