Key Takeaways
- P50 is the median energy yield — there’s a 50% chance production will exceed this value in any given year
- P90 is the conservative estimate — there’s a 90% chance production will meet or exceed this value
- P90 values are typically 10–15% lower than P50, depending on climate variability
- Lenders and investors use P90 (or P75) for debt sizing and financial modeling
- Accurate P50/P90 analysis requires multi-year weather data and detailed loss modeling
- P-values are standard in bankability assessments for commercial and utility-scale projects
What Is P50/P90?
P50 and P90 are probabilistic energy yield estimates used in solar project development. They express the likelihood that a solar system will produce at least a certain amount of energy in a given year.
- P50: The median estimate. There is a 50% probability that actual annual production will equal or exceed this value. This is the “expected” yield.
- P90: The conservative estimate. There is a 90% probability that actual annual production will equal or exceed this value.
The difference between P50 and P90 reflects uncertainty — primarily from year-to-year weather variability, but also from equipment performance uncertainty and modeling accuracy.
Banks finance solar projects based on P90 revenue, not P50. If your P50/P90 spread is too wide, it signals high uncertainty and can kill a deal or increase the cost of capital.
How P50/P90 Analysis Works
P50/P90 estimates are derived from statistical analysis of energy yield simulations combined with historical weather data variability.
Collect Weather Data
Gather 10–20+ years of solar irradiance data (GHI, DNI, DHI) for the project location from satellite or ground-station sources.
Run Energy Yield Simulation
Model the system using a typical meteorological year (TMY) dataset to generate a baseline annual production estimate — this is the deterministic P50.
Quantify Uncertainty Sources
Identify and quantify all uncertainty components: inter-annual weather variability, irradiance data accuracy, model uncertainty, and equipment degradation.
Calculate Combined Uncertainty
Combine individual uncertainties using root-sum-square (RSS) method to determine total uncertainty as a standard deviation percentage.
Derive P-Values
Apply the normal distribution to calculate P75, P90, and P99 values from the P50 mean and combined uncertainty.
P90 = P50 × (1 − z-score × σ_total)Where z-score for P90 = 1.282 and σ_total is the combined uncertainty expressed as a fraction.
Common P-Values in Solar
Different stakeholders use different probability levels depending on their risk tolerance.
P50
50% exceedance probability. Used for expected-case financial returns, equity investor projections, and system performance benchmarks. The “most likely” annual output.
P75
75% exceedance probability. Used by some lenders as a compromise between P50 optimism and P90 conservatism. Common in European project finance.
P90
90% exceedance probability. The standard for debt sizing in project finance. Lenders base loan repayment schedules on P90 revenue to ensure debt service coverage.
P99
99% exceedance probability. Used for worst-case scenario planning and stress testing. Rarely used for financial modeling but important for risk management.
For residential proposals, P50 is typically sufficient. Commercial and utility-scale projects almost always require a formal P50/P90 report from an independent engineer. The cost of a third-party yield assessment is $5,000–$25,000 depending on project size.
Key Metrics & Calculations
Understanding P50/P90 requires familiarity with the underlying uncertainty components:
| Uncertainty Source | Typical Range | Impact on P90 |
|---|---|---|
| Inter-Annual Weather Variability | 3–7% | Largest single factor in most locations |
| Irradiance Data Accuracy | 2–5% | Depends on data source (satellite vs. ground) |
| Energy Model Uncertainty | 2–4% | Varies by simulation tool and modeling approach |
| Equipment Performance | 1–3% | Module power tolerance, inverter efficiency |
| Degradation Uncertainty | 0.5–1.5% | Grows over project lifetime |
| Combined Uncertainty (σ_total) | 5–10% | RSS of all individual sources |
P90 ≈ P50 × 0.85 to 0.92 (depending on location and data quality)Practical Guidance
P50/P90 analysis is relevant at different levels depending on your role in the solar project lifecycle.
- Use quality irradiance data. P50/P90 accuracy depends heavily on the weather dataset. Use at least 10 years of satellite data, and cross-reference with ground stations where available.
- Model all loss factors. Shading, soiling, clipping, wiring, mismatch, and temperature losses must all be included. Omitting losses inflates P50 and makes P90 unreliable.
- Document uncertainty assumptions. Clearly state each uncertainty component and its value. Lenders and independent engineers will scrutinize these numbers.
- Use solar design software with built-in yield analysis. Tools that integrate irradiance databases and loss modeling reduce manual errors in P50/P90 calculations.
- Understand what lenders need. If your commercial customers need financing, the lender will require a P90 estimate. Build this into your project timeline — independent assessments take 2–6 weeks.
- Compare actual vs. predicted. After the first year of operation, compare actual production to the P50 estimate. Consistently underperforming systems may have installation issues (shading, soiling, inverter problems).
