The Experts below are selected from a list of 30 Experts worldwide ranked by ideXlab platform

Khaoula Ghefiri - One of the best experts on this subject based on the ideXlab platform.

  • fuzzy supervision based pitch angle control of a Tidal Stream Generator for a disturbed Tidal input
    Energies, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Joseph Haggege, Aitor Josu Garrido Hernandez, Eugen Rusu, Izaskun Garrido Hernandez
    Abstract:

    This work was supported by the MINECO through the Research Project DPI2015-70075-R (MINECO/FEDER, UE) and in part by the University of the Basque Country (UPV/EHU) through PPG17/33. The authors would like to thank the collaboration of the Basque Energy Agency (EVE) through Agreement UPV/EHUEVE23/6/2011, the Spanish National Fusion Laboratory (EURATOM-CIEMAT) through Agreement UPV/EHUCIEMAT08/190 and EUSKAMPUS - Campus of international Excellence.

  • hybrid neural fuzzy design based rotational speed control of a Tidal Stream Generator plant
    Sustainability, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Izaskun Garrido Hernandez, Joseph Haggege, Aitor Josu Garrido Hernandez
    Abstract:

    This work was supported by the MINECO through the Research Project DPI2015-70075-R (MINECO/FEDER, UE). The authors would like to thank the collaboration of the Basque Energy Agency (EVE) through Agreement UPV/EHUEVE23/6/2011, the Spanish National Fusion Laboratory (EURATOM-CIEMAT) through Agreement UPV/EHUCIEMAT08/190 and EUSKAMPUS-Campus of International Excellence.

  • fuzzy gain scheduling of a rotational speed control for a Tidal Stream Generator
    International Symposium on Power Electronics Electrical Drives Automation and Motion, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Izaskun Garrido, Aitor J Garrido, Joseph Haggege
    Abstract:

    In the field of marine energy conversion, the main aim of a Tidal Stream Generator (TSG) plant is the maximization of the output power as the speed of the Tidal current varies. In this context, this paper deals with the modeling and control of a Doubly Fed Induction Generator (DFIG)-based TSG system. A Fuzzy Gain Scheduling controller is presented to improve the rotational speed control by means of the Rotor Side Converter. The Maximum Power Point Tracking strategy is implemented to provide the reference signal to the fuzzy supervisor in order to extract the maximum power from the Tidal resource. Simulation results demonstrate that this novel control strategy successfully improve the generated power and provide an effective result against the change of the Tidal speed input.

  • multi layer artificial neural networks based mppt pitch angle control of a Tidal Stream Generator
    Sensors, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Izaskun Garrido, Aitor J Garrido, Joseph Haggege
    Abstract:

    Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream Generator (TSG) systems aim to provide clean and reliable electrical power. However, the power captured from Tidal currents is highly disturbed due to the swell effect and the periodicity of the Tidal current phenomenon. In order to improve the quality of the generated power, this paper focuses on the power smoothing control. For this purpose, a novel Artificial Neural Network (ANN) is investigated and implemented to provide the proper rotational speed reference and the blade pitch angle. The ANN supervisor adequately switches the system in variable speed and power limitation modes. In order to recover the maximum power from the tides, a rotational speed control is applied to the rotor side converter following the Maximum Power Point Tracking (MPPT) generated from the ANN block. In case of strong Tidal currents, a pitch angle control is set based on the ANN approach to keep the system operating within safe limits. Two study cases were performed to test the performance of the output power. Simulation results demonstrate that the implemented control strategies achieve a smoothed generated power in the case of swell disturbances.

  • firefly algorithm based pitch angle control of a Tidal Stream Generator for power limitation mode
    2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET), 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Joseph Haggege, Izaskun Garrido, Aitor J Garrido
    Abstract:

    This paper deals with the modeling and control of a Tidal Stream Generator (TSG) for marine renewable energy. The Power Take Off system consists of a Tidal Stream Turbine coupled to a Doubly Fed Induction Generator with a 1.5 MW power. At any Tidal site, there is a variation in the Tidal current speed with the occurring of maximum velocities. This means that the TSG system needs to be controlled in order to limit the generated power and shedding mechanical load at high current speeds. For this purpose, a Proportional Integral (PI) controller for the blade pitch angle is investigated. A firefly algorithm based-metaheuristic theory is used to tune the gains of the PI. Simulation results show the performance of the implemented control strategy by optimizing the generated power in case of strong flow speeds.

Soufiene Bouallegue - One of the best experts on this subject based on the ideXlab platform.

  • fuzzy supervision based pitch angle control of a Tidal Stream Generator for a disturbed Tidal input
    Energies, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Joseph Haggege, Aitor Josu Garrido Hernandez, Eugen Rusu, Izaskun Garrido Hernandez
    Abstract:

    This work was supported by the MINECO through the Research Project DPI2015-70075-R (MINECO/FEDER, UE) and in part by the University of the Basque Country (UPV/EHU) through PPG17/33. The authors would like to thank the collaboration of the Basque Energy Agency (EVE) through Agreement UPV/EHUEVE23/6/2011, the Spanish National Fusion Laboratory (EURATOM-CIEMAT) through Agreement UPV/EHUCIEMAT08/190 and EUSKAMPUS - Campus of international Excellence.

