Reconstructing the merchant revenue from trading wind and solar power in Europe

In 2024, we wrote about the pressures facing the renewables business case: falling day-ahead prices, rising imbalance costs, and a widening gap between what a solar or wind asset could theoretically earn and what it actually earns.

Two years on, we went back to find out how these dynamics evolved. In this article, we trace how low-price hours and capture prices are shifting across European markets, and rebuild the Profit and Loss (P&L) to quantify the impact on short-term power trading revenue.

Low and negative power prices

We begin by looking at the frequency of hours with prices below 0.5 EUR/MWh across European markets, comparing 2025 and 2026 year-to-date data.

So far in 2026, Spain leads Europe with 1,099 hours below 0.50 EUR/MWh; 650 of these are negative, more than any other zone we track. Portugal and Greece follow the same pattern. Germany-Luxembourg, the Netherlands, Poland, and Belgium cluster far lower.

Compared to 2025, Spain, Portugal, Greece, and France all saw 100–300+ hours of sub-0.50 EUR/MWh pricing. In Spain and Portugal, that’s due to high hydro reserves from heavy early-2026 rainfall; in Greece, it’s likely because rapid solar capacity expansion is outpacing flexible assets. Most CWE and broader-scope zones are broadly stable.

Sweden (SE1 – Northern Sweden, SE2 – North-central) and Finland moved in the opposite direction: sub-0.50 EUR/MWh hours are falling there.

To sum up, two trends have become apparent: low-price hours are climbing in Spain, Portugal, and France, while falling in bidding zones such as Sweden (SE1, SE2) and Finland, which used to lead on this metric.

Solar and wind exposure to low-price hours

We next examine how much of each technology’s output clears in those low-price hours, comparing the period ending August 2026 with the same period in 2025.

The split from the previous section repeats here. Greek solar now sees 23.2 percentage points (pp) more of its output clearing below 0.50 EUR/MWh than a year ago; Portuguese solar is up 17.4 pp, and Spanish solar is up 7.6 pp. Nordic solar moved the other way entirely, down 13-16pp.

Wind tells the same story, just less severely. Portugal wind gained 11.9 pp, the largest move we saw in either direction, while Nordic wind kept declining, down 14–15pp. Solar is clearly the technology under the most pressure in the deteriorating cluster, while wind is holding up comparatively well.

The effect on capture prices

Thirdly, we look at capture prices to see how the shifts above show up in what wind and solar assets actually earn.

The year-to-date capture price picture is more mixed than the low-priced hours suggest. Greek solar is down 11.8 EUR/MWh, the sharpest fall we measured. Spanish and Portuguese solar are close to flat, down 1.4 EUR/MWh and 0.9 EUR/MWh, respectively. Capture prices for wind in Greece, Spain, and Portugal fell between 4 and 8 EUR/MWh.

France added 208 hours below 0.50 EUR/MWh year-to-date, producing more wind and solar in low-priced hours, yet both technologies earned more than in 2025 year-to-date. Solar is up 4.4 EUR/MWh and wind is up by 7.4 EUR/MWh. The explanation is that the French baseload price rose by 10 EUR/MWh, which is offsetting the increase in low-priced hours.

In the recovering cluster, the moves are large and positive, but not symmetric: Swedish and Finnish solar is up between 6.6 EUR/MWh and 18.7 EUR/MWh, while wind is up between 18.8 EUR/MWh and 22.4 EUR/MWh.

Hence, capture price alone cannot tell you whether an asset earned more because the market rose, or less because its own profile is worth less. To separate the two, we rebuilt the P&L.

Reconstructing fully merchant revenue from wind and solar

The methodology

To quantify the impact of cannibalization and other cost factors, we rebuilt the P&L for a wind or solar asset. We started from a fixed reference price: what the asset would earn if every MWh sold at a single, constant number. Then, we applied four adjustments:

• Resource: how much the asset produces, valued at the reference price. This is a function of site quality (capacity factor).
• Market price: whether power is generally dear or cheap in that country.
• Cannibalization: the discount an asset takes because it produces in the same hours as every other asset of its type, and prices sag in those hours.
• Imbalance: the cost of the gap between the day-ahead forecast and what the weather actually delivers.

The result is a euros-per-megawatt view that lets us compare countries on a standardized basis, without incorporating curtailment data.

Two examples

The examples below show how these three levers can combine differently, and why the P&L bridge matters more than the capture price alone. Indexing each component to the fixed reference price puts every country and technology on the same scale and lets us disentangle how much of a P&L change is explained by market price, cannibalization, or imbalance costs, rather than reading a single net number that blends all three.

Spanish solar’s realized value fell from 38.1% of the reference price in 2025 to 35.7% year to date in 2026. Market price actually moved in the asset’s favor, adding 2.4pp, but cannibalization more than offset this, costing 3.9pp as growing solar penetration pushed down prices during the hours when solar produces. Imbalance added a further, smaller drag of 0.9pp. Therefore, solar cannibalization can be seen as a driver of the decline in Spain.

Finnish wind moved sharply in the opposite direction, rising from 14.3% to 40.2%. Market price drove most of that gain, adding 24.0pp as Nordic power prices recovered. Cannibalization took a further 2.3pp, while imbalance improved by 4.3pp. Here, the gain was almost entirely market-driven, with cannibalization only a modest offsetting factor.

These two cases show that the dominant lever isn’t always the same: for Spanish solar, cannibalization drove the decline; for Finnish wind, market price alone explains most of the increase. That’s a useful corrective to reading capture price movements. A rising or falling top-line number can reflect very different underlying causes depending on the market and technology.

The evolution of imbalance costs across Europe

Imbalance costs are the fourth lever in the P&L, and the one most directly tied to forecast quality. Using a blended methodology that combines TSO settlement data with customer data, we’re seeing meaningful differences by country. For instance, the Netherlands currently has the highest solar imbalance costs in Europe, while Romania leads in wind at 22 EUR/MWh.

These country-level dynamics deserve more space than a single article can give them. Over the coming weeks, we’ll publish a series of posts covering imbalance costs market by market. Follow along on LinkedIn for the full breakdown.

Forecasting strategies to protect trading profits

In conclusion, we see that margins for wind and solar asset owners are continuing to shrink. Cannibalization is eroding capture prices, imbalance costs persist, and subsidy schemes increasingly withhold support during negative-price hours.

Maintaining revenue now requires a more sophisticated trading setup. We note two mitigations for renewable asset traders to protect trading profits:

• Closing positions intraday: With intraday liquidity rising across Europe and 15-minute products now standard, more traders close their imbalance positions before delivery instead of leaving them to the imbalance price.
• Multi-market optimization. Trading day-ahead alone is no longer profitable enough. A more robust strategy combines selling day-ahead, committing to aFRR capacity, and holding back for intraday to diversify revenues.

Both approaches depend on accurate power and price forecasts, with probabilistic forecasting specifically becoming more popular. Instead of a point forecast, a probabilistic forecast shows the distribution around the number through quantiles. Traders can then match volume decisions to their risk appetite. For example, they can commit a conservative quantile to aFRR capacity and day-ahead, and trade the remaining uncertainty intraday. We’ve covered this approach in more detail in our article on probabilistic wind and solar power forecasting for bidding into aFRR.

Would you like to explore what a multi-market, probabilistic approach would look like for your portfolio? Reach out, and we’ll work through it with you.