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By | June 14, 2024

Recap of the 5th Power Grid Model Community Meet-up

By Thijs Meeuwisse

On 6 June 2024, the Power Grid Model (PGM) community came together at Eindhoven University of Technology to share knowledge and to discuss the future directions of the project. In this blogpost, I share a quick recap of the event. Slides and a video recording from the meet-up can be viewed here.

The 5th Power Grid Model Meet-Up took place at Eindhoven University of Technology (TU/e). The room, which offered a magnificent view over the university campus, was packed with over forty members of the PGM community. In addition, another forty participants joined the meet-up online via the seamless livestream that was offered.

Tony Xiang, chair of the Power Grid Model steering committee, facilitated the event and welcomed the audience. A recap of the presentations follows.

Welcome address by Koen Kok (TU/e)

Koen Kok, full professor in Intelligent Energy Systems at TU Eindhoven, kicked off the meet-up by delivering a keynote speech on the role of systems simulation in intelligent energy systems research. “Electricity grids are in the centre of attention,” commenced Kok, referring to the cover of a recent edition of *The Economist*, which read “Hug pylons, not trees.”

Kok continued: “TU Eindhoven tries to transform the energy supply to make it future-proof and sustainable.” He noted that the research considers both the software and hardware side of power systems. According to Kok, the current grid capacity scarcity in the Netherlands is a big driver for innovation and development.

“Congestion is becoming the new normal,” Kok argued. He indicated that networks are only used at full capacity for a fraction of the time. “Optimising this obviates the need for new cables,” according to the professor. What we need, then, is a new coordination system to balance supply and demand in the electricity system.

This requires a rethinking of the electricity market. Kok: “The market operations need to fuse with the system operations.” Currently the market considers the grid as a copper plate and it is up to system operations to fix imbalances. This is untenable in the long run, says Kok: “We should move toward network-aware commodity markets.”

Kok also warned that quick fixes in the short term may cause problems later. “Our solutions *now* may not be the best solutions in the long run.”

In order to find the best solutions, Kok shared parts of his latest research, in which simulation systems are expanded to incorporate different actors. Kok: “We now simulate not only grids, but also demand and supply actors and how market parties respond to dynamic pricing.”

Asked about the role of open source projects like PGM in his research, Kok replied that his department embraces open source and open data as well. “Our dissemination is mainly about making things open.”

Network calculations for enhanced capacity management by Irena Dukovska (Alliander)

After the keynote talk, Irena Dukovska shared a concrete use case of PGM in an operational setting. Dukovska, energy data expert at the System Operations department at Dutch DSO Alliander, showed how her team is using PGM to enhance capacity management.

Dukovska: “We activate flexibility from our customers to do active congestion management.” She showed how Alliander uses both current state estimation and forecasting of power flows in the near future in order to see where problems may arise.

“When a problem arises, we check what appropriate action we can take,” said Dukovska. “We can take grid solutions, such as curtailment, but preferably we take market-based solutions, such as congestion-limiting contracts or redispatch contracts.”

Duksovska shared which part of the process is handled by PGM. “We first do a common information model request. We then convert this data to PGM input data. PGM then does the required calculations and we convert the result again for further processing.” Dukovska remarked that the tools in PGM help in solving the challenges that arise, such as the low availability of measurement data, or unknown accuracy of sensor data. “Open source tools like PGM that are fast and efficient help us with tackling the challenges we face.”

Optimising reactive power flow by Niels Dirks (Enexis)

Next up, Niels Dirks from Dutch DSO Enexis shared another use case of PGM. Dirks recently graduated at TU Eindhoven and used PGM in his research into reactive power flow.

Dirks first gave a very brief explainer of his research topic. “Active power is for the useful stuff. Reactive power on the other hand is used in the network to build and maintain the electric field that transports active power.” Dirks showed that in the past, DSOs mostly *consumed* reactive power, but recently this consumption has decreased, up to the point that DSOs sometimes started *delivering* reactive power back to the TSO.

“This delivery of reactive power causes problems with voltage regulation for the TSO,” Dirks said. “Dutch TSO TenneT regularly has to switch off circuits in order to deal with the reactive power and to keep the voltage within limits.”

In order to solve these issues, Dirks investigated the feasibility of introducing inductor and capacitor banks in the grid. Dirks used PGM to model the behaviour of these banks in the grid: “I made a model of a small medium-voltage grid in PGM to run my experiments. I then investigated how the optimal solution depends on the cost of these banks.”

Dirks chose PGM as a modelling tool because of his former familiarity with the tool and the high computational performance of PGM. “With alternative tools, it would have taken far more time to run the calculations.”

Highlights and community announcements by Peter Salemink (PGM)

After these use cases, Peter Salemink hit the stage to share the progress on PGM the last semester and to look forward to the upcoming period. Salemink is the development lead of the PGM maintainers.

In the past half year, PGM added [Newton-Raphson state estimation](, which considers all measurements to be *independent* real measurements. Furthermore, an automatic tap changing algorithm was released, currently as an experimental feature. Finally, some additional conversion options are added to the data conversion package [PGM-IO](, such as custom mappings for Vision.

Concerning outreach, Salemink mentioned that they are open to provide workshops for new users and have recorded a webinar workshop which is [available on YouTube]( What is more, PGM was [presented during the open-source conference FOSDEM 2024](

Towards the end of the meet-up, Salemink invited the audience to share their opinions on the future directions of the project. This led to vibrant discussions both from the room and online. Salemink stimulated the community to think big: we want PGM to become a community-driven ecosystem, and every event that contributes to this goal is warmly welcomed.

On Power Grid Model (PGM)

Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behaviour and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.

Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analysing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimisation.

Note on authorship: the section ‘On Power Grid Model (PGM)’ is copy-pasted from the [event page]( The rest of the article is written by Thijs Meeuwisse without the use of AI tooling.