Renewable project lenders across Southeast Europe increasingly need to size debt against a range of potential revenues, as wholesale electricity prices diverge from prices captured by renewable generators. Traditionally, renewable project financing converted a limited set of assumptions into a debt capacity: expected generation was multiplied by forecast electricity prices to calculate revenue, operating costs were deducted, and the remaining cash flow indicated how much debt a project could service. That framework is still necessary, but it is no longer sufficient.
Model generation and realised prices
The analysis needs to follow the full sequence: production, captured price, curtailment, imbalance and operating costs, cash flow, DSCR and debt capacity. Each stage can materially affect the one that follows. The first input should be hourly production, because annual P50 output alone does not show when a project will generate electricity.
For photovoltaic projects in particular, generation timing determines exposure to periods of system surplus. A technology-specific captured-price curve is also required: a baseload forecast should not automatically be treated as the price a solar or wind project will receive. Matching hourly production with hourly market prices allows lenders to estimate the price actually realised.
AleaSoft argues that average market prices are no longer sufficient for photovoltaic valuation. It says captured prices, hourly production and curtailment should all be included in the assessment. Availability and curtailment must also be accounted for, since electricity that cannot reach the market cannot be valued like delivered power.
Account for operating and contract exposures
Technical availability, grid restrictions, connection conditions and contractual compensation therefore need to be reflected in cash-flow assumptions. Balancing is another layer: forecasting errors and deviations from the expected generation profile can create costs even when the gross electricity price is attractive. These factors can change the revenue available to service debt.
Contract terms form a further part of the analysis. PPAs, CfDs, floors, caps and merchant exposure should, where appropriate, be modelled hour by hour rather than compressed into a single annual average selling price. Financing ratios should be tested only after these variables have been combined.
AleaSoft highlights the difference between retaining enough cash to make scheduled principal and interest payments and meeting the DSCR thresholds set out in financing agreements. The distinction is particularly important when revenue deteriorates gradually rather than collapsing outright. A project can remain economically viable even as its financial structure becomes unsuitable.
Possible responses may include extending the tenor, reshaping amortisation, resizing debt, changing reserve requirements or refinancing, rather than abandoning the asset. The appropriate response depends on how the project’s revenue and financing constraints interact. The analysis should therefore test the structure against a range of market conditions.
Use probability-based downside scenarios
Probabilistic modelling should be central to that process. AleaSoft argues that one long-term forecast curve cannot represent the range of possible market outcomes, and advocates analysing multiple revenue scenarios with associated probabilities. For lenders, this points to a broader framework covering P50/P75/P90 generation cases, central and downside captured-price scenarios, curtailment and balancing-cost stresses, and PPA counterparty and expiry scenarios.
The analysis should also include merchant-tail assumptions, interest-rate and refinancing sensitivities, and DSCR and LLCR outcomes. Correlation between variables matters: a project should not combine pessimistic assumptions that cannot logically occur together, but adverse factors should not be treated as independent when they are related. High renewable output may coincide with depressed captured prices and increased curtailment.
That combination can produce much weaker cash flow than applying separate, modest discounts to production and price. The methodology therefore needs to move away from arbitrary conservatism and towards internally consistent downside scenarios. This approach assesses how related risks may affect the same project at the same time.
Integrate technical, market and financial analysis
Technical, market and financial advisers can no longer work in isolated workstreams. The engineer’s production model affects the market consultant’s captured-price calculation, while the grid review determines available volumes. Those results feed into the financial model, and the PPA determines how the resulting exposure is allocated.
For banks in Southeast Europe, renewable finance is becoming less like lending against a predictable infrastructure yield and more like lending against actively managed electricity-market exposure. The key figure in a credit paper may therefore no longer be a project’s average expected electricity price. It may instead be the amount of debt that remains serviceable when several plausible adverse market conditions occur at once.
