Agent StoreOperationsEnergy & Utilities Management
Live

Energy Consumption Anomaly Agent

OperationsEnergy & Utilities Management

Monitors real-time facility energy consumption data to detect anomalies, equipment inefficiencies, and cost-saving opportunities across sites.

4
Process steps
5
Integrations
3
Data inputs

Facility energy consumption is typically reviewed only monthly via utility bills, long after an equipment malfunction or scheduling error has already wasted significant energy and cost

Identifying which specific piece of equipment or system is driving an anomaly requires manual correlation across submeter data, weather, and occupancy schedules that most facilities teams don't have time to do regularly

Energy efficiency opportunities like off-hours HVAC running or lighting left on in unoccupied areas often go unnoticed for months

This agent continuously monitors submeter and building automation system data, detects consumption anomalies in near real time, and pinpoints the likely equipment or scheduling cause, enabling facilities teams to act within hours instead of discovering the cost on next month's bill

The agent ingests real-time or interval energy consumption data from submeters and the building automation system (BAS), along with weather, occupancy schedule, and equipment run-time data. It applies statistical anomaly detection against expected consumption baselines (adjusted for weather and occupancy) to flag deviations, then correlates the anomaly timing and magnitude against equipment schedules and known load profiles to identify the likely cause. An LLM synthesizes the finding into a plain-language alert with estimated cost impact and recommended action, routed to the facilities team, and tracks resolution to confirm the anomaly was addressed.

1

Establish Consumption Baseline

  • Ingest historical interval energy data by meter/submeter
  • Adjust baseline for weather and occupancy patterns
  • Calculate expected consumption range by time period
  • Update baseline continuously as new data arrives
Outcome: A dynamic, weather- and occupancy-adjusted consumption baseline is maintained for every meter.
2

Detect and Diagnose Anomalies

  • Compare real-time consumption against expected baseline
  • Flag statistically significant deviations
  • Correlate timing against equipment schedules and BAS logs
  • Identify likely equipment or scheduling root cause
Outcome: Anomalies are detected within the same operating day and diagnosed to a likely cause.
3

Alert and Recommend Action

  • Calculate estimated cost impact of the anomaly
  • Generate plain-language alert with recommended action
  • Route to facilities team via email/mobile app
  • Prioritize alerts by cost impact and duration
Outcome: Facilities teams receive actionable, prioritized alerts instead of raw meter data.
4

Track Resolution and Report Savings

  • Monitor consumption after corrective action taken
  • Confirm anomaly resolved and consumption normalized
  • Calculate realized cost savings from corrections
  • Publish monthly energy efficiency report across sites
Outcome: Savings from anomaly resolution are tracked and quantified for ongoing energy management.
Building Automation System (BAS)
equipment schedules and control data
Submeter/Energy Monitoring Platform
interval consumption data
Weather Data API
temperature and conditions for baseline adjustment
Facilities Mobile App
alert delivery and resolution tracking
Utility Billing System
rate data for cost impact calculation