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Bidgely AMI-Driven Insights Report Reveals Analyses from Utility AI Deployments

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Bidgely introduced the AMI-Driven Insights Report, which provides concrete examples of how applying artificial intelligence to AMI (advanced metering infrastructure) data can support utilities across core operational use cases. Analyses included in the report are derived from deployments of Bidgely UtilityAI Insights Engine with progressive, multi-million-customer utilities in the northeastern, western and southern U.S. The utility operational use cases include electric vehicle (EV) adoption, non-wires solutions (NWS), demand-side management (DSM), rooftop solar (PV) analysis and time-of-use (TOU) rate optimization.

“Already the trusted partner for technology and innovation, our smart reporting exemplifies how Bidgely layers on human intelligence and business acumen to achieve strategic utility goals.”

“Releasing these sample customer reports illustrate the deep value that AI can bring to utilities as well as the advantages of having data-driven reporting for internal decision making, understanding key drivers of various utility programs, proving return on AMI investments to regulators and more,” said Bidgely CEO Abhay Gupta. “Already the trusted partner for technology and innovation, our smart reporting exemplifies how Bidgely layers on human intelligence and business acumen to achieve strategic utility goals.”

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Sample analyses in the AMI-Driven Insights Report include:

  • EV Adoption – Grid Disruption Potential Reporting
    • EVs can have a disproportionate impact on the grid even at low penetration. An analysis shows how AI can identify feeder lines or even individual transformers that could come under strain due to multiple EVs to avoid blackouts.
  • Non-Wires Solutions – Key Appliance Ownership Statistics
    • Understanding ownership of key appliances in a specific geographic region impacts planning. An air conditioning targeting analysis reveals the opportunities for load shifting by targeting individual customers with large peak loads.
  • DSM – Targeting
    • AMI-based end-use disaggregation can improve the whole lifecycle of DSM programs. Program targeting analyses illustrate the benefits of efficient marketing better allocation of rebate dollars.

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