What Is P50/P90? Definition & Guide

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?

For accurate solar design software that uses this metric in real-world calculations, see how modern platforms model energy yield directly from irradiance data.

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.

Core Formula

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.

Median

P50

50% exceedance probability. Used for expected-case financial returns, equity investor projections, and system performance benchmarks. The “most likely” annual output.

Moderate

P75

75% exceedance probability. Used by some lenders as a compromise between P50 optimism and P90 conservatism. Common in European project finance.

Conservative

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.

Very Conservative

P99

99% exceedance probability. Used for worst-case scenario planning and stress testing. Rarely used for financial modeling but important for risk management.

Designer’s Note

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

Typical P50 to P90 Gap

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

Pro Tip

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.