He and his team are working on the region’s structural strategy and its energy transformation, in which artificial intelligence plays an important part. “Our goal is to develop an energy generation plant that operates autonomously, identifies damage and can run in critical situations, excluding the possibility of standstills or further damage. In short, we want an operating plant that makes its own decisions on how to react in the event of potential damage.”
Schulz says that the company monitors “everything that is powered mechanically” in gas, water and wind turbines by using artificial intelligence. He adds: “Despite sophisticated sensor technology it would be impossible for us to draw as many conclusions as we can today without AI. One person could never analyze so much data.” Schulz estimates that around 600,000 measurements per sensor, per minute are produced in a wind power station. Sound data, for example, can be collected and aggregated via a decentralized field bus or PLC in cycles of a few seconds up to several hours, depending on the protocol.
This data is then fed to an IM&P server. A genetic algorithm with weak AI establishes recursive neural networks which compare the data with images of damage or report threshold levels which have been exceeded. This is no simple task due to the volume of technical details to monitor across the entire drive train of the wind energy plant, as well as the fluctuations in wind-generated energy (for example, Central Europe typically experiences strong fluctuations in wind speeds), the connection of wind energy plant to the central grid but also the whole process control, which means that it is necessary to compensate for the sometimes strong variations in the measurement data.