This scenario outlines how to use OBEM to diagnose and fix an energy issue in a building and generate a relevant work order for the fault.
In Figure 12, the Energy Performance widget displays the total energy consumption for March for a single building location in Sydney.
To identify potential faults in the high consumption period, the energy manager uses the Equipment Performance widget for the same period, as shown in Figure 13.
Chillers account for 53% of the total energy consumption and AHUs account for 15%. The manager decides to focus on these areas to identify potential improvements. The manager opens the Total AHUs widget to see one year of data, as shown in Figure 14.
The March AHU total exceeds the baselines. This suggests that there may be a problem.
The manager opens the Total CHW widget to six months of chiller energy data, as shown in Figure 15.
The chiller consumption for March is also slightly above the baseline. The manager opens the FDD tab for the location, as shown in Figure 16.
The manager examines the FDD tab to identify the likely root cause of the March issues. He examines the equipment and space relationships and determines that the cause of the energy leak was a faulty supply air humidity sensor bringing high dew point air into the building in March. This issue caused the following energy faults:
- High thermal energy resulted in two chillers operating
- High AHU fan power opening additional VAV boxes
Using the work order module, the manager assigns a ticket to his field technician team:
The maintenance team replaces the supply air humidity sensor.
Equipment fault rates can indicate areas that a manager can control their operating expense budget. The manager uses the Summary tab to track the work order along with the other location and equipment service reports:
In subsequent months, the manager checks the same OBEM's widgets to ensure the problem does not reoccur. The AHU and chiller energy usage widgets indicate that the troubleshooting was a success:
