“Not too hot, not too cold. Just right”
Luca Cotta Ramusino
Around 38% of all UK emissions are related to heat of some kind and a large proportion to heating in buildings. In schools, heating often accounts for the largest proportion of energy use and emissions.
So, how do you assess and improve the heating performance of a building?
BAM FM manages a range of buildings for our customers (including schools, hospitals and offices) and we work with occupiers across the estate to improve energy efficiency and provide comfortable, healthy and productive spaces. Providing efficient heating is a major part of this.
There are a range of approaches, but two very useful and simple tools stand out: the scatterplot chart and the CUSUM (cumulative sum of differences) analysis. Both are based on your heating consumption (e.g. units of gas used taken from metering or billing) and a measure of how cold the weather has been (e.g. heating degree days, which are a measure of how much heating is needed in buildings based on how cold it is…the more degree days there have been over a period, the colder it’s been. Learn more here).
The scatterplot chart
If you plot your heating energy use against degree days for the same period you should come up with a chart like the one below, based on one of our recently built academies in the Midlands.
As expected, colder weather (i.e. higher degree days) requires more gas to keep the building warm. By analysing data in this way and plotting the trend line we can help to highlight how energy efficient heating systems are.
The chart shows there are times during cold weather that we don’t even need to heat the building (where little to no gas is used despite the cold weather indicated by degree days). This is achieved through a combination of efficient insulation and solar gains (making use of ‘free heat’).
Ideally we want to see high gas consumption alongside high degree days. This shows there is a high correlation between energy use and colder weather, which means heating systems are operating pretty efficiently.
Any spread sheet application will calculate a correlation coefficient (or R-square) for you. In this case, the value of 0.93 (out of a maximum of 1) indicates exceptionally good correlation between energy use and weather, meaning that plant, distribution and controls all work efficiently to supply a comfortable indoor temperature.
Cumulative sum of differences or CUSUM analysis
A useful tool in measuring long-term performance is the CUSUM chart. Produced using the same data as the scatterplot, you can use it to check if you’re becoming more energy efficient.
The first step is to calculate how much heating you should have used, based on degree days in a month (this is effectively a ‘prediction’ but after the fact, once you know how cold it’s been). The predicted value can be worked out using the formula shown in the chart above and you can find out more here. Differences on a month by month basis are not that revealing, but the cumulative sum of differences usually is. The chart below is an actual CUSUM for one of our 13,000 m² secondary schools in West Sussex.
The curve consistently pointing down over time demonstrates that the more we’ve learnt about the building, the better we’ve become at managing energy.
The path to energy efficiency
As our example above shows, the ideal is to achieve continual improvements or an acceleration in efficiency. The red line shows the efficiency trend from about September 2009 to March 2010 improving. The green line shows the trend for the most recent period where even greater improvements have been made. This is a clear indication that energy saving measures are working, and the building is operating more efficiently.
As we learn about a building we can introduce new control strategies, operate equipment differently and “tweak” the building management system to squeeze more efficiency out of the whole heating system, helping to reduce costs, emissions and improve comfort for building users.
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