Despite the annual weather-related fluctuations in energy requirements for heating, the question arises as to how the energy manager can still demonstrate his energy efficiency from year to year.
Energy costs have almost exploded in the last two years, making many companies more aware of the need for energy efficiency. In order to become more efficient, we first need to understand the current state of energy consumption. This can only be assessed by those who analyze their company’s energy data. The following is particularly striking when comparing the energy requirements for heating from year to year:
Despite the implementation of various efficiency measures, energy demand does not remain constant, nor does it fall continuously from year to year. Examples of these efficiency measures include replacing light bulbs, operating machinery efficiently and taking measures to optimize heating. They also include improving insulation, raising colleagues’ awareness of energy-conscious behavior and replacing old heating systems with more efficient ones.
Despite these efforts, energy consumption has actually increased in some years compared to the previous year. There are also large fluctuations in the savings made at different locations, even though the same measures have been taken. This raises the question of why this might be the case.
External influences affect the heating energy requirement
This phenomenon is mainly due to external influences. External effects such as the weather have an impact on the energy data and make it difficult to correctly evaluate and interpret the results. The following points should be emphasized in order to make this plausible and to clarify the connection between energy demand and the weather:
- Long-term trend analysis:
By evaluating measurement data over a longer period of time, a trend in energy demand can be identified. It is important to look at the data over several years in order to take into account seasonal fluctuations and annual differences in the weather. - Comparison with historical data:
By comparing the current energy demand with past years, it is possible to determine whether the increased energy demand is in line with climatic changes. This is because if energy consumption was reduced in times with comparable weather, this indicates that energy efficiency has also changed. - Weather adjustment of measurement data:
One method of isolating the influence of the weather on energy demand is the so-called weather adjustment or climate adjustment of measurement data. Statistical methods are used to eliminate the influence of the weather and determine an adjusted energy demand. This enables a direct comparison of the adjusted energy demand between different time periods. - Documentation of energy efficiency measures:
To prove that efficiency improvements have actually been implemented, all energy efficiency measures carried out should be accurately documented. This includes, for example, the installation of energy-efficient devices, the optimization of processes or changes in energy management.
By taking these points into account and adopting a holistic approach, it is possible to ensure whether efficiency-enhancing measures have been implemented effectively and whether a change in energy demand can actually be attributed to the weather.
The climate correction factor
The climate correction factor is available to check this. This factor is published on the website of the German Weather Service specifically for each zip code area and always refers to the respective year. The ZIP code separation is necessary in order to take each microclimate precisely into account and to enable detailed work with this factor.
The climate correction factor is calculated by comparing degree day figures for a reference period, usually a year. The degree day numbers of all days of a year are summed to obtain an annual degree day number (GTZ year), which is approximately in the range of 3500 Kd/a. This figure is then set in relation to the same figure for a reference period, such as the previous year. The ratio of these two values gives the climate correction factor, which is usually between 0.8 and 1.2.
In order to calculate this value, it could be laboriously determined from your own measurement data. Alternatively, it is also possible to save yourself the preparatory work and use the climate correction factor provided by the German Weather Service.
Use of the climate correction factor
In practice, this means that the climate correction factor is defined as a base value in our energy data management system and updated with a new value every year (or every other period).
KBR’s visual energy EDM system is used for this purpose. In the next step, a key figure (or a calculated metering point) is formed for each 15-minute measured value by multiplying the real, measured energy demand by the climate correction factor.
This results in a key figure for each 15-minute measured value. This is then compared with the original energy demand, most simply in the form of a diagram. For this purpose, it is advisable to use values averaged over monthly or annual periods. These averaged values are shown below as a comparison of the real and climate-adjusted gas demand over a period of three years.
This diagram clearly shows that actual gas consumption (shown in red) has increased in 2021 compared to the previous year. If, on the other hand, the climate-adjusted gas consumption (shown in green) is considered over this period, a decrease is recognized in the second year. Although these data appear contradictory, they illustrate the added value of climate adjustment.
From this, it can be deduced that the winter in 2021 was correspondingly colder than in the previous year and that gas consumption would have been lower in a warmer winter, similar to the reference year 2020. This climate adjustment therefore shows that this business has become more energy efficient despite the higher real consumption from 2020 to 2021.
Why an energy data management system (EDM)?
At first glance, this calculation may sound very simple and could also be solved using standard spreadsheet programs. However, errors can quickly occur. With the visual energy EDM system, you avoid such errors and gain further advantages:
- Security thanks to reliable data:
In visual energy, the original energy consumption data is used, regardless of the media (gas or electricity). This means that calculations are always based on plausible data. - Save time with the open key figure editor:
The open key figure editor makes it possible to quickly and easily create the climate correction factor as a basic variable among the key figures. This allows it to be output as a “climate-adjusted heating energy requirement” in a separate key figure. Multiplication with the original measurement data can be carried out in just a few clicks. - Individual diagrams:
In order to obtain an immediate comparison between the climate-adjusted measurement data and the original measurement data, these two data points can be individually prepared graphically. The observation period can be freely selected. In addition, visual energy allows you to link the data points and check the measurement data with a single click. - More convenience through immediate individual access:
In visual energy, this data can be shared immediately with specific colleagues without having to send additional emails every time a change is made. - Overview through linking in the action plan:
There is a separate measures plan in visual energy. All diagrams and data points are linked in the specially created measure “Climate adjustment of my measurement data” and can be easily viewed during the energy audit.
The use of visual energy facilitates the calculation of climate-adjusted measurement data and at the same time offers an efficient way to visualize, share and present the data as part of the energy audit.
Conclusion
Simply analyzing the energy measurement data and comparing the annual totals is no longer sufficient for many ISO auditors. This is mainly due to the fact that, despite numerous conversion measures, savings are not immediately apparent every year. In such cases, a weather adjustment of the energy measurement data, especially the heating data, is helpful. This measure makes it possible to clarify the influence of the climate on the measurement data and draw a correct conclusion from the data.
To achieve this efficiently and with plausible results, the solution in the visual energy EDM system is the most commonly used approach.