The Experts below are selected from a list of 23988 Experts worldwide ranked by ideXlab platform
M. Lydia - One of the best experts on this subject based on the ideXlab platform.
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a comprehensive review on wind turbine power Curve Modeling techniques
Renewable & Sustainable Energy Reviews, 2014Co-Authors: M. Lydia, S. Suresh Kumar, Immanuel A. Selvakumar, Edwin Prem G. KumarAbstract:The wind turbine power Curve shows the relationship between the wind turbine power and hub height wind speed. It essentially captures the wind turbine performance. Hence it plays an important role in condition monitoring and control of wind turbines. Power Curves made available by the manufacturers help in estimating the wind energy potential in a candidate site. Accurate models of power Curve serve as an important tool in wind power forecasting and aid in wind farm expansion. This paper presents an exhaustive overview on the need for Modeling of wind turbine power Curves and the different methodologies employed for the same. It also reviews in detail the parametric and non-parametric Modeling techniques and critically evaluates them. The areas of further research have also been presented.
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A comprehensive review on wind turbine power Curve Modeling techniques
Renewable and Sustainable Energy Reviews, 2014Co-Authors: M. Lydia, A. Immanuel Selvakumar, S. Suresh Kumar, G. Edwin Prem KumarAbstract:The wind turbine power Curve shows the relationship between the wind turbine power and hub height wind speed. It essentially captures the wind turbine performance. Hence it plays an important role in condition monitoring and control of wind turbines. Power Curves made available by the manufacturers help in estimating the wind energy potential in a candidate site. Accurate models of power Curve serve as an important tool in wind power forecasting and aid in wind farm expansion. This paper presents an exhaustive overview on the need for Modeling of wind turbine power Curves and the different methodologies employed for the same. It also reviews in detail the parametric and non-parametric Modeling techniques and critically evaluates them. The areas of further research have also been presented. © 2013 Elsevier Ltd. All rights reserved.
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Advanced Algorithms for Wind Turbine Power Curve Modeling
IEEE Transactions on Sustainable Energy, 2013Co-Authors: M. Lydia, S. Suresh Kumar, Immanuel A. Selvakumar, Edwin Prem G. KumarAbstract:A wind turbine power Curve essentially captures the performance of the wind turbine. The power Curve depicts the relationship between the wind speed and output power of the turbine. Modeling of wind turbine power Curve aids in performance monitoring of the turbine and also in forecasting of power. This paper presents the development of parametric and nonparametric models of wind turbine power Curves. Parametric models of the wind turbine power Curve have been developed using four and five parameter logistic expressions. The parameters of these expressions have been solved using advanced algorithms like genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), and differential evolution (DE). Nonparametric models have been evolved using algorithms like neural networks, fuzzy c-means clustering, and data mining. The Modeling of wind turbine power Curve is done using five sets of data; one is a statistically generated set and the others are real-time data sets. The results obtained have been compared using suitable performance metrics and the best method for Modeling of the power Curve has been obtained.
Edwin Prem G. Kumar - One of the best experts on this subject based on the ideXlab platform.
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a comprehensive review on wind turbine power Curve Modeling techniques
Renewable & Sustainable Energy Reviews, 2014Co-Authors: M. Lydia, S. Suresh Kumar, Immanuel A. Selvakumar, Edwin Prem G. KumarAbstract:The wind turbine power Curve shows the relationship between the wind turbine power and hub height wind speed. It essentially captures the wind turbine performance. Hence it plays an important role in condition monitoring and control of wind turbines. Power Curves made available by the manufacturers help in estimating the wind energy potential in a candidate site. Accurate models of power Curve serve as an important tool in wind power forecasting and aid in wind farm expansion. This paper presents an exhaustive overview on the need for Modeling of wind turbine power Curves and the different methodologies employed for the same. It also reviews in detail the parametric and non-parametric Modeling techniques and critically evaluates them. The areas of further research have also been presented.
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Advanced Algorithms for Wind Turbine Power Curve Modeling
IEEE Transactions on Sustainable Energy, 2013Co-Authors: M. Lydia, S. Suresh Kumar, Immanuel A. Selvakumar, Edwin Prem G. KumarAbstract:A wind turbine power Curve essentially captures the performance of the wind turbine. The power Curve depicts the relationship between the wind speed and output power of the turbine. Modeling of wind turbine power Curve aids in performance monitoring of the turbine and also in forecasting of power. This paper presents the development of parametric and nonparametric models of wind turbine power Curves. Parametric models of the wind turbine power Curve have been developed using four and five parameter logistic expressions. The parameters of these expressions have been solved using advanced algorithms like genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), and differential evolution (DE). Nonparametric models have been evolved using algorithms like neural networks, fuzzy c-means clustering, and data mining. The Modeling of wind turbine power Curve is done using five sets of data; one is a statistically generated set and the others are real-time data sets. The results obtained have been compared using suitable performance metrics and the best method for Modeling of the power Curve has been obtained.
