Case Study: RESOLV Technology Reduces Alert Noise by 92%

RESOLV cuts down on the noise created by alerts by using machine learning and AI-driven issue engines to compress issues with a common root cause.

by Bree Brouwer

When traditional monitoring platforms see that an inverter is not producing, they create a new alert every day that the inverter continues to not produce. These are separate alerts for the same problem that an asset manager has to sift through to find the real, actionable issues.

The issue engine of Omnidian’s proprietary technology, RESOLV, tracks and merges alerts with the same root cause into one issue. In the RESOLV Operations Portal, more alerts contributing to the same issue means that the issue increases in priority level in our Performance Team’s queue, ensuring that they always automatically see the highest-priority issues first.

Case Study Stats

Asset Count: 1,227 commercial PV systems
Total Size: ~125 MW
Timeframe: 12 months
Total Issues: 189,610
Total Corrective Truck Rolls: 1,476

Alerts vs. Issues

RESOLV cuts down on the noise created by alerts by using machine learning and AI-driven issue engines to compress issues with a common root cause.

The following image is an analysis of issues filtered through Omnidian technology and actioned remotely or remediated through a service visit:

Percent of Resolv issue compression – Click to Enlarge

Legend:

• RESOLV autodiagnosis as inactionable: Removes low actionability root causes like snow and issues that were raised but symptoms have now resolved on their own.
• Human diagnosis as inactionable: Omnidian Operations team member dismissed or snoozed the issue based on their review of the data.
• Remote resolution: Any issue with an associated ticket but no truck roll. Though relatively rare, we do sometimes remotely walk a client through steps to reset equipment remotely.