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Related Concept Videos

Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

263
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
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Design Example: Calculating Safe Diameter for Wind-Exposed Disc01:17

Design Example: Calculating Safe Diameter for Wind-Exposed Disc

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Assessing safety in wind-exposed installations is crucial to preventing potential failures. This example explores the calculation and design adjustments needed to mount a circular disc on a building facade, where wind forces are a primary concern. A 4-meter diameter disc was initially designed as an aesthetic feature facing winds at a velocity of 25 meters per second, with an air density of 1.25 kilograms per cubic meter. Given these conditions, the drag force on the disc was determined using...
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Wind Turbine Machine Models01:24

Wind Turbine Machine Models

85
In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
85
The Swing Equation01:21

The Swing Equation

229
The Swing Equation is a fundamental tool in power system dynamics, especially for analyzing the behavior of generating units like three-phase synchronous generators. This equation emerges from applying Newton's second law to the rotor of a generator, encompassing factors such as inertia, angular acceleration, and the interplay between mechanical and electrical torques.
In a steady-state operation, the mechanical torque (Τm) supplied to the generator is balanced by the electrical torque...
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Moment-of-Momentum Equation01:09

Moment-of-Momentum Equation

54
The moment-of-momentum equation is a critical tool for analyzing the torque produced by the rotating blades of a wind turbine. This equation is derived by applying Newton's second law to a fluid particle, which states that the rate of change of linear momentum is equal to the external force acting on the particle.
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Turbine-Governor Control01:17

Turbine-Governor Control

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Turbine-governor control is crucial for maintaining power system stability by balancing turbine mechanical power output with electrical load demand. This mechanism ensures that generator frequency and rotor speed are within acceptable limits during load variations. Turbine-generator units store kinetic energy due to their rotating masses; this energy is released to meet the load requirement when the load increases. The electrical torque of turbines rises to meet the demand, whereas the...
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Related Experiment Video

Updated: May 7, 2025

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing
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A novel energy pattern factor-based optimized approach for assessing Weibull parameters for wind power applications.

Ghulam Abbas1, Arshad Ali2, Mohamed Tahar Ben Othman3

  • 1Department of Electrical Engineering, The University of Lahore, Lahore, 54000, Pakistan.

Scientific Reports
|January 3, 2025
PubMed
Summary

A new method, the novel optimized energy pattern factor method (NOEPFM), accurately estimates wind speed data parameters for assessing wind energy potential. This approach offers a superior fit compared to existing methods.

Keywords:
Energy EfficiencyEnergy Pattern Factor (EPF)NOEPFMOptimizationStatistical IndicatorsWeibull ParametersWind Speed Data

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Area of Science:

  • Renewable Energy
  • Meteorology
  • Statistical Modeling

Background:

  • Wind energy is a crucial green energy source.
  • Accurate wind speed data analysis is vital for wind power potential assessment.
  • The Weibull distribution (WD) is commonly used for wind speed data, requiring accurate parameter estimation (shape k and scale c).

Purpose of the Study:

  • To propose and validate a novel optimized energy pattern factor method (NOEPFM) for determining Weibull distribution parameters from wind speed data.
  • To compare the performance of NOEPFM against existing energy pattern factor (EPF) methods.

Main Methods:

  • The study introduces the NOEPFM, utilizing the trust-region-dogleg algorithm.
  • NOEPFM was applied to wind speed data from four cities in Southern Punjab, Pakistan.
  • Performance was evaluated using goodness-of-fit indices: RMSE, MAE, R, CoE, and MaxAE.

Main Results:

  • The NOEPFM demonstrated a superior fit to wind speed datasets compared to conventional EPF-based methods.
  • The proposed method showed high accuracy in estimating Weibull distribution parameters (k and c).

Conclusions:

  • The NOEPFM is a workable and enhanced approach for calculating wind power potential.
  • This method provides a reliable tool for accurate wind energy resource assessment.