Due to an openEMS fork it is capable of generating electricity via PV modules, and monitor the output. Furthermore, it offers several interfaces, MQTT, REST, OPU UA, to access the generated data. Using the monitored data, the participants can start to train an AI/ML model to predict future generation. As an alternative AI/ML methods can be applied to determine the current SoC – of the battery inside. Understand the challenges in PV generation and ways to mitigate unpredictable generation, using AI-based forecasting. The role of buffering capacity as an important component in renewaber energy systems. The monitoring, buffering and forcasting techniques can be adapted to be used in any energy consuming process, e.g. for peak consumption monitoring, forecasting and shaving.