The ResMa® energy management system’s regression and correlation analysis broadens opportunities for energy managers. The additional tool cleans data and standardizes KPIs. Through the expansion module, organizations can manage their energy systems in compliance with ISO 50006 while adhering to the EU’s corporate sustainability reporting directives (CSRD).
Dependencies result in incorrect conclusions – but not with ResMa®!
Particularly regarding energy management, it is especially intriguing to discover how much energy will be conserved by acquiring a new system. Nevertheless, when assessing energy usage, information can frequently rely on outside factors. For example, in the scenario of a heating and air conditioning system, this might appear like this: on an exceptionally hot summer day, the energy manager finds that the system is consuming a higher than usual amount of current. New machinery might result in possible savings. As a result, he swaps the old system for a new one in the wintertime. The next summer, though, the temperatures do not meet expectations. The climate is chillier than it was last year. The upgraded heating and air conditioning system consumes less energy because of the reduced temperatures. In what ways can the energy manager demonstrate that the investment was worthwhile?
This is where ResMa® employs regression and correlation analysis: the system aligns data gathered from the previous year with that from the current year. This indicates that data can be analyzed irrespective of varying temperatures. This allows the program to demonstrate the actual savings achieved by the heating and air conditioning system.
Developing regression models in just a few steps
The initial step in developing a regression model is conducting a correlation analysis. Users utilize the data gathered in ResMa® to identify connections between specific values. By doing this, users can recognize correlations among, for instance, sunlight hours, daily peak temperatures, working hours, and the energy used by the heating and cooling system.
The emphasis is on the quality of these connections. ResMa® performs correlation analysis calculations that yield results between +1 and -1. The nearer a value is to +1, the greater the dependency becomes. Conversely, if the value nears -1, it indicates a negative interdependence. If the system outputs a result near 0, it indicates no dependency exists between the examined values.
Once the energy manager has identified dependencies between the values and determined the type of correlation, they can create a regression model. The model automatically calculates the data and transmits the harmonised results. Now, the data can be compared and values can be drawn from the system regardless of other measured values.
Implementing a regression analysis requires no data science expertise. The expansion module specifies the exact steps for users to create models, helping them to implement use cases.
In addition to energy management, regression analyses can also be used for troubleshooting in production. The regression analysis can use an error in the quality of the final product, for example, to identify a correlation to a known irregularity or other data. In addition, increased energy consumption can help identify incorrect machine settings or a system defect.
Energy management in accordance with ISO 50001 and ISO 50006
Energy management is becoming a more and more important focus for companies. Driven by new EU guidelines, especially the CSRD, companies are now obligated to provide precise information on their energy usage. The energy and resource management tool ResMa® facilitates energy management according to ISO 50001 and meets EU specifications. The regression analysis tool adds energy management according to ISO 50006 to ResMa®. ResMa® and the regression analysis tool make it possible for companies to plan for the future and prepare optimally for future legal requirements.
Weidmüller offers a comprehensive energy management portfolio. In addition to the ResMa® software and regression analysis, the solution includes a variety of hardware products: energy meters, as well as the improved energy measurement module for the I/O system u-remote.