- Keep as-built documentation. Any changes from the original design (panel layout, inverter model, tilt angle) affect the yield estimate. Update the P50/P90 report if changes occur.
- Monitor degradation rates. If actual degradation exceeds the assumed rate, long-term P90 projections become invalid. Annual monitoring helps catch this early.
- Use P50 for customer-facing proposals. Homeowners and small commercial customers expect the “expected” output. P90 is for lenders, not sales presentations.
- Explain variability simply. “In a below-average sun year, your system will still produce at least X kWh” is an effective way to present P90 without statistical jargon.
- Build confidence with ranges. Presenting a production range (P90 to P50) shows transparency and builds trust. Customers appreciate honesty about uncertainty.
- Highlight conservative guarantees. If you offer a production guarantee, base it on P90. You’ll meet or exceed the guarantee 90% of the time, keeping customers satisfied.
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Real-World Examples
Residential: 10 kW System
A 10 kW residential system in Arizona is modeled with P50 production of 17,200 kWh/year. With 6.5% combined uncertainty, the P90 estimate is 15,770 kWh/year. The homeowner’s proposal shows expected savings based on P50, with a note that “even in a low-sun year, your system should produce at least 15,770 kWh.” The 8.3% P50-to-P90 gap reflects Arizona’s relatively low inter-annual irradiance variability.
Commercial: 500 kW Rooftop
A 500 kW commercial rooftop in the UK has P50 production of 425,000 kWh/year. Due to higher weather variability in northern Europe, combined uncertainty is 9.2%, yielding a P90 of 375,000 kWh/year. The lender sizes the debt based on P90 revenue of approximately £30,000/year, with a 1.3x debt service coverage ratio.
Utility-Scale: 20 MW Ground-Mount
A 20 MW ground-mount project in India models P50 at 32,400 MWh/year. The independent engineer’s report identifies 7.8% combined uncertainty, producing a P90 of 29,150 MWh/year. The project’s power purchase agreement is structured around P50 production, while debt repayment is sized to P90 — the gap provides a financial cushion for below-average years.
Impact on System Design
P50/P90 analysis influences design decisions, especially for projects seeking financing:
| Design Decision | P50 Focus (Equity) | P90 Focus (Debt) |
|---|---|---|
| Financial Returns | Higher expected IRR | Lower but more certain returns |
| System Sizing | Optimized for maximum production | May be slightly oversized to ensure P90 meets targets |
| Technology Choice | Standard equipment acceptable | Bankable, Tier 1 equipment preferred |
| Data Requirements | TMY sufficient | Multi-year dataset, ground-truth validation |
| Reporting | Internal estimates | Independent engineer report required |
To tighten the P50/P90 gap (and improve bankability), use on-site irradiance measurements for at least 12 months and correlate them with long-term satellite data. This can reduce irradiance data uncertainty from 5% to 2–3%, significantly improving P90 projections.
Frequently Asked Questions
What is the difference between P50 and P90 in solar?
P50 is the median expected energy production — there’s a 50/50 chance actual output will be higher or lower. P90 is the conservative estimate that production will meet or exceed 90% of the time. The gap between them reflects uncertainty from weather variability, data quality, and modeling accuracy. Lenders use P90 for financing; project owners use P50 for expected returns.
How much lower is P90 than P50?
P90 is typically 8–15% lower than P50, depending on location and data quality. In regions with stable, predictable sunlight (deserts), the gap may be 6–8%. In regions with high weather variability (northern Europe, monsoon climates), the gap can reach 12–17%. Better irradiance data and on-site measurements help narrow this spread.
Why do banks use P90 for solar project financing?
Banks use P90 because it represents a conservative production estimate that will be met or exceeded in 9 out of 10 years. This provides a margin of safety for loan repayment. By sizing debt to P90 revenue, lenders ensure that even in below-average sun years, the project generates enough revenue to cover debt service obligations.
Do residential solar proposals need P50/P90 analysis?
Formal P50/P90 reports are not typically required for residential projects. However, presenting a production range rather than a single number builds customer trust and sets realistic expectations. Using solar software that incorporates weather variability into its estimates gives you a built-in production range without the cost of an independent assessment.
Related Glossary Terms
About the Contributors
CEO & Co-Founder · SurgePV
Keyur Rakholiya is CEO & Co-Founder of SurgePV and Founder of Heaven Green Energy Limited, where he has delivered over 1 GW of solar projects across commercial, utility, and rooftop sectors in India. With 10+ years in the solar industry, he has managed 800+ project deliveries, evaluated 20+ solar design platforms firsthand, and led engineering teams of 50+ people.
Content Head · SurgePV
Rainer Neumann is Content Head at SurgePV and a solar PV engineer with 10+ years of experience designing commercial and utility-scale systems across Europe and MENA. He has delivered 500+ installations, tested 15+ solar design software platforms firsthand, and specialises in shading analysis, string sizing, and international electrical code compliance.