Power Curve Estimation of a Wind Turbine Considering Different Weather Conditions using Machine Learning Algorithms

Al‐Gabalawy, Mostafa; Ramadan, Haïtham Saad Mohamed; Mostafa, Mohammed A.; Hussien, Shimaa A.

doi:10.1109/mepcon55441.2022.10021759

Cited by 3 publications

(2 citation statements)

References 24 publications

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“…8 shows the implementation of data interpolation to handle missing value. Various Exploratory Data Analysis (EDA) were conducted to visualize and analyze the distribution of data before and after preprocessing [26]. The data preprocess will enhance the quality of imputation that will contribute to accurate and meaningful outcomes.…”

Section: A Preprocessing Data For Imputationmentioning

confidence: 99%

Rainfall-Runoff Modeling Using Artificial Neural Network for Batu Pahat River Basin

Zulkiflee,

Mohd Safar,

Kamaludin

et al. 2024

JOIV : Int. J. Inform. Visualization

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This research delves into the effectiveness of Artificial Neural Networks with Multilayer Perceptron (ANN-MLP) and Nonlinear AutoRegressive with eXogenous inputs (NARX) models in predicting short-term rainfall-runoff patterns in the Batu Pahat River Basin. This study aims to predict river water levels using historical rainfall and river level data for future intervals of 1, 3, and 6 hours. Data preprocessing techniques, including the management of missing values, identification of outliers, and reduction of noise, were applied to enhance the accuracy and dependability of the models. This study assessed the performance of the models for ANN-MLP and NARX by comparing their effectiveness across various forecast timeframes and evaluating their performance in different scenarios. The findings of the study revealed that the ANN-MLP model showed robust performance in short-term prediction. On the contrary, the NARX model exhibited higher accuracy, particularly in capturing intricate temporal relationships and external impacts on river behavior. The ANN-MLP produces 99% accuracy for 1-hour prediction, and NARX yields 98% accuracy with 0.3245 Root Mean Squared Error and 0.1967 Mean Absolute Error. This study makes a valuable contribution to hydrological forecasting by presenting a rigorous and precise modeling methodology.

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Section: A Preprocessing Data For Imputationmentioning

confidence: 99%

Rainfall-Runoff Modeling Using Artificial Neural Network for Batu Pahat River Basin

Zulkiflee,

Mohd Safar,

Kamaludin

et al. 2024

JOIV : Int. J. Inform. Visualization

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“…Power electronic converters have been a staple of the wind energy industry since commercial wind turbines have been operating on the grid. There have been significant advancements in this technology in the last 30 years [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Controlling PMSG Wind Turbine Connected to Three Level Neutral Point Clamped Inverter Based on MPC

Al-Gabalawy,

Ibrahim A. Abdel-Sattar,

Mohamed M. M. Salama

et al. 2023

J. Electron. Electric. Eng.

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Wind energy generation systems are facing increasing importance in terms of harmonic distortion control and power quality standards. In recent years, variable speed has also risen rapidly due to advancements in power electronics. The three key elements of a wind power conversion system (WECS) are electrical generators, machine-side converters, and grid-side converters. It should be noted that the permanent magnet synchronous generator is one of the most often used types of electrical generators due to its special qualities. When wind energy is converted to the proper electrical power, it may be injected into the utility grid using either synchronous generators or grid-side converters. Therefore, an investigation of several topologies and control strategies is required to determine which is the best for the machine-side converter. The use of model predictive control (MPC) for a surface mount permanent magnet synchronous machine wind turbine is the main topic of this work. The machine's electrical model is the one that was utilized. The power converters are selected considering the intricate and highly nonlinear aerodynamic system of the wind turbines. MPC is a promising control technique despite being a relatively recent application in power electronics. In addition, MATLAB and Simulink are used to build the MPC code and offer a simplified model of the turbine.

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Estimation of the residual useful life of EV batteries using advanced hybrid learning tools

Hussien,

BaQais,

Al-Gabalawy

2023

Electr Eng

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Power Curve Estimation of a Wind Turbine Considering Different Weather Conditions using Machine Learning Algorithms

Cited by 3 publications

References 24 publications

Rainfall-Runoff Modeling Using Artificial Neural Network for Batu Pahat River Basin

Rainfall-Runoff Modeling Using Artificial Neural Network for Batu Pahat River Basin

Controlling PMSG Wind Turbine Connected to Three Level Neutral Point Clamped Inverter Based on MPC

Estimation of the residual useful life of EV batteries using advanced hybrid learning tools

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