European Electricity Market Prices: July 2026

Written by: Olivier Lam, Physical AI Team, Jua.ai AG

Key Takeaways for EU Power Traders

• European day-ahead electricity prices in July 2026 remain elevated and volatile. Italy and Germany show the highest zonal averages, driven by gas-fired plants setting the marginal price.
• Negative-price hours have more than doubled year-on-year in solar-heavy markets. Renewable portfolios without accurate forecasts face growing imbalance exposure.
• A four-percentage-point improvement in day-ahead wind or solar forecast accuracy can deliver €1.5–3 M in annual savings per GW through lower imbalance costs and stronger auction positioning.
• Jua’s EPT-2 foundation model outperforms ECMWF HRES across all lead times and key variables. The Athena agent layer turns those forecasts into trading decisions within minutes.
• Quantify the P&L impact on your portfolio by benchmarking EPT-2 head-to-head against your current provider.

How EU Day-Ahead Power Prices Are Set

Under the European merit-order principle, generation units are ranked and dispatched from the lowest to the highest marginal cost, with all accepted units receiving the single market-clearing price set by the marginal unit, the last plant needed to meet demand. Renewables such as wind, solar, and hydro sit at the bottom of the merit order with near-zero marginal cost. Nuclear usually follows. Gas-fired plants, with fuel costs of €101–112/MWh in 2025, sit near the top and set the clearing price whenever demand exceeds what cheaper sources can supply.

Gas-fired plants, despite their limited share of EU generation, still set the marginal price in roughly 50% of hours because they provide flexibility. That share varies sharply by zone and reflects each market’s generation mix. Gas sets electricity prices in only 7–9% of hours in Spain, where renewables dominate. Gas is typically the marginal technology in Italy, which lacks comparable renewable or nuclear capacity. Across all researched European countries, coal- and natural gas-fired power plants set the price for only 40 per cent of all hours.

The day-ahead auction under Single Day-Ahead Coupling (SDAC) determines the official zonal market-clearing price for each European bidding zone and the resulting scheduled cross-border flows for the following day. Day-ahead prices then act as the benchmark for most forward contracts traded across Europe. The 2024 EU electricity market reforms (Regulation (EU) 2024/1747) kept the marginal pricing framework and expanded two-way Contracts for Difference and Power Purchase Agreements to stabilize revenues for low-carbon generators.

Why EU Power Prices Have Moved in 2026

Wholesale electricity prices increased across many EU countries in 2025 compared to 2024. Sharp price spikes during morning and evening hours, when gas generation share exceeded 20%, acted as the main driver. That pattern has continued into 2026.

During periods of geopolitical tension in 2026 linked to LNG flow disruptions, day-ahead electricity prices exceeded €120–150/MWh in Italy and Germany while remaining closer to €60–80/MWh in France. TTF front-month gas prices fluctuated between €20–30/MWh and peaks above €60–70/MWh in recent months of geopolitical tension, directly driving spikes in day-ahead power prices in gas-sensitive markets.

In Germany in 2025, wholesale electricity prices were higher during high gas-use periods than during hours with plentiful solar generation. That structural bifurcation is widening as installed renewable capacity grows. In Europe's weather-driven energy markets, traders are turning to AI and machine-learning tools designed not to predict temperatures and precipitation, but to forecast the forecast, specifically shifts in the ECMWF two-week outlook that reprice risk around heating demand, renewable output, and system tightness.

Current Day-Ahead Electricity Prices by Zone

These structural dynamics show up as concrete price differences across European bidding zones. The table below presents indicative recent day-ahead wholesale prices by major bidding zone, sourced from the ENTSO-E Transparency Platform via euenergy.live, alongside 2024 baseline ranges from IEEFA.

Italy currently shows the highest day-ahead price among major European zones, reflecting the prominent role gas plays in setting its prices. Finland and Estonia sit at the opposite extreme, driven by hydro and wind surplus in the Nordic-Baltic cluster. The spread between the highest and lowest zones exceeds €137/MWh, a direct consequence of transmission constraints and divergent generation mixes.

Retail prices sit substantially above these wholesale figures. The energy supplier's charge for electricity consumed accounts for a substantial share of the household electricity bill in 2024. The remaining share consists of network charges plus taxes and levies set at national level. As of September 2025, Germany recorded a household electricity price of $0.43/kWh while Belgium's price was lower at approximately €0.33/kWh, implying a retail-to-wholesale multiplier of roughly 3–4× at current wholesale levels. Network charges, policy levies, and VAT together account for 50% or more of the final retail electricity price in many European countries.

Compare EPT-2 on your bidding zone to your current forecast provider in a live head-to-head accuracy test.

Negative Electricity Prices in Europe

Negative prices occur when supply exceeds demand, typically during midday solar peaks or high-wind periods when must-run generation cannot be curtailed fast enough. Their frequency is accelerating sharply.

