Paid for power consumption
05/12/2026Several households in the district of Schweinfurt were able to rejoice: on a few days in April and May 2026, they received money thanks to negative electricity prices. This market phenomenon was observed by a project team.
Since June 2025, Stadtwerke Schweinfurt, the Chair of Information Systems and AI in Business at the University of Würzburg under the direction of Professor Gunther Gust and other project partners have been investigating how private households deal with dynamic electricity tariffs in everyday life. Around 65 people from the district of Schweinfurt are taking part in the field trial.
The focus is not primarily on the question of how much money can be saved, but whether the effort is worthwhile for the participants - and how their usage behaviour develops over time.
On several days, the participants witnessed a remarkable market phenomenon: on the last weekend in April and the first weekend in May, electricity prices fell so sharply into negative territory for several hours that households received money for their electricity consumption.
Lowest value of around minus 40 cents per kilowatt hour reached
The effect was particularly evident on 1 May: Due to a high feed-in from renewable energies and a simultaneous low grid load, the day-ahead prices on the electricity exchange were negative between 10 am and 5 pm. Between 12 noon and 4 pm, wholesale prices fell so sharply that even after the addition of grid fees, taxes and levies, the end customer price also slipped into negative territory - with a low of around minus 40 cents per kilowatt hour, the lowest value in recent history. Exchange prices were also negative at times on 25 and 26 April and 2 and 3 May, making them correspondingly favourable for participants.
"One participant with an electric car and wallbox achieved a credit of around 5 euros on 26 April simply by charging during the midday hours," reports Justus Ameling, research assistant at Professor Gust's Chair. "There is also a second effect that further increases the value of these hours: At the end of the charging process, a fully charged vehicle battery is available with enough energy content for a few journeys."
Those who can use their energy flexibly therefore benefit twice over during such hours - through the immediate remuneration and a fully charged battery for the coming days. However, Ameling points out one caveat: "We also see that not all participants have taken advantage of the prices - either because they missed the opportunity or simply don't have a large number of flexible electricity consumers."
Negative electricity prices: The trend is rising
Negative electricity prices are no longer an isolated occurrence: in 2025, they occurred around 570 times on the German electricity exchanges - and the trend is rising. The multiple negative price phases at the end of April and beginning of May 2026 also fit into this picture.
With the increasing expansion of renewable energies, such hours are likely to increase further in the coming years. "It is precisely these effects, the behaviour of households and their tariff decisions that we want to systematically investigate in the field trial," explains Professor Gunther Gust.
Background to the pilot project
Dynamic electricity tariffs link the end customer price to the wholesale prices of the electricity exchange on an hourly basis. A smart meter that records and transmits consumption data to the hour is a prerequisite for use. Households can use an app to track the current prices and adjust their consumption accordingly.
Since 2025, all energy providers in Germany have been legally obliged to offer dynamic tariffs. The scientific monitoring of the Schweinfurt pilot project provides valuable insights into how these tariffs prove themselves in practice and which households benefit in particular. After completion of the project in summer 2026, the tariff offer is to be stabilised. Interested parties can obtain information directly from Stadtwerke Schweinfurt.
Contact
Prof Dr Gunther Gust, Head of Chair of Information Systems and AI in Business, gunther.gust@uni-wuerzburg.de
