Renewable Energy Project Finance Modeling

This page brings together my individual coursework for INAF U6326, Renewable Energy Project Finance Modeling at Columbia SIPA in spring 2025, taught by Haydn Palliser and Goksenin Ozturkeri.

The course case used a largely intact document set from a recently constructed wind project, with confidential information redacted. The work summarized here is mine; the underlying course documents and model inputs are not redistributed.

Separate assignments, not one transaction

The work came as a sequence of individual assignments:

• Contract summaries and issue spotting for the credit agreement, power purchase agreement, and construction agreement
• Staged modeling exercises covering operating cash flow, debt sizing, debt sculpting, taxes, scenarios, and sensitivities
• A separate tax exercise comparing PTC and ITC mechanics
• A final individual wind-project financial model that brought the operating and financing pieces together

That distinction matters. The contract reviews, tax exercise, and final model tested related skills, but they were not stages of one transaction and should not be made to look like one.

The final individual model

The final model used a 30-year useful life and a 20-year PPA followed by merchant exposure. It linked generation, operating costs, PTCs, tax depreciation, cash flow available for debt service, and equity cash flow. Debt amortization was sculpted to a 1.40× DSCR in the P50 base case with full repayment within 20 years, and a P99 case provided a separate downside check.

The output page compared thirteen scenarios. Net capacity factor produced the largest return swings in my submitted analysis. Under 20% curtailment, minimum DSCR fell below 1.0×. The covenant consequence was no longer a red cell buried in a sensitivity table; it became part of the story the model told.

Why the dependencies mattered

A model is useful when its dependencies are explicit. Generation and price drive revenue. Revenue and operating costs determine cash flow available for debt service. That cash flow constrains debt sizing and repayment, and the debt profile changes distributions to equity.

Once those links are auditable, the model can explain why a scenario passes or fails instead of merely reporting an IRR. Contract language also becomes easier to read: dates, performance obligations, reserve requirements, and coverage tests are inputs and risk allocations, not decorative legal terms.

Where the claim ends

This was individual coursework based on a redacted real-project case supplied by the course. I did not advise, finance, or underwrite the transaction. Some inputs were simplified for teaching; the source documents, counterparties, and confidential details remain private. Nothing here is investment advice.