Grid stability and renewables |
Using AI to deal with complex load flows: DSOs are dipping their toes
The number of decentralised and fluctuating electricity producers, particularly photovoltaic installations, is rising. This is creating a growing challenge for distribution system stabilisation. To provide better management of producers and consumers, creating grid stability and overcoming bottlenecks, artificial intelligence is becoming an attractive option that can help evaluate the flood of grid status data
So far, it is just baby steps. Grid operators are testing artificial intelligence for various applications. The objective is to make the power system more secure and efficient, especially at the level of the distribution system. As decentralised power generation rises and load flows become more complex, this will become increasingly urgent.
German utility Stadtwerk am See in Überlingen recently collaborated with HTWG Konstanz – University of Applied Sciences, Fraunhofer Institute for Solar Energy Systems (ISE) and the International Solar Energy Research Center Konstanz in a research project aimed at the development and testing of prototypes of AI- based low voltage controllers.
“We had previously worked with algorithms without AI, with a similar intention,” says Jan Etzel, Head of Power Grid Operation at Stadtwerk am See. AI is now employed to optimise the system. According to Etzel, being able to use the novel algorithms was contingent on the extensive deployment of measurement technology within the low-voltage grid. The project used data from an industrial estate in Friedrichshafen to “design the power grid of the future and successfully simulate grid control,” says Etzel.
Grid status is often unknown However, there is one factor potentially limiting this application of AI in Germany: in many parts of the country – not just at Stadtwerk am See in the federal state of Baden-Württemberg – distribution system operators often know very little about the status of individual grid lines (and this is likely to be the case in other countries as well). The absence of data means that frequently, the measurement infrastructure must be expanded before sophisticated algorithms can be employed. AI depends on measurement data. Once real time data is available, “the heart of a smart grid”, a smart control system based on AI, can be used. Stadtwerk am See explains that the control system accesses all relevant information from the low-voltage grid, such as up-to-date measurement data from transformer stations, consumers and producers. It also has data on annual consumption, weather, forecasts and much more at its disposal.
This allows AI to analyse the data sprawl in order to take quick and accurate decisions,
20 | April 2025|
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says Jan Etzel. Nowadays, load flows are too multidimensional for human operators to oversee – let alone control. This is where AI comes in, by flattening peak loads and preventing grid congestion, if necessary by curtailing generation. The fact that software learns from past events and mistakes means that, based on ever more detailed forecasts, it will be able to work more and more effectively to prevent critical situations in the grid.
“Digitainability”, a vision of the electricity industry
The Smart Grids Platform Baden-Württemberg recently demonstrated the state of the art of AI for the electricity industry, during the Smart Grids Dialog 2024 in Konstanz, with the theme “Artificial intelligence in grid operation.” Arno Ritzenthaler of Smart Grids Platform Baden-Württemberg stressed that AI is “more than a digital twin”. It can help stabilise the grids and reduce the need for grid expansion.
Professor Gunnar Schubert of HTWG Konstanz introduced the concept of “Digitainability”, a combination of digitalisation and sustainability. Renewable sources of energy depend on intelligence and digitalisation of the grid. Feeding 60 GW of PV generated electricity into the medium or low voltage grid will create major challenges, according to Schubert, who also sees this as an area of research aimed at forecasting potential disruptions.
Managing 400 GW of solar power Manuela Linke, the leader of the AI4Grids research project at HTWG Konstanz, which was concluded at the end of 2023, explains how complex the power system of the future will be: there are expected to be 35 million electric vehicles on German roads by 2045, leading to the demand for electricity at least doubling. At the same time, photovoltaic capacity will be expanded to more than 400 GW, wind power to more than 300 GW.
EM-Power Europe: digitalisation for more transparent low-voltage grids
The European Commission estimates that network operators will need to invest at least 170 billion euros in grid digitalisation and intelligence by 2030. Which technologies are available today? Where is artificial intelligence already being used, and what are the trends? At EM-Power Europe, to be held 7-9 May 2025 in Munich, topics will include innovative solutions for grid digitalisation and control, increasing the accuracy of generation and load forecasts, as well as the integration of decentralised systems. Presentations at The smarter E Forum, taking place during EM-Power Europe, will look
at how artificial intelligence can be used for grid management and the integration of prosumer installations into the energy system. The EM-Power Europe Conference, to be held 6-7 May 2025, will also focus on digital solutions, with disruptive AI and GenAI technologies, digital twins and 5G to be discussed in the “Innovation and Digitalization” session. EM-Power Europe is part of The smarter E Europe, the continent’s largest alliance of exhibitions for the energy industry. 3000 exhibitors and 110 000+ energy experts are expected in Munich in May at four parallel exhibitions: Intersolar; ees; Power2Drive; and EM-Power Europe. For more information, visit:
www.EM-Power.eu
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