Insight into energy management

In energy management, energy consumption often depends on external factors - such as the weather. For example, a new air conditioning system is purchased to reduce electricity consumption. However, the following summer is unusually cool. Although electricity consumption falls, this is not necessarily due to the new technology, but to the lower outside temperature. How can you still prove whether the investment was really successful?

This is precisely where the regression analysis in ResMa comes in: it compensates for influencing factors such as temperature or hours of sunshine and normalizes the consumption data. This creates an objective picture of the savings potential regardless of fluctuating framework conditions.

The path to regression analysis begins with a correlation analysis. Users examine their energy data for dependencies - for example between maximum daily temperatures, production times or hours of sunshine and the electricity consumption of a system. The calculations provide values between +1 (strong positive correlation) and -1 (strong negative correlation). A value close to 0 indicates that there is no correlation.

Once the relevant influencing factors have been identified, the regression model follows. This calculates how certain variables - such as the weather - affect energy consumption and isolates these effects. The analysis does not require in-depth data science expertise: ResMa guides users through the process step by step. The tool is also useful beyond traditional energy management. In production, for example, it can be used to investigate quality problems based on data. At the same time, energy anomalies can be traced back to machine faults or incorrect settings.

Fit for ISO 50006 - and the future

Energy management is becoming increasingly important for companies. Driven by the new EU directives, in particular the CSRD, companies are obliged to make precise statements about their energy consumption. The energy and resource management tool ResMa enables energy management in accordance with ISO 50001 and therefore complies with EU requirements. The regression analysis tool expands ResMa to include energy management in accordance with ISO 50006. Together, they enable companies to plan for the future and prepare for upcoming legal changes.

Weidmüller, http://www.weidmueller.de