1. What is UQ or Uncertainty Quantification?

Uncertainty Quantification (UQ) is the science of measuring and managing unknowns in complex systems. In the context of renewables, it means understanding how uncertainty in weather, degradation, equipment availability, and modeling assumptions can affect project outcomes like energy generation or financial returns.

PowerUQ brings rigorous UQ methods - inspired by aerospace and nuclear industries - into renewable energy modeling, enabling you to quantify and trace uncertainty across the entire project lifecycle.

For more, refer to https://www.poweruq.com/uq-primer

2. How are you different from PVsyst? Why do you exist?

PVsyst is an energy modeling tool used primarily for pre-build simulations. It assumes fixed inputs to produce a single energy estimate (e.g., base case or P50 resource case), and optionally allows a P90 estimate based on rough rule-of-thumb adjustments (see TMY-RSS below).

PowerUQ exists to close the gap: we quantify uncertainty systematically and dynamically, using statistical simulations that span input variability, component tolerances, and operational realities. We don’t replace PVsyst - we complement it by turning its outputs into a probabilistic, risk-adjusted view of your project’s future.

Typical workflow

PV Design tools (PVsyst/PlantPredict) => Base case generation (TMY/P50 resource) => [PowerUQ => P50/P90/P95/P99 generation] => Financial models

3. What is wrong with just applying a haircut to my energy predictions?

A “haircut” (e.g. applying a flat 10% discount to energy estimates to get a P90) may seem conservative, but it’s not traceable, data-driven, or tailored to the project.

This approach:

• Ignores the actual drivers of uncertainty (aleatoric and epistemic to be exact)

• Assumes all risk is symmetric and uniform

• Cannot be updated dynamically as the operational data comes in

PowerUQ replaces the haircut with a statistical simulation that lets you see which assumptions actually move the needle - and how to reduce or hedge against them.

4. What is TMY-RSS method?

TMY-RSS refers to the standard method for combining Typical Meteorological Year (TMY) weather data with a Root-Sum-of-Squares (RSS) approach to uncertainty:

Total Uncertainty ≈ √(Interannual Variability² + Irradiance measurement uncertainty² + Model uncertainty² +  ...)

It’s widely used but:

• Assumes independent uncertainties (which is often not true)

• Loses traceability of where the risk comes from

• Offers no lifecycle view

• Can't model non-linear model interactions, e.g. degradation vs. clipping

• Can't benefit from real-world operations data to make better predictions

     Special note: Satellite data providers generate a P50 or P90 (see below for more on that) weather file for a location in lieu of the TMY to better estimate the effects of weather variability on cash flows. While a step in the right direction, used with the RSS method, it still can't account for a combined effect with model or other aleatoric uncertainties.

PowerUQ replaces TMY-RSS with Monte Carlo simulations and data-driven inference, preserving traceability and actionability for both - pre-build and operating phase.

5. What are P50 and P90 (PXX)? 

PXX values are the probability of exceedance values that tell you how much energy your system is likely to generate under uncertainty:

• P50 = median outcome (50% chance the project will do better)

• P90 = conservative outcome (90% chance of doing better, lower than P50)

PowerUQ gives you not just P50 and P90, but a full “risk-adjusted forward curve” across time, along with preliminary impact on financial metrics such as IRR and DSCR.

6. What is IRR?

IRR (Internal Rate of Return) is the discount rate at which the net present value (NPV) of a project’s cash flows equals zero. It’s a key metric for investors to understand project profitability. For more details, click here.

PowerUQ helps you quantify how uncertainty in energy production translates to uncertainty in IRR making your business case more transparent and defensible.

7. What is DSCR?

DSCR (Debt Service Coverage Ratio) is the ratio of cash available to service debt. A DSCR of 1.2, for example, means you have 20% more gross  than you need to cover loan payments (principal and interest). For more details, click here.

PowerUQ models how variability in production or availability impacts PXX-based DSCR metrics- helping you avoid covenant breaches and design smarter financing structures.

8. What is an Out-year?

Out-year refers to the expected generation in a specific year in the project's lifecycle. It assumes each year in project's lifecycle is an independent weather-year. Simply put, it is assumed that bad weather years don't cancel out good weather years, making this a conservative way of predicting performance, hence useful in determining debt service coverage ratio (DSCR).

9. What is a Through-year?

Through-year refers to the average expected generation through a specific year in the project's lifecycle.  Simply put, it is the average expected outcome, hence assumes over time, bad weather years and good weather years average out, making it a more realistic way of including averaging of weather variability.  It is more suited to calculate the project profitability metrics such as the Net present value (NPV) or internal rate of return (IRR) of the project.