How the energy industry assesses the winter season

08.09.2026

Every year we see a lot of headlines in the media about the “hardest winter” we’re facing. They appeared last year, this year, and most likely will appear next year. The problem with these statements is that they are based not on calculations, but on a list of risks. Damaged generation, worn-out networks, dependence on imports, weather, shelling – the list always looks threatening, because the risks do not disappear anywhere. They just have different probabilities and different weights.

To understand the weight of such statements, it is worth looking at how seasonal assessments are generally carried out in the energy sector – using European examples.

What does the seasonal assessment in the EU consist of

ENTSO-E – the association of European transmission system operators, of which Ukrenergo has been a member since 2022 – issues the Seasonal Outlook twice a year, a seasonal assessment of capacity adequacy. The document itself explicitly states that this is not a forecast, but a risk assessment.

The assessment is based on the Monte Carlo method. A number of metrics are built for each “climatic year”: demand (taking into account temperature-load dependence), wind/solar/hydrogeneration, planned repairs, forced (emergency) downtime, cross-border flows. The “Winter Outlook 2025/2026”, for example, uses 36 climate projections consistent with the SSP2-4.5 climate change scenario.

Several indicators are calculated from this distribution:

• LOLE (Loss of Load Expectation) – the expected number of hours per season when available generation, together with imports, is statistically insufficient to meet demand.
• LOLP (Loss of Load Probability) – the probability that a shortage will occur during a particular week.
• EENS (Expected Energy Not Served) – the expected amount of energy not delivered to consumers.

Key to understanding: non-zero LOLE does not mean a blackout. It means that at certain hours it will be necessary to attract reserves – strategic capacities outside the market, imports, restrictions of individual consumers.

Where does this approach have a limit

However, this approach has limits. The probabilistic model is built on the assumption that accidents are random and approximately independent of each other.

But in Ukrainian conditions this is not entirely true. We have another variable – massive shelling by Russia. They are not random, but coordinated and aimed precisely at the most critical nodes – large stations, main substations, power output nodes, often – at the moment of maximum load.

Such an event cannot be correctly entered into a model that considers failures to be independent: it is either included with too low a weight, or is completely excluded from the calculation.

The Ukrainian analytical center DiXi Group tried to apply the ENTSO-E methodology to the Ukrainian summer, changing the assumptions not only about the temperature, but also about the scale of new damage: from “no shelling, moderate weather” to “destruction of the shunting generation continues”. The result showed the limit of the method: in the most difficult scenario, it was not possible to estimate the undelivered energy – the dependence on specific days and the scale of the strikes turned out to be too great for the probabilistic model. And for the regions along the front line, the researchers completely abandoned the probabilistic assessment: there the deficit is determined not by statistics, but by the fact of hostilities, and it should rather be considered practically guaranteed than “99% probable”.

The winter preparations are arranged in a similar way: the government and Ukrenergo operate with optimistic, basic and pessimistic scenarios tied to three factors – weather, intensity of shelling, level of preparation. And the factors reinforce each other.

What does this mean for business and communities

No matter how detailed the analysis method is, the honest answer to the question “what will the winter be like” is this: it is impossible to calculate the exact probability for each region, and the closer to the front line, the less statistics help in this. Therefore, the working strategy is not to wait for a single forecast number, but to plan according to a pessimistic scenario.

Businesses and communities can calculate their own, smaller-scale analogue of such an assessment. This requires three things:

• The first is to know your critical nodes: which processes stop first, which cannot be turned off at all, and which will withstand a pause.
• The second is to understand how long these nodes can withstand without the network: hours, days, weeks. In essence, this is the same principle behind EENS, only calculated for your own facility, and not for the power system as a whole.
• The third is to reserve by priority, not evenly.

The question “what kind of winter will it be” should be asked differently – and what kind of winter are you ready for?

Evgeny Korf, CEO of the international engineering and industrial consortium Energo-Plus