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Smart Meter Outage Prediction

August 12, 2020

Client: Leading Utility Organization

Problem Statement

Organization wanted to gauge value of its new Smart-Grid initiative for their infrastructure management:

    • Predicting meter events and outages including likely malfunction
    • Predicting spike in consumption to reduce spot-procurement
    • Ability to notify customers of their consumption habits / patterns in near-real time.

    Analysis Led Approach

    • Define population by zip codes, time period, manufacturer & events (power and meter events)
    • A pair wise correlation of events and Linear Regression model to predict total event count with variables as events identified in previous events
    • Prioritization Algorithms arrived by using cluster analysis for prediction of outages & spikes

    Business Approach

    • Prediction of last mile consumption spikes with accuracy of 89%
    • Increase up to 80% in prediction of consumption leakage
    • 10 times decrease costs decrease in network audit
    • Reduction in field staff workload that repairs/replaced smart meters at 0.014% from 1% of 1.2 million meters in a 45 day period

    Critical Success Factors

    • Consumption spikes accurately predicted with an efficiency of 89%
    • Consumption leakage controlled with a 80% positive prediction for similar events
    • Results seen in 45 days post implementation of the suggestions

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