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Related Experiment Video

Updated: Apr 12, 2026

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Published on: February 13, 2018

Wind power error estimation in resource assessments.

Osvaldo Rodríguez¹, Jesús A Del Río², Oscar A Jaramillo³

¹Posgrado en Ingeniería, Universidad Nacional Autónoma de México, Temixco, Morelos, México; Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, México.

|May 23, 2015

Summary

This summary is machine-generated.

This study presents a new method for estimating wind power errors using wind speed data and turbine power curves. A 10% wind speed error can lead to a 5% error in power output, improving renewable energy project assessments.

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Last Updated: Apr 12, 2026

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Published on: February 13, 2018

Area of Science:

Renewable Energy Engineering
Wind Power Technology
Techno-economic Analysis

Background:

Accurate power output estimation is crucial for renewable energy project feasibility.
Current methods for wind power assessment need enhancement for better reliability.
Increased wind power penetration requires robust techno-economic evaluation tools.

Purpose of the Study:

To develop a reliable method for wind power error estimation.
To quantify the impact of wind speed measurement errors on power output.
To improve the accuracy of techno-economic assessments for wind energy projects.

Main Methods:

Proposed a novel error estimation method for wind power.
Utilized wind speed measurement error and probability density functions.
Applied 28 fitted wind turbine power curves (Lagrange's method) to actual wind speed data.
Calculated estimated wind power output and error propagation.

Main Results:

Demonstrated that a 10% wind speed error propagates to a 5% error in estimated power output.
The proposed error propagation method complements traditional power resource assessments.
Enabled estimation of intervals for leveled cost of energy and investment time return.

Conclusions:

The implemented method enhances the reliability of techno-economic resource assessment studies.
Accurate error estimation is vital for the successful deployment of wind energy.
This approach provides a more realistic view of wind power project economics.