EU-27 day-ahead power markets recorded 1,223 negative-price hours in Q1 2026, more than double the total in Q1 2025, according to Ricardo (part of WSP Group) using ENTSO-E Transparency Platform data. The distribution is uneven:

• Spain recorded 397 negative-price hours in Q1 2026, up from 48 hours in Q1 2025.
• Greece recorded 138 negative-price hours in Q1 2026 after zero hours in Q1 2025, the largest single year-on-year increase among EU bidding zones.
• Germany recorded between 40 and 50 negative-price hours in each Q1 from 2024 to 2026, well below its Q1 2019 peak of 131 hours. However, in April 2026, Germany recorded negative day-ahead prices in 123 of 720 hours (17.1%).
• Italy has recorded few negative-price hours in Q1 periods.

In Germany in April 2026, a substantial share of solar generation occurred during negative-price hours. A generator that failed to forecast those hours accurately, and therefore did not curtail, shift, or hedge output in advance, absorbed the full negative clearing price on that volume. Accurate wind and solar forecasts are the primary tool for reducing that exposure. A portfolio that knows a negative-price window is coming can reposition before the auction closes.

Forecast Accuracy Impact on P&L

That repositioning capability has a measurable economic value. The link between forecast skill and trading P&L is quantifiable. A four-percentage-point improvement in day-ahead wind or solar forecast accuracy, achievable by switching from a legacy NWP pipeline to a state-of-the-art AI foundation model, translates directly into lower imbalance costs, better auction positioning, and reduced negative-price exposure.

These figures are anchored to typical European hedging and imbalance penalty structures. Jua's forecasts carry an estimated $1.5 million P&L impact per gigawatt annually in European energy markets, translating to hundreds of millions for large portfolios. Customers operating multi-GW portfolios scale these economics linearly. The underlying model performance that drives these savings is documented in peer-reviewed technical reports: EPT-2 (arXiv:2507.09703) and EPT-1.5 (arXiv:2410.15076).

The mechanism is direct. Imbalance settlement in European balancing markets penalizes deviations between nominated and actual generation. A wind portfolio that over-nominates into a negative-price hour pays the imbalance price on the excess. A portfolio with a more accurate forecast nominates correctly, avoids the penalty, and in some market designs captures the spread between the day-ahead and intraday price as the market reprices toward the accurate forecast. The ECMWF two-week outlook is the definitive reference point for traders repricing risk around heating demand, renewable output, and system tightness, which means that whoever forecasts the forecast revision first captures the spread before the market moves.

Run a 5-minute benchmark and test your region and variable against 25+ models live.

Jua for Energy: EPT Models and Athena Agent

Jua is a foundation model and agent company, with Jua for Energy as its first applied product. The structure mirrors Anthropic's relationship to Claude Code, a horizontal AI platform that powers a flagship vertical product. EPT, the Earth Physics Transformer, is a general spatiotemporal transformer foundation model that learns the governing physics of complex systems directly from observational data. Athena is an AI agent instrumented with the Jua for Energy tool surface. The atmosphere is the first physical system EPT has been fine-tuned for. Energy trading is the first market Athena has been deployed in.

Inside Jua for Energy, EPT-2 is the deterministic flagship. It outperforms ECMWF HRES on every lead time and on 10 m wind, 100 m wind, 2 m temperature, and surface solar radiation across the full 0–240 hour range, benchmarked against more than 10,000 real ground stations on open-source StationBench with no post-processing. EPT-2e, the ensemble variant, beats the 50-member ECMWF ENS mean on both RMSE and CRPS at virtually every lead time. Both results are published in arXiv:2507.09703. Jua's models natively forecast at up to 5 km resolution over Europe.

The 25-model benchmarking surface puts EPT-2, EPT-2e, ECMWF HRES, ECMWF ENS, ECMWF AIFS, NOAA GFS, Microsoft Aurora, GFS GraphCast, DWD ICON, and 16 additional models on a single platform with a unified schema. A meteorologist can run a head-to-head accuracy comparison on their most stakes-relevant region and variable in under 30 seconds. Aurora and GraphCast run on the Jua platform as guests, so the comparison is built in.

Athena turns raw physics predictions from EPT-2 into trading decisions by reading market context and modeling participant behavior. A trader types a natural-language request such as “what is the 100 m wind forecast spread across models for northern Germany tonight?” or “backtest a wind-ramp strategy on EPT-2e over the last two winters” and Athena returns the answer, the underlying widget, or the full backtest report. Typical queries resolve in approximately 90 seconds. Backtests complete in approximately 5 minutes. Trading houses and quant desks describe Athena as “another headcount, for free.”

