@misc{1ccf362dce5b4d6a92fe3afe08bd2778,
title = "The Power Curve Working Group's Assessment of Wind Turbine Power Performance Prediction Methods",
abstract = "A wind turbine power curve is often only strictly valid for a subset of all atmospheric conditions (i.e., the inner range), while wind turbines also operate in other scenarios (i.e., the outer range). Hence, modeling the power output in real-world conditions is a fundamental challenge. For example, the power deviation matrix (PDM) in Figure 1 displays an overprediction of power production using a reference power curve when wind speed (WS) and turbulence intensity (TI) are both low. Many experts use the PDM approach to observe any systematic bias in power curves and correct this in energy yield models. The mission of the Power Curve Working Group (PCWG) is to bring together wind industry stakeholders to help identify, validate, and develop ways to improve modeling of wind turbine performance in all atmospheric conditions.",
keywords = "energy yield model, power-curve modeling, turbines, wind energy",
author = "Lee, {Cheuk Yi Joseph} and Michael Fields and Jordan Perr-Sauer and Lindy Williams and Peter Stuart and Andrew Clifton and Lee Cameron and Taylor Geer and Paul Housley",
year = "2019",
language = "American English",
series = "Presented at the Wind Resource and Project Energy Assessment Conference, 10-11 September 2019, Renton, Washington",
type = "Other",
}