In Southeast Europe, financing renewable projects increasingly requires lenders to assess a range of potential revenues rather than one central forecast. Wholesale electricity prices and the prices captured by renewable generators are diverging. As a result, the average expected electricity price alone may no longer establish how much debt a project can support.
The traditional approach starts with expected generation multiplied by forecast electricity prices, then deducts operating costs. The resulting cash flow sets the amount of debt the project can service. That framework remains necessary, but it does not by itself account for how and when renewable output earns revenue.
A more complete debt-sizing chain runs from production to captured price, curtailment, imbalance and operating costs, cash flow, debt service coverage ratio (DSCR) and debt capacity. Each stage can materially change the next. The first input must therefore be hourly production: annual P50 output does not show when electricity is generated, particularly for photovoltaic projects exposed to periods of system surplus.
Hourly prices, deliverable output and contracts
Lenders also need a technology-specific captured-price curve rather than automatically applying a baseload forecast to solar or wind generation. Matching hourly production with hourly market prices gives an estimate of the price actually realised. AleaSoft argues that average market prices are no longer sufficient to value photovoltaic projects and that assessments should include captured prices, hourly production and curtailment.
The next layer is availability and curtailment: electricity that cannot reach the market cannot be valued like delivered output. Technical availability, grid restrictions, connection conditions and contractual compensation must therefore become cash-flow assumptions. Forecasting errors and deviations from the expected generation profile can also create balancing costs, even when the gross electricity price remains attractive.
Contracts determine how those exposures reach the project. Power purchase agreements (PPAs), contracts for difference (CfDs), floors, caps and merchant exposure should be modelled hour by hour where appropriate, not reduced to a single annual average selling price. Financing ratios should be tested only after production, prices, deliverable volumes, costs and contractual terms have been combined.
Debt tests and consistent downside scenarios
AleaSoft distinguishes between having enough cash to pay scheduled principal and interest and meeting the DSCR thresholds in a financing agreement. That gap matters especially when revenue declines gradually rather than collapsing. A project can remain economically viable even as its financial structure becomes unsuitable, potentially calling for a longer tenor, revised amortisation, less debt, different reserve requirements or refinancing rather than abandonment.
AleaSoft also argues that one long-term forecast curve cannot represent the full range of possible market outcomes. It advocates multiple revenue scenarios with associated probabilities. For lenders, such a framework can combine P50/P75/P90 generation cases; central and downside captured-price scenarios; curtailment and balancing-cost stresses; PPA counterparty and expiry scenarios; merchant-tail assumptions; interest-rate and refinancing sensitivities; and DSCR and loan life coverage ratio (LLCR) outcomes.
Those assumptions must reflect correlation. A model should neither combine pessimistic variables that cannot logically occur together nor treat adverse variables as independent when they are connected. High renewable output can coincide with lower captured prices and greater curtailment, producing substantially weaker cash flow than separate small discounts to generation and price would indicate. Downside scenarios therefore need internal consistency rather than arbitrary conservatism.
Linked technical, market and financial models
This approach also links work that technical, market and financial advisers have traditionally handled separately. The engineer’s production model feeds the market consultant’s captured-price calculation, while the grid review establishes available volumes. Those findings shape the financial model, and the PPA determines how the resulting exposure is allocated.
For Southeast European banks, renewable lending is consequently becoming less like lending against a predictable infrastructure yield and more like lending against an actively managed electricity-market exposure. The decisive figure in a credit paper may be the debt that remains serviceable when several plausible adverse market conditions occur together, rather than the project’s average expected electricity price.