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Temporal and locational variations in power generation result in relatively large fluctuations in the power supply and power prices. Grid infrastructure providers are increasingly forced to intervene in order to balance supply and demand and avoid power outages. Consequently, the EU Commission is assessing a possible split of the German uniform price zone and the day-ahead market into smaller price zones. Researchers at the Technical University of Munich (TUM) have shown that smaller price zones would have little effects on the power price or re-dispatch measures. By contrast, the use of nodal pricing would reduce overall costs for providing energy by 9 percent.
What political discussions are taking place on this topic, and what does your research show?
Current discussions revolve around dividing Germany into two to four bidding zones instead of the current uniform zone. The EU Commission has ordered a bidding zone review to reassess the price zones in the EU. In our study we used the data set from the bidding zone review to analyze trends in power prices and the costs of re-dispatch measures under the assumption that Germany were divided into the proposed bidding zones. Never before was such a comprehensive data set available for analysis.
In addition, we calculated local (nodal) prices. Under a zonal price system, a single hourly price applies for the entire bidding zone. By contrast, a nodal system sets an individual price for each node.
How much would a nodal pricing rule reduce the total power costs?
With power price zones, it was evident that there would be practically no difference between the individual zonal prices. At the same time, the price variance and re-dispatch costs would not decrease significantly compared to the power price in a German uniform price zone. Several experts had expected a stronger impact from a zonal split. However, we do not see this in the data set provided for the bidding zone review.
With our calculations we were able to show that the lowest total costs would result if Germany were to use nodal pricing. Compared to the uniform price or zonal pricing, the total costs would be around 9 percent lower. That is in particular due to the fact that the market mechanism takes network restrictions into account and that it succeeds in efficiently allocating the available resources. As a result, costly re-dispatch measures are largely avoided.
To understand these effects, one must consider how power pricing currently works in Germany.
Power prices across Europe are determined in a day-ahead auction. Across Europe there are various price zones, each with its own electricity prices. The zones can be entire countries. However, some countries, such as Italy, are divided into several zones.
What is the situation in Germany?
Germany has only one price zone. It may happen, however, that large amounts of wind energy are generated in northern Germany, for example, while demand is particularly high in the south. But due to the limited grid capacity, not enough power can be transmitted from the north to the south. The uniform price for Germany determined in the day-ahead auction does not take this into account.
What problems result from the uniform price?
Under the current pricing mechanism, there is little incentive to adjust consumption on the demand side when electricity is in short supply – because the price at locations where power is scarce is the same everywhere in Germany.
In the example I mentioned, the production of wind power needs to be throttled in the north while expensive gas-fired power stations are fired up in the south to cover demand there. These re-dispatch measures are very costly. In 2023 they totalled 3.1 billion euros. That amount was passed on to consumers.
How could that be changed?
By replacing uniform prices for large power pricing zones by locational prices set for individual nodes in the grid. This system operates in many countries around the world, including the USA. Texas has more than 4000 nodes, for example. Due to the fluctuating power supply, some nodes have excess supply at some times and less at others. This results in temporary downward or upward price movements at those locations.
When prices rise, there would be an incentive for the industry to reduce demand at these nodes. Either production would be shifted elsewhere or energy storage would be utilized. The demand-side flexibility would help grid operators to stabilize the network and substantially reduce the need for re-dispatch measures
About Martin Bichler:
Martin Bichler is a Professor of Decision Sciences and Systems at the TUM Department of Computer Science. His research focuses on mathematical optimization, machine learning and market design and, consequently, forms an interface between computer science and economic sciences. Prof. Bichler is a member of the Bidding Zones Review Consultative Group, a European committee that is currently reviewing the configuration of European electricity price zones.
Prof. Dr. Martin Bichler
Technical University of Munich
Chair of Decision Sciences and Systems
Tel: +49 89 289 17500
bichler@in.tum.de
www.tum.de
Ahunbay, M. Bichler, and J. Knoerr. Pricing optimal outcomes in coupled and non-convex markets: Theory and applications to electricity markets. Operations Research, 2024. https://doi.org/10.1287/opre.2023.0401.
J. Knörr, M. Bichler, and T. Dobos. Zonal vs. nodal pricing: An analysis of different pricing rules in the German day-ahead market. Working Paper at https://arxiv.org/abs/2403.09265, 2024, supported by the BMBF project SynErgie (https://synergie-projekt.de/).
https://www.tum.de/en/news-and-events/all-news/press-releases/details/splitting-...
Martin Bichler, Professor of Decision Sciences and Systems
Astrid Eckert
© Astrid Eckert, Muenchen (Free for use in reporting on TUM, with the copyright noted)
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