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Take the first steps to converting forced outages into planned outages
Customer outages caused by faulty equipment are a problem that affect every utility. When an outage occurs, field crews are dispatched to try to locate and fix the faulty equipment as quickly as possible. Often the crews don’t know where the fault is on the circuit, which equipment failed and what caused it to fail. This process can be incredibly time consuming and costly for the utility, eating into operations and maintenance budgets. Utilities need to know when equipment is failing before it results in an unplanned outage. That way they can turn reactive maintenance into proactive maintenance and keep customer outage time to a minimum.
So…what do the first steps to predicting outages look like?
Data Pipeline setup
The first step is to establish a pipeline that supplies PQ data, outage logs and any other supporting data to a dedicated AWS instance that is stood up specifically for the utility. Toumetis will adapt to the processes and formats used by the utility in order to ensure a real time data stream is securely established and the Cascadence dashboard can be used to view data and predictions.
Validation
The second step is to analyse the utility’s data set to identify key pain points and utility specific challenges.
Refinement
In parallel, Toumetis will monitor the performance of the models and services to identify whether refinement is required in order to best solve the challenges specific to the utility. This phase will provide tangible examples of mitigated outages.
Operationalise
Once Cascadence is deployed and validated it needs to be embedded into a utility's operational workflows to ensure its predictive power is being properly harnessed. Toumetis will work with the utility to produce Cascadence’s predictions in a format best suited to the utility.
