What is the control chart telling me?

The purpose of the control chart is to give you some feel for the fluctuations in your building energy performance. The chart helps your quickly detect if something might be amiss with your heating system or control if one week energy use is plotted to be significantly above predicted.

The control chart visually displays how your actual weekly energy consumption varies from your predicted energy consumption, which is determine from the slope of your performance line. This is calculated by substracting your predicted consumption (i.e. from the equation of the performance line) from the actual consumption for each week.

This difference is then plotted for each week energy data was provided, as a percentage above or below zero, which is the point where actual and predicted are the same so cancel each other out.. Note that the convention for determining these differences is always actual minus predicted. Any energy savings against the predicted will show up as negative values.

It is possible to set limits on the normal expected operating range of the building. There are statistical methods for determining what should be the acceptable range your building might be above or below predicted energy use. At the moment in SMEasure we have set the range threshold as plus or minus 20% in the control chart. However, we will be developing the functionality to let you set your own operating range and advise you what that range should be.

Example 1: Office

In this chart of an office using electricity for heating you can see that actual energy use from November through to February was generally above predicted estimation, but it did not go above 20%. The only point during that period when the energy use was significantly lower that predict was during the Christmas and New Year holidays when heating was probably turned off as the office was closed. From February to April actual energy use has been lower than predicted.

Example 2: Venue

In this chart there are a few points at which actual energy use has been 20% more than or less than predicted. The first week in January energy use was about 20% - this would flag to the energy champion that they should investigate if there is a logical reason for this (e.g. that have several big events taking place) or if there could be an issue with the heating system. There are several points when actual energy use was more than 20% less than predicated - this could have been there were no events taking place so the heating was no turned on as much. In SMEasure when readings are entered you can add a comment - this can be helpful when looking back are energy performance to understand what might be triggering high or low energy consumption.