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Energy data analysis
This section contains a more detailed explanation of concepts and techniques for analysing energy data.
Monitoring and targeting
The first step in monitoring energy consumption is to perform an energy review.
The energy review should be evaluated at regular intervals and especially when significant changes take place in an organisation’s systems, processes and activities (e.g. procuring new equipment). A formal energy audit can be a major supporting component of the energy review. It can provide a detailed assessment of how energy is used and what the saving opportunities are.
Initially, energy consumption data can be collected from utility bills and manual meter readings. To develop a more detailed understanding of energy use, more frequently collected, or granular, data is needed. Current smart metering technologies allow for real-time monitoring and collection of energy consumption data; half-hourly or more frequent data is particularly useful.
Sub-meters are a good option for organisations that wish to gain a more in-depth understanding of the most energy intensive areas they have identified. Once installed, these allow isolated monitoring of a specific area of energy use such as a staff room, kitchen, or even individual equipment or appliances.
Analysis of the collected data should aim to correlate energy use with its driving factors. For instance, when examining energy use within an industrial process, the process output is often the main driver for energy consumption; increased consumption. In the case of energy used for heating or cooling buildings, weather is usually considered the main driving factor.
Example: Degree days
Building heating and cooling are often significant drivers of energy use. ‘Heating degree days’ are used as a measure of cold weather over a specific period of time. Equivalent indicators for hot weather are known as ‘cooling degree days’.
Degree days measure the difference between the outside temperature and a theoretical or desired static indoor temperature (often referred to as the base temperature) that is comfortable for carrying out everyday activities without the need for heating or cooling. Thus in the context of heating, if the outside temperature is higher than the base temperature, the heating system should not need to be turned on, and the heating degree days equal zero.
In the UK, the base temperature for most buildings is 15.5°C, whereas in the United States, it is 65°F (approximately 18°C).
Figure 6 depicts an example of the relationship between the levels of gas consumption in a building and the number of heating degree days.
Typically, the relationship between fuel consumption for space heating and heating degree days can be represented by a straight line on an x–y diagram. This line is referred to as the performance characteristic line or trend line.
The trend line allows the energy manager to calculate expected consumption and compare it to actual energy consumption. For instance, given the consumption data plotted in Figure 6, for 100 heating degree days expected gas consumption is about 520,000 kWh. In this example when space heating is not needed (0 degree days), there is still an expected gas consumption of approximately 300,000 kWh; this would be driven by demand unrelated to the outside temperature, such as water heating.
Building heating and cooling represent just one example of energy consumption that should be examined during an energy review. All forms of energy use should be monitored; this can be accomplished using simple spreadsheets or more automated and fully-featured energy management software.
Degree day correlations
Heating is usually provided by gas, therefore heating degree days are usually correlated with an organisation’s gas consumption. Cooling is normally provided by electrical chillers, therefore cooling degree days tend to be correlated with electricity consumption. Many resources for calculating heating and cooling degree days are available online.
Energy Performance Indicators
As discussed in the example, heating degree days are used as a metric for measuring energy consumed for space heating. This relationship between the number of degree days and energy used for space heating is an Energy Performance Indicators (EnPI), and would be expressed in units of energy per degree day. A deviation from this relationship may indicate that something has changed within the heating system, such as equipment maintenance, replacement, or malfunction, or human-driven change in use. Another example EnPI is the amount of energy used per person in a building or other context.
A particularly effective M&T technique for setting targets and detecting irregularities in energy performance is cumulative sum, or CUSUM analysis. For the implementation of CUSUM analysis, the differences between the actual and expected energy consumption must be estimated. CUSUM analysis consists of three steps:
Firstly, the actual and the expected energy consumption are plotted on the same chart. The expected energy consumption is calculated based on the EnPIs of the process or area being examined.
Figure 7 shows an example of how the actual energy consumption (orange points) of a process correlates with expected consumption (blue line). Secondly, the differences between actual and expected consumption over the applicable time interval are calculated, as illustrated in Figure 8.
Thirdly, the cumulative sum of differences (commonly referred to as CUSUM chart) is calculated and plotted as shown in Figure 9.
The trend line of a CUSUM chart indicates whether the monitored procedure consumes more or less energy than expected.
An upward trend in the CUSUM chart indicates consistent use of more energy than expected, whereas a downward trend indicates less energy use than expected. A horizontal trend implies that there are no substantial differences between the actual and the expected consumption. An alteration in the slope of the trend line implies that a change has taken place in the performance of the monitored procedure.
CUSUM charts are particularly useful for achieving continuous improvement in energy efficiency. As explained above, if a downward sloping trend line is consistently observed, less energy is being used than expected for the monitored activity. To ensure continuous improvement in efficiency, this expected amount should be ratcheted down via new targets, resetting the expected energy consumption (or EnPIs) to the current level of use. This adjustment should level the slope of the CUSUM line, until the efficiency of the monitored process is altered again.
In order for the M&T process to be fully effective, an energy manager should create energy consumption reports based on analysis of the collected data. These reports can vary from simple visual representation of consumption to more analytical reports that include the correlation between consumption and driving factors. Reports should be tailored to the needs of the target audience. For instance, reports addressed to senior management could contain a synopsis of the most important findings, whereas reports addressed to key end users are likely to be more detailed or focused. If overconsumption is detected, exception reports can be created. Action can then be taken based on the findings presented in these reports.
Automatic monitoring and targeting (aM&T)
Larger organisations or those with more experience managing energy can opt for automatic monitoring and targeting (aM&T) systems. These systems are widely used and benefit from modern integrated communication systems. An aM&T system consists of meters, data logger devices for capturing and storing energy metering data, and software for analysis.
A typical aM&T system is able to:
- automatically collect meter readings at regular intervals (half hourly, daily, weekly) depending on the energy manager’s requirements
- transmit the collected data to the aM&T software for further analysis
- automatically identify malfunctions in data collection
- automatically identify missing data.
M&T software products have a wide variety of useful features:
- bill validation allows the user to examine whether supplier invoices are in line with the collected metering data
- system alerts highlight irregularities in energy consumption
- benchmarking functions enable automatic comparisons of current energy performance against established benchmarks.