The opt.cloud visualizes the recorded data in real time in the frontend. So the user always has a clear representation of any energy and cost parameters and can use them for further analysis and optimization purposes. As soon as the opt.cloud detects or can predict a peak load with the help of artificial intelligence, regenerative energy sources and storage can be switched on automatically. As an alternative to this, it is also possible to counteract the detected peak load by targeted load shedding, i.e. targeted shutdown or regulation of defined consumers to counteract. Using these fully automatic processes, load peaks that occur can be compensated for in a targeted and proactive manner by means of regenerative and free-of-charge energy or a short-term reduction in energy consumption. In order to be able to implement this, the opt.cloud records the corresponding energy parameters in real time and permanently at any consumer in the backend, digitizes them and stores them in a central storage location. This data collection forms the basis for the use of the artificial intelligence of opt.cloud. The specially developed algorithms for artificial intelligence continuously analyze the database in order to recognize patterns, which in turn provide information and conclusions about when and for what reason a load peak occurred on the consumer. By recognizing these specific patterns, it is possible to make a detailed load peak prediction.