Energy management series: Find meaning in your data

In the previous energy management blog, we talked about quality data being the starting point for an efficient energy strategy.

So, now that you have a secure and reliable set of data for a defined period, the next stage is to make effective and proactive use of it.

There are a variety of ways to analyse your data, and considerations should be based on the following factors:

• Building purpose: office, shopping centre, manufacturing plant or school, for example
• Site installations: such as heating and cooling systems and lighting
• Installation usage: are they manually controlled or are there control systems or timers installed?
• Weather conditions: where your site is based and typically what the weather is like.

Generally, these are the main drivers behind energy consumption, so to find meaning in the data set, a full evaluation of these points will help you determine a method for analysis.

There are a number of different methods for analysis, each offering its own benefits. Here are a few examples:

• Degree Day Data: this method is good for year-on-year assessment of your organisation’s consumption profile by removing the affect of different weather conditions
• Heatmapping: for a great visual way of finding anomalies in your data over a specific period
• Intensity Ratio: good for measuring your energy use in relation to certain areas of your business, helping to monitor to expected performance levels
• Benchmarking: a way of comparing performance to buildings of a similar type and to published standards to find poor performance
• Historic Data Comparison: if you have previous years’ data, you can use it to create a typical consumption pattern for your building and to compare this to each year’s use.

In this blog, we are going to focus on understanding and relating energy use to weather conditions.
Degree Day Analysis presents one of the best methods for finding meaning in your data. It provides a metric that compares the energy consumption of a building relative to local ambient air temperature, providing an expected energy consumption based on those conditions, in effect an “ideal”.
There are two types of analysis:

• Heating Degree Day Analysis: this compares ‘fuel’ consumption i.e. natural gas against weather data to determine whether heating on site is being used efficiently.
• Cooling Degree Day Analysis: this compares electricity consumption against weather data to determine whether cooling on site is being used efficiently.

With both types you perform a regression analysis and then a CUSUM (a cumulative sum of the deviation); allowing you to easily find out how far the energy performance deviates from the expected.

A Regression Analysis is illustrated here:

An R² value is a measure of how reliable the line of best fit or trendline is and is deemed excellent if it is in the region of 0.9~1.0. It means the value is as close to the “ideal” consumption as possible and lies on the trendline. With this analysis it is easy to pinpoint periods of over or underconsumption and, depending on the purpose of the building or organisation, helping you identify issues and make recommendations to implement energy savings.

Furthermore, plotting an additional 12-month period of data on the same regression graph can be used to compare against the previous year’s consumption, allowing for a trend to be established. This makes it easier to spot anomalies such as unusual signs of overconsumption. A spike of heating consumption in the summer may indicate that a boiler may have been left on a timer and has not been adjusted to the new seasonal requirement. A similar scenario during the winter months could be related to heat loss in the premises when there is a broken or open window. Cooling degree days would help you identify when air conditioning is using more energy to cool your building if the heating has been left on.

It is important to add, at this time businesses will all have experienced significant and unusual changes in their energy data due to operational restrictions as a result of the Coronavirus. For most, this will create a significant anomaly in consumption. So, when conducting energy analysis over the next 12-24 months, consideration must be made for this.

For help and guidance in finding the meaning in your energy data or pinpointing where improvements can be made in your organisation’s energy consumption get in touch, or call on 01908 690018. Our team of professional Energy Consultants has a wealth of experience in analysing data and finding the methodology that will best suit your business needs.

In the next blog in the series, we will be looking at compliance and legislation. What areas of energy legislation are there, what types of organisations they apply to, and how to comply with them.