The integration of electricity consumption data into the various work areas and living environments has revealed considerable potential for the sustainable use of resources in companies. In this process, guidelines for the design of energy management systems were developed, which allow users to view historical and current electricity consumption data in a task-oriented and action-centered way, in order to identify irregularities in consumption patterns, to evaluate efficiency measures retrospectively and to make optimization potentials visible.
In order to counteract the constant changes ahead of time in the future and to be able to evaluate efficiency measures in advance, usable and reliable future forecasts are needed in addition to the historical data. Such forecast data can be used by companies to investigate possible deviations or peak loads as well as to simulate various measures. Both the technical implementation and the practical design for integration into the various work areas in the company are still largely unknown.
In the research project, the following aspects are to be investigated and tested within the framework of a Living Lab-based research and development in an application-oriented manner and together with the industrial partners:
- Testing of different methods for the generation of prognosis data (statistical modelling and (un)monitored machine learning methods)
- Context analysis for the application of the developed forecast data in operative and strategic business units
The aim of the research project is to develop a tool set including design guidelines, which enables the flexible and dynamic use of power consumption forecast data in companies based on real-world case studies. In addition, the Living Labs will develop methods for the introduction of such socio-technical systems and investigate their organizational effects.