Compound scenario bankability model for a 1 GW solar PV project in Nigeria
Description
This dataset is the live spreadsheet model behind the compound bankability analysis reported in the related article on a proposed 1 GW utility-scale solar photovoltaic project in the Federal Capital Territory of Nigeria. The model evaluates the project under four simultaneous sources of uncertainty rather than one at a time, as a full factorial of four levers at three levels each, giving 81 deterministic scenarios to which no probabilities are assigned. The levers are energy yield at the P50, P90, and P95 exceedance levels, grid curtailment at 0, 5, and 10 percent, contracted tariff at 0.115, 0.110, and 0.105 US dollars per kilowatt hour, and capital expenditure at 845, 887, and 930 million US dollars. The headline measure is the unlevered project internal rate of return, with levered equity returns and debt service coverage reported on separate sheets. The workbook has 26 sheets and 12,713 formulas, every reported figure is a live formula with no stored constants beyond the documented inputs, and each formula also carries its computed value so the numbers display without recalculation. It reproduces every financial quantity in the article, including the four reference cases, the band counts, the driver decomposition, the hurdle-rate sensitivity, the replacement fiscal regime, the phased and levered variants, and the benchmark notes. The parameter values originate in a proprietary feasibility study that cannot be shared, so only non-confidential inputs and the derived outputs are included, matching what the article reports. Benchmark and contextual material is drawn from public sources, each listed with its verification note on the Source_Register sheet. The workbook uses standard spreadsheet functions only, with no macros and no external links, and opens in Microsoft Excel, LibreOffice Calc, and compatible applications.
Files
Steps to reproduce
1. Open the workbook in Microsoft Excel or LibreOffice Calc. Every figure recomputes automatically, and each cell also stores its computed value, so the results are visible even in a viewer that does not recalculate. 2. Read the Data_Dictionary sheet, which describes every column on every sheet. 3. For the reported matrix, inspect the Scenario_Model sheet, where each of the 81 rows applies equations 1 to 4 to one combination of the four levers and returns the unlevered project internal rate of return and the net present value at 8 percent. 4. To change an input, edit only the Assumptions, Scenario_Levels, Incentive_Regime, and Capital_Structure sheets. Everything else is derived and recomputes automatically. 5. For a variant reported in Appendix C of the article, set the corresponding value on Capital_Structure, namely the phasing weights for Table C.1 and the gearing, debt pricing, and tenor for Tables C.2 and C.3, then read the result on Cashflow_Engine_Phased, Cashflow_Engine_Levered, DSCR_Schedule, Debt_Capacity, or Structure_Summary. 6. For the replacement fiscal regime, compare the Cashflow_Engine_EDTI and Regime_Comparison sheets with the exemption result. 7. To rebuild the model independently, apply the four equations to the inputs, which fully specify the matrix in any programming language. The equations are G(t) = G0 × (1 − c) × (1 − d)^(t−1), R(t) = G(t) × τ, CF(t) = R(t) − OPEX(t) − Tax(t), and the internal rate of return is the r satisfying −CAPEX + Σ CF(t)/(1+r)^t = 0 over t = 1 to 25.
Institutions
- National and Kapodistrian University of AthensAttica, Athens