  • hybrid neural fuzzy design based rotational speed control of a Tidal Stream Generator plant
    Sustainability, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Izaskun Garrido Hernandez, Joseph Haggege, Aitor Josu Garrido Hernandez
    Abstract:

    This work was supported by the MINECO through the Research Project DPI2015-70075-R (MINECO/FEDER, UE). The authors would like to thank the collaboration of the Basque Energy Agency (EVE) through Agreement UPV/EHUEVE23/6/2011, the Spanish National Fusion Laboratory (EURATOM-CIEMAT) through Agreement UPV/EHUCIEMAT08/190 and EUSKAMPUS-Campus of International Excellence.

  • fuzzy gain scheduling of a rotational speed control for a Tidal Stream Generator
    International Symposium on Power Electronics Electrical Drives Automation and Motion, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Izaskun Garrido, Aitor J Garrido, Joseph Haggege
    Abstract:

    In the field of marine energy conversion, the main aim of a Tidal Stream Generator (TSG) plant is the maximization of the output power as the speed of the Tidal current varies. In this context, this paper deals with the modeling and control of a Doubly Fed Induction Generator (DFIG)-based TSG system. A Fuzzy Gain Scheduling controller is presented to improve the rotational speed control by means of the Rotor Side Converter. The Maximum Power Point Tracking strategy is implemented to provide the reference signal to the fuzzy supervisor in order to extract the maximum power from the Tidal resource. Simulation results demonstrate that this novel control strategy successfully improve the generated power and provide an effective result against the change of the Tidal speed input.

  • multi layer artificial neural networks based mppt pitch angle control of a Tidal Stream Generator
    Sensors, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Izaskun Garrido, Aitor J Garrido, Joseph Haggege
    Abstract:

    Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream Generator (TSG) systems aim to provide clean and reliable electrical power. However, the power captured from Tidal currents is highly disturbed due to the swell effect and the periodicity of the Tidal current phenomenon. In order to improve the quality of the generated power, this paper focuses on the power smoothing control. For this purpose, a novel Artificial Neural Network (ANN) is investigated and implemented to provide the proper rotational speed reference and the blade pitch angle. The ANN supervisor adequately switches the system in variable speed and power limitation modes. In order to recover the maximum power from the tides, a rotational speed control is applied to the rotor side converter following the Maximum Power Point Tracking (MPPT) generated from the ANN block. In case of strong Tidal currents, a pitch angle control is set based on the ANN approach to keep the system operating within safe limits. Two study cases were performed to test the performance of the output power. Simulation results demonstrate that the implemented control strategies achieve a smoothed generated power in the case of swell disturbances.

  • firefly algorithm based pitch angle control of a Tidal Stream Generator for power limitation mode
    2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET), 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Joseph Haggege, Izaskun Garrido, Aitor J Garrido
    Abstract:

    This paper deals with the modeling and control of a Tidal Stream Generator (TSG) for marine renewable energy. The Power Take Off system consists of a Tidal Stream Turbine coupled to a Doubly Fed Induction Generator with a 1.5 MW power. At any Tidal site, there is a variation in the Tidal current speed with the occurring of maximum velocities. This means that the TSG system needs to be controlled in order to limit the generated power and shedding mechanical load at high current speeds. For this purpose, a Proportional Integral (PI) controller for the blade pitch angle is investigated. A firefly algorithm based-metaheuristic theory is used to tune the gains of the PI. Simulation results show the performance of the implemented control strategy by optimizing the generated power in case of strong flow speeds.

Joseph Haggege - One of the best experts on this subject based on the ideXlab platform.

  • fuzzy gain scheduling of a rotational speed control for a Tidal Stream Generator
    International Symposium on Power Electronics Electrical Drives Automation and Motion, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Izaskun Garrido, Aitor J Garrido, Joseph Haggege
    Abstract:

    In the field of marine energy conversion, the main aim of a Tidal Stream Generator (TSG) plant is the maximization of the output power as the speed of the Tidal current varies. In this context, this paper deals with the modeling and control of a Doubly Fed Induction Generator (DFIG)-based TSG system. A Fuzzy Gain Scheduling controller is presented to improve the rotational speed control by means of the Rotor Side Converter. The Maximum Power Point Tracking strategy is implemented to provide the reference signal to the fuzzy supervisor in order to extract the maximum power from the Tidal resource. Simulation results demonstrate that this novel control strategy successfully improve the generated power and provide an effective result against the change of the Tidal speed input.

