| Grid stability and renewables
The resulting grid fluctuations can only be managed with intelligent grid management involving control of production and consumption as well as managing of local grid transformers. In some places, tap changers can be deployed to allow variable turn ratios. This will prevent any overvoltage within a line from being transferred to the next voltage level.
This latter sounds simple in theory, but in practice it is often more difficult. Manuela Linke mentions the lack of grid data in Germany, such as valid information on operating status within the secondary substations. As soon as enough data and control options are available, AI can take on various tasks, such as load flow calculations based on the load forecast and the photovoltaic generation forecast. AI can then help to ensure grid stability and identify errors. It also permits grid planning based on time series. This means that it can predict where grid expansion will become necessary.
Manuela Linke explains that AI can be based on various algorithms. Some require additional training when the grid topology changes, some can be directly applied to a new topology. The main practical challenge for grid operation is not necessarily the quality of the algorithm, though. The quality of data collection and IT security can be more of a problem. After all, both IT and the electricity industry are affected by a lack of skilled workers, adds the researcher.
The limitation of standard load profiles
Processes in the electricity industry must be adapted to the changing grid situation, as Jann Binder of the Center for Solar Energy and Hydrogen Research Baden-Württemberg (ZSW) points out. Today, the electricity industry in Germany still applies the traditional standard load profile to residential customers. This is based on the assumption that all households have the same specific load profile over the course of a day. But households that use photovoltaic self-consumption or even photovoltaics in combination with battery storage, do not exhibit a standard load profile. “The currently used model produces serious errors,” says Jann Binder. This is why we need new load profiles, and these could be created with the help of AI.
The Fraunhofer Institute for Energy Economics and Energy System Technology (IEE) is conducting a research project on this topic. Standard load profiles are no longer able to cover a situation shaped by the rising number of photovoltaic installations, storage systems, heat pumps and EV chargers. “This is where our research project comes in: our AI-supported processes generate the data basis needed for various optimisation and forecasting tasks,” says Dominik Jost, project manager at IEE.
AI field support for installation engineers
Karen auf der Horst, leader of the GenAI project at German distribution system operator Netze BW, demonstrates that electricity companies can use AI for more than controlling the grid. She explains how Netze BW already uses AI to support the daily tasks of installation engineers. When they are in the field, they feed images documenting the installed technology into the system. Using image recognition, this provides valuable information. Based on standardised isolator switch colours, the insulating material used there can be automatically identified. Photos of type labels enable the technical data to be automatically read and stored in databases. While maintaining and repairing assets, workers can obtain the information they need from their own databases, which store AI-formatted, needs-based information. AI will also answer specific questions. New documents generated in the field by installation engineers, such as photos or reports, are entered into the database directly. “We only use our own documents, which prevents AI from hallucinating,” says project manager Karen auf der Horst. Hallucinations are still a problem for generative AI – anyone using chatbots such as ChatGPT will have experienced this. Sometimes, the systems work on the basis of false information. Key Industries, such as power distribution, have to avoid this at all cost.
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