S. Suresh Kumar - One of the best experts on this subject based on the ideXlab platform.
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a comprehensive review on wind turbine power Curve Modeling techniques
Renewable & Sustainable Energy Reviews, 2014Co-Authors: M. Lydia, S. Suresh Kumar, Immanuel A. Selvakumar, Edwin Prem G. KumarAbstract:The wind turbine power Curve shows the relationship between the wind turbine power and hub height wind speed. It essentially captures the wind turbine performance. Hence it plays an important role in condition monitoring and control of wind turbines. Power Curves made available by the manufacturers help in estimating the wind energy potential in a candidate site. Accurate models of power Curve serve as an important tool in wind power forecasting and aid in wind farm expansion. This paper presents an exhaustive overview on the need for Modeling of wind turbine power Curves and the different methodologies employed for the same. It also reviews in detail the parametric and non-parametric Modeling techniques and critically evaluates them. The areas of further research have also been presented.
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A comprehensive review on wind turbine power Curve Modeling techniques
Renewable and Sustainable Energy Reviews, 2014Co-Authors: M. Lydia, A. Immanuel Selvakumar, S. Suresh Kumar, G. Edwin Prem KumarAbstract:The wind turbine power Curve shows the relationship between the wind turbine power and hub height wind speed. It essentially captures the wind turbine performance. Hence it plays an important role in condition monitoring and control of wind turbines. Power Curves made available by the manufacturers help in estimating the wind energy potential in a candidate site. Accurate models of power Curve serve as an important tool in wind power forecasting and aid in wind farm expansion. This paper presents an exhaustive overview on the need for Modeling of wind turbine power Curves and the different methodologies employed for the same. It also reviews in detail the parametric and non-parametric Modeling techniques and critically evaluates them. The areas of further research have also been presented. © 2013 Elsevier Ltd. All rights reserved.
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Advanced Algorithms for Wind Turbine Power Curve Modeling
IEEE Transactions on Sustainable Energy, 2013Co-Authors: M. Lydia, S. Suresh Kumar, Immanuel A. Selvakumar, Edwin Prem G. KumarAbstract:A wind turbine power Curve essentially captures the performance of the wind turbine. The power Curve depicts the relationship between the wind speed and output power of the turbine. Modeling of wind turbine power Curve aids in performance monitoring of the turbine and also in forecasting of power. This paper presents the development of parametric and nonparametric models of wind turbine power Curves. Parametric models of the wind turbine power Curve have been developed using four and five parameter logistic expressions. The parameters of these expressions have been solved using advanced algorithms like genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), and differential evolution (DE). Nonparametric models have been evolved using algorithms like neural networks, fuzzy c-means clustering, and data mining. The Modeling of wind turbine power Curve is done using five sets of data; one is a statistically generated set and the others are real-time data sets. The results obtained have been compared using suitable performance metrics and the best method for Modeling of the power Curve has been obtained.
G. Edwin Prem Kumar - One of the best experts on this subject based on the ideXlab platform.
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A comprehensive review on wind turbine power Curve Modeling techniques
Renewable and Sustainable Energy Reviews, 2014Co-Authors: M. Lydia, A. Immanuel Selvakumar, S. Suresh Kumar, G. Edwin Prem KumarAbstract:The wind turbine power Curve shows the relationship between the wind turbine power and hub height wind speed. It essentially captures the wind turbine performance. Hence it plays an important role in condition monitoring and control of wind turbines. Power Curves made available by the manufacturers help in estimating the wind energy potential in a candidate site. Accurate models of power Curve serve as an important tool in wind power forecasting and aid in wind farm expansion. This paper presents an exhaustive overview on the need for Modeling of wind turbine power Curves and the different methodologies employed for the same. It also reviews in detail the parametric and non-parametric Modeling techniques and critically evaluates them. The areas of further research have also been presented. © 2013 Elsevier Ltd. All rights reserved.
Immanuel A. Selvakumar - One of the best experts on this subject based on the ideXlab platform.
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a comprehensive review on wind turbine power Curve Modeling techniques
Renewable & Sustainable Energy Reviews, 2014Co-Authors: M. Lydia, S. Suresh Kumar, Immanuel A. Selvakumar, Edwin Prem G. KumarAbstract:The wind turbine power Curve shows the relationship between the wind turbine power and hub height wind speed. It essentially captures the wind turbine performance. Hence it plays an important role in condition monitoring and control of wind turbines. Power Curves made available by the manufacturers help in estimating the wind energy potential in a candidate site. Accurate models of power Curve serve as an important tool in wind power forecasting and aid in wind farm expansion. This paper presents an exhaustive overview on the need for Modeling of wind turbine power Curves and the different methodologies employed for the same. It also reviews in detail the parametric and non-parametric Modeling techniques and critically evaluates them. The areas of further research have also been presented.
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Advanced Algorithms for Wind Turbine Power Curve Modeling
IEEE Transactions on Sustainable Energy, 2013Co-Authors: M. Lydia, S. Suresh Kumar, Immanuel A. Selvakumar, Edwin Prem G. KumarAbstract:A wind turbine power Curve essentially captures the performance of the wind turbine. The power Curve depicts the relationship between the wind speed and output power of the turbine. Modeling of wind turbine power Curve aids in performance monitoring of the turbine and also in forecasting of power. This paper presents the development of parametric and nonparametric models of wind turbine power Curves. Parametric models of the wind turbine power Curve have been developed using four and five parameter logistic expressions. The parameters of these expressions have been solved using advanced algorithms like genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), and differential evolution (DE). Nonparametric models have been evolved using algorithms like neural networks, fuzzy c-means clustering, and data mining. The Modeling of wind turbine power Curve is done using five sets of data; one is a statistically generated set and the others are real-time data sets. The results obtained have been compared using suitable performance metrics and the best method for Modeling of the power Curve has been obtained.
