Data bank: nine numerical methods for determining the parameters of weibull for wind energy generation tested by five statistical tools

Badawi, Ahmed Samir; Yusoff, Siti Hajar; Zyoud, Alhareth; Khan, Sheroz; Hashim, Aisha Hassan Abdalla; Uyaroğlu, Yılmaz; Ismail, Mohd Iswadi

doi:10.11591/ijpeds.v12.i2.pp1114-1130

Cited by 6 publications

(3 citation statements)

References 33 publications

(55 reference statements)

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“…This is illustrated in Figures 1(a) and 1(b). In addition, to explain the behavior of the wind speed, the Weibull and Rayleigh distributions were implemented [24]- [26]. The Weibull distribution function is represented in (1).…”

Section: Data Processing and Analysismentioning

confidence: 99%

Wind power prediction using a nonlinear autoregressive exogenous model network: the case of Santa Marta, Colombia

Guillot

Leal

Robles-Algarín

et al. 2023

IJECE

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<span lang="EN-US">The monitoring of wind installations is key for predicting their future behavior, due to the strong dependence on weather conditions and the stochastic nature of the wind. However, in some places, in situ measurements are not always available. In this paper, active power predictions for the city of Santa Marta-Colombia using a nonlinear autoregressive exogenous model (NARX) network were performed. The network was trained with a reliable dataset from a wind farm located in Turkey, because the meteorological data from the city of Santa Marta are unavailable or unreliable on certain dates. Three training and testing cases were designed, with different input variables and varying the network target between active power and wind speed. The dataset was obtained from the Kaggle platform, and is made up of five variables: date, active power, wind speed, theoretical power, and wind direction; each with 50,530 samples, which were preprocessed and, in some cases, normalized, to facilitate the neural network learning. For the training, testing and validation processes, a correlation coefficient of 0.9589 was obtained for the best scenario with the data from Turkey, while the best correlation coefficient for the data from Santa Marta was 0.8537.</span>

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Section: Data Processing and Analysismentioning

confidence: 99%

Wind power prediction using a nonlinear autoregressive exogenous model network: the case of Santa Marta, Colombia

Guillot

Leal

Robles-Algarín

et al. 2023

IJECE

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show abstract

“…The power coefficient (C p ) depends on blade tip speed (λ) and blade pitch angle (β). As a result of the Betz limit a wind turbine can ideally and theoretically excerpt 59% maximum wind power [39], [41]- [43]. On the other hand, practically the maximum power that can be produced from the wind turbine is up to 40% [44].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Incremental Conductance and Adaptive HCS MPPT Algorithms for WECS

Badawi,

Ali,

M. Elzein

et al. 2024

IJCDS

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This paper presents a novel Maximum Power Point Tracking (MPPT) algorithm designed for Wind Energy Conversion Systems (WECS) to achieve optimal power extraction (P max ). The controllers employed in this study utilize a Direct Power Control (DPC) framework to assess efficiency and performance, particularly under uncertain and rapid variations in wind speed profiles. The research aims to evaluate the effectiveness of the Incremental Conductance (INC) and adaptive Hill-Climbing Search (HCS) algorithms for MPPT in WECS under such conditions. The modeling of the WECS system utilizes a Permanent Magnet Synchronous Generator (PMSG) due to its reliability and robustness. Simulation results demonstrate the significant impact of wind speed on rotor speed and electromagnetic torque, highlighting the proportional relationship between wind speed parameters and power output. The controller performance is evaluated using INC and adaptive HCS, with the latter demonstrating superior efficiency under rapid wind speed changes. Additionally, simulation results show that the INC algorithm exhibits rapid tracking capability in approaching the peak maximum power point. Overall, this study provides valuable insights into the performance of MPPT algorithms in WECS, particularly under varying wind conditions.

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“…Furthermore, the wind power potential is based on several parameters [7]. So, a careful study is required to install a wind power conversion system.…”

Section: Introductionmentioning

confidence: 99%

Wind characteristics analysis and application of ontrol strategy for wind system based on direct power control

Bedoud

Bahi

Merabet

2022

IJPEDS

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This study analyses yearly and seasonal wind speed data recorded over eight years using Weibull distribution function and the direct power control application of a wind chain. The wind potential evaluation was carried out based on empirical model. Results show that, during the warm months the wind speed is uniform, constant and stable. In addition, it has been found that the use of a control strategy was necessary for extracting the optimum power. For this purpose, the second part of this work presents a direct power control (DPC) technique in order to adjust the produced active and reactive powers. The application and performance evaluation of the proposed control system implemented within the d-q reference framework has been exposed and discussed. The system modeling and the control diagram are built under MATLAB software. According to simulation results, the forward power control provides almost sinusoidal input waveform current, constant switching frequency operation, unity power factor regulation and also provides powers decoupling. As shown by simulation results, the suggested control method is efficient.

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Data bank: nine numerical methods for determining the parameters of weibull for wind energy generation tested by five statistical tools

Cited by 6 publications

References 33 publications

Wind power prediction using a nonlinear autoregressive exogenous model network: the case of Santa Marta, Colombia

Wind power prediction using a nonlinear autoregressive exogenous model network: the case of Santa Marta, Colombia

Performance Evaluation of Incremental Conductance and Adaptive HCS MPPT Algorithms for WECS

Wind characteristics analysis and application of ontrol strategy for wind system based on direct power control

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