A study on data accuracy by comparing between the Weibull and Rayleigh distribution function to forecast the wind energy potential for several locations of Bangladesh

Reza, Syed Enam; Zaman, Pallabi; Ahammad, Arif; Ifty, Ifrat Zaman; Nayan, Md Faysal

doi:10.1109/icdret.2016.7421510

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…The distribution parameters, which determine the distribution of wind speeds, are defined using the distribution curve. Three different types of Weibull distributions the Rayleigh, the 2-factor, and the 3-factor are defined by the following equations [23][24][25]: The Rayleigh Distribution Function: Maximum likelihood estimation (MLE) was employed to evaluate the distribution factors [26,27]. To find the distribution parameters and solve the MLE, numerical iterations are carried out.…”

Section: Probability Density Functionsmentioning

confidence: 99%

Enhancing Wind Energy Potential Assessment with Three-Parameter Weibull Distribution: A Comparative Analysis using MATLAB

M K,

et al. 2024

E3S Web of Conf.

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To determine the wind energy potential, the probability density function is typically used. For data distribution with modest wind speeds, this paper developed a three-parameter Weibull model. The distribution factors were determined using the maximal likelihood technique. The world renowned, user-friendly programming language Matrix Laboratory (MATLAB) processes all data that needs analysis. A comparison was made between the 3-factor Weibull, the 2-factor Weibull, and Rayleigh through R2 and root mean square error (RMSE). The ECMWF Reanalysis v5 (ERA 5) reanalysis's hourly wind speeds are statistically represented by these three distributions. Due to its placement between the optimal R2 and RMSE, the three-parameter Weibull model achieves good results. Weibull with three parameters has a R2 of 0.9898, Weibull with two parameters has a R2 of 0.9886, and Rayleigh has a R2 of 0.5162. The root-mean-squared errors (RMSEs) for Rayleigh, 2-factor and 3-factor Weibull, are 0.0082 and 0.0070, respectively.

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Section: Probability Density Functionsmentioning

confidence: 99%

Enhancing Wind Energy Potential Assessment with Three-Parameter Weibull Distribution: A Comparative Analysis using MATLAB

M K,

et al. 2024

E3S Web of Conf.

View full text Add to dashboard Cite

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“…Forecasting also requires the consideration of ramp event and potentially high-risk scenarios of wind power. Amongst numerous wind power forecasting techniques, many authors proposed to employ the WD function due to its reliability, accuracy, stability, and sophisticated computations and accurate results as compared to other techniques like the Rayleigh distribution [36].…”

Section: Wind Power Generation Fundamentalsmentioning

confidence: 99%

Recent Approaches of Forecasting and Optimal Economic Dispatch to Overcome Intermittency of Wind and Photovoltaic (PV) Systems: A Review

et al. 2019

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Renewable energy sources (RESs) are the replacement of fast depleting, environment polluting, costly, and unsustainable fossil fuels. RESs themselves have various issues such as variable supply towards the load during different periods, and mostly they are available at distant locations from load centers. This paper inspects forecasting techniques, employed to predict the RESs availability during different periods and considers the dispatch mechanisms for the supply, extracted from these resources. Firstly, we analyze the application of stochastic distributions especially the Weibull distribution (WD), for forecasting both wind and PV power potential, with and without incorporating neural networks (NN). Secondly, a review of the optimal economic dispatch (OED) of RES using particle swarm optimization (PSO) is presented. The reviewed techniques will be of great significance for system operators that require to gauge and pre-plan flexibility competence for their power systems to ensure practical and economical operation under high penetration of RESs.

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Sonar echo signal processing based on Convolution Blind source separation

Zhang

Sun

Liu

et al. 2020

2020 IEEE 3rd International Conference on Information Communication and Signal Processing (ICICSP)

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A study on data accuracy by comparing between the Weibull and Rayleigh distribution function to forecast the wind energy potential for several locations of Bangladesh

Cited by 4 publications

References 6 publications

Enhancing Wind Energy Potential Assessment with Three-Parameter Weibull Distribution: A Comparative Analysis using MATLAB

Enhancing Wind Energy Potential Assessment with Three-Parameter Weibull Distribution: A Comparative Analysis using MATLAB

Recent Approaches of Forecasting and Optimal Economic Dispatch to Overcome Intermittency of Wind and Photovoltaic (PV) Systems: A Review

Sonar echo signal processing based on Convolution Blind source separation

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