Load Profile Analysis allows you to quickly identify load anomalies by plotting interval data over a daily time series for specific days of the week.
👍 This article will help you:
Visualize daily load profile trends
Identify load profile anomalies
To access Load Profile Analysis, go to Apps in the side menu at left, then Load Profile Analysis.
Overview
In the Load Profile graph, you can configure:
Field | Instructions |
Building | Select a building. |
Point | Select the data point you wish to graph. |
Period | Select the time period. Choose from standard calendar views or rolling views. |
Days | Select a day view, such as weekends, weekdays, or a particular day of the week. |
Overlay (optional) | Select an optional graph overlay. Choose from daily average temperature or daily peak temperature. |
Above: Graph of electricity consumption over the last 30 days during Mondays.
The Max (red) trend line is the profile with the highest overall peak demand value. The Min (green) trend line is the profile with the lowest overall peak demand value. The Average (orange) trend line that is an average of all the profile lines. Individual profile trend lines are rendered in gray.
Below the graph, statistics are displayed in a table: average hourly demand and maximum hourly demand.
Above: Statistics for a graph of electricity consumption over the last 30 days during Mondays.
Best practices & ways to use
Determine if your buildings have scheduling in place: If your buildings have lots of disparate profile trend lines, with no recognizable pattern, this likely indicates that there is no building equipment schedule in place for the selected point. Lines that are close together, with a small range between the minimum and maximum, indicate that building usage is predictable and there is likely scheduling in place.
Find deviations in your building schedule: Load Profile Analysis is a great way to visualize deviations from what is normal. For example, if you are looking at a building where a setback schedule has been implemented, the lines during the day should be very close together during unoccupied hours. Analyze the graph for loads that appear to deviate from what is expected during those hours.
Identify and curtail peak demand use: Load Profile Analysis can help you review past peak use and make data-driven decisions on how to curtail future peak consumption.
Isolate the effects of weather on building performance: If you want to compare your building’s use over all the days during the "shoulder" season, or if you want to see how consistent your building’s usage has been over the same day of the week for the past year, then choose an optional overlay of 'Daily average temperature' or 'Daily peak temperature' to isolate the effects of weather from the data.
Troubleshooting
Problem | Solution |
I cannot hover over a specific trend line. | At times, there can be multiple profile trend lines in a single area of the graph. If you cannot easily hover over the desired trend line, try limiting the period to a shorter time range. |