Jua for Energy does not replace ECMWF. It displaces the plumbing around it. The 7–9 a.m. manual prep routine, downloading grib files, processing them through brittle in-house pipelines, and waiting for the meteorologist's briefing, compresses into a single workspace that refreshes on every new model run. Divergence alerts fire the moment two models disagree and correction alerts fire the moment a model revises its own output. Customers who need programmatic access install the Python SDK with pip install jua and pipe forecasts directly into their own trading and risk systems via the REST API with Apache Arrow support. Run a live benchmark now at athena.jua.ai.

See Athena in action and explore EPT-2e ensemble forecasts with your own portfolio data.

What to Watch in EU Power Markets Next

Intraday volatility is the next frontier for traders. As negative-price hours multiply and renewable penetration continues to grow, the value of rapid-refresh forecasts will compound. EPT-2 RR updates up to 24 times per day, compared with the two to four daily runs of traditional NWP.

Jua for Energy is expanding power-forecast coverage across additional European bidding zones on a weekly basis. The platform is adding solar, wind onshore, wind offshore, load, and residual load to markets beyond the current five, Germany, Great Britain, France, the Netherlands, and Belgium. Traders positioned on zones currently outside that coverage should expect live power forecasts to become available in the near term.

Frequently Asked Questions

How often do negative prices occur in Germany in 2026?

Germany recorded between 40 and 50 negative-price hours in Q1 2026, consistent with Q1 2024 and Q1 2025 and well below its Q1 2019 peak of 131 hours. However, April 2026 showed a sharp acceleration. More than 17% of hours cleared at negative prices, with most of those hours falling between 10:00–16:00 CEST during peak solar generation. In full-year 2025, Germany recorded approximately 575–576 negative-price hours with a mean of -10.89 €/MWh and a record low of approximately -250 €/MWh. Midday solar generation exceeding demand, particularly on weekends and public holidays when industrial consumption is low, acts as the primary driver. Accurate solar and wind forecasts are the primary tool for avoiding imbalance exposure during these windows.

Which bidding zone currently shows the highest day-ahead price?

Italy currently records the highest day-ahead price among major European bidding zones, at approximately €152/MWh as an average across its six internal sub-zones. This reflects Italy's structural dependence on gas-fired generation, where gas is typically the marginal technology. During periods of geopolitical tension and LNG supply disruption in 2026, Italian day-ahead prices have exceeded €150/MWh while French prices remained closer to €60–80/MWh, a spread driven by France's nuclear-dominated generation mix. At the opposite extreme, Finland and Nordic-Baltic zones with surplus hydro and wind capacity have recorded day-ahead prices below €15/MWh in the same period.

What is the retail-to-wholesale multiplier in major EU markets?

The retail-to-wholesale multiplier in major EU markets typically ranges from 3× to 5× at current wholesale price levels, though it varies significantly by country and contract type. As of September 2025, Germany recorded a household electricity price of $0.43/kWh while Belgium's price was lower at approximately €0.33/kWh. At a wholesale day-ahead price of €119/MWh, approximately $0.13/kWh, the implied multiplier is roughly 3.3×. Network charges for transmission and distribution, policy levies such as renewable support schemes and capacity mechanisms, VAT, and other national taxes explain most of the gap. In many European countries, these non-energy components account for 50% or more of the final retail bill. The energy supplier's own margin and procurement costs account for a substantial share of the household bill on average across the EU. Seventy-three percent of EU households are on fixed-price contracts, which insulate them from short-term wholesale movements but also prevent them from capturing wholesale price drops.

How does forecast skill directly affect trading P&L?

Forecast skill affects trading P&L through three primary channels. First, imbalance settlement, because European balancing markets penalize deviations between nominated and actual generation. A wind or solar portfolio that nominates incorrectly into the day-ahead auction pays the imbalance price on the deviation volume. A four-percentage-point improvement in day-ahead forecast accuracy reduces that deviation volume and the associated penalty cost.

Second, auction positioning, because a trader with a more accurate renewable generation forecast can submit bids that reflect the true supply curve. That trader captures better prices in the day-ahead and intraday auctions instead of correcting positions later at unfavorable prices.

Third, negative-price avoidance, because a portfolio that accurately forecasts a negative-price window can curtail, shift, or hedge output before the auction closes. That portfolio avoids the full negative clearing price on that volume. The combined effect of these three channels is approximately €1.5 M per year per GW of wind capacity at a four-percentage-point accuracy gain and approximately €3 M per year per GW of solar capacity at the same gain. For a 5 GW wind portfolio, that improvement translates to €7.5 M per year from a single model upgrade. Jua for Energy supplies EPT-2 and EPT-2e, both benchmarked against more than 10,000 real ground stations and documented in peer-reviewed technical reports on arXiv, alongside 25+ models on a single platform for continuous accuracy surveillance.