  • multi layer artificial neural networks based mppt pitch angle control of a Tidal Stream Generator
    Sensors, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Izaskun Garrido, Aitor J Garrido, Joseph Haggege
    Abstract:

    Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream Generator (TSG) systems aim to provide clean and reliable electrical power. However, the power captured from Tidal currents is highly disturbed due to the swell effect and the periodicity of the Tidal current phenomenon. In order to improve the quality of the generated power, this paper focuses on the power smoothing control. For this purpose, a novel Artificial Neural Network (ANN) is investigated and implemented to provide the proper rotational speed reference and the blade pitch angle. The ANN supervisor adequately switches the system in variable speed and power limitation modes. In order to recover the maximum power from the tides, a rotational speed control is applied to the rotor side converter following the Maximum Power Point Tracking (MPPT) generated from the ANN block. In case of strong Tidal currents, a pitch angle control is set based on the ANN approach to keep the system operating within safe limits. Two study cases were performed to test the performance of the output power. Simulation results demonstrate that the implemented control strategies achieve a smoothed generated power in the case of swell disturbances.

  • firefly algorithm based pitch angle control of a Tidal Stream Generator for power limitation mode
    2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET), 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Joseph Haggege, Izaskun Garrido, Aitor J Garrido
    Abstract:

    This paper deals with the modeling and control of a Tidal Stream Generator (TSG) for marine renewable energy. The Power Take Off system consists of a Tidal Stream Turbine coupled to a Doubly Fed Induction Generator with a 1.5 MW power. At any Tidal site, there is a variation in the Tidal current speed with the occurring of maximum velocities. This means that the TSG system needs to be controlled in order to limit the generated power and shedding mechanical load at high current speeds. For this purpose, a Proportional Integral (PI) controller for the blade pitch angle is investigated. A firefly algorithm based-metaheuristic theory is used to tune the gains of the PI. Simulation results show the performance of the implemented control strategy by optimizing the generated power in case of strong flow speeds.

  • modeling and mppt control of a Tidal Stream Generator
    International Conference on Control Decision and Information Technologies, 2017
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Joseph Haggege, Izaskun Garrido, Aitor J Garrido
    Abstract:

    This paper deals with the design, modeling and control of a Tidal Stream Generator (TSG) system including a Tidal turbine, a rotor shaft and a Doubly Fed Induction Generator (DFIG). Below high Tidal speed the system is regulated so that for every Tidal velocity reaches the maximum power. A rotational speed control based-Maximum Power Point Tracking (MPPT) for a TSG is investigated to provide the suitable rotational speed to the system in order to track the maximum power and thus keeping the pitch angle null. Two study cases were proposed to test the performance of the control strategy. The obtained results show that the proposed control provide satisfactory tracking of the MPPT reference.

Aitor Josu Garrido Hernandez - One of the best experts on this subject based on the ideXlab platform.

Aitor J Garrido - One of the best experts on this subject based on the ideXlab platform.

  • fuzzy gain scheduling of a rotational speed control for a Tidal Stream Generator
    International Symposium on Power Electronics Electrical Drives Automation and Motion, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Izaskun Garrido, Aitor J Garrido, Joseph Haggege
    Abstract:

    In the field of marine energy conversion, the main aim of a Tidal Stream Generator (TSG) plant is the maximization of the output power as the speed of the Tidal current varies. In this context, this paper deals with the modeling and control of a Doubly Fed Induction Generator (DFIG)-based TSG system. A Fuzzy Gain Scheduling controller is presented to improve the rotational speed control by means of the Rotor Side Converter. The Maximum Power Point Tracking strategy is implemented to provide the reference signal to the fuzzy supervisor in order to extract the maximum power from the Tidal resource. Simulation results demonstrate that this novel control strategy successfully improve the generated power and provide an effective result against the change of the Tidal speed input.

  • multi layer artificial neural networks based mppt pitch angle control of a Tidal Stream Generator
    Sensors, 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Izaskun Garrido, Aitor J Garrido, Joseph Haggege
    Abstract:

    Artificial intelligence technologies are widely investigated as a promising technique for tackling complex and ill-defined problems. In this context, artificial neural networks methodology has been considered as an effective tool to handle renewable energy systems. Thereby, the use of Tidal Stream Generator (TSG) systems aim to provide clean and reliable electrical power. However, the power captured from Tidal currents is highly disturbed due to the swell effect and the periodicity of the Tidal current phenomenon. In order to improve the quality of the generated power, this paper focuses on the power smoothing control. For this purpose, a novel Artificial Neural Network (ANN) is investigated and implemented to provide the proper rotational speed reference and the blade pitch angle. The ANN supervisor adequately switches the system in variable speed and power limitation modes. In order to recover the maximum power from the tides, a rotational speed control is applied to the rotor side converter following the Maximum Power Point Tracking (MPPT) generated from the ANN block. In case of strong Tidal currents, a pitch angle control is set based on the ANN approach to keep the system operating within safe limits. Two study cases were performed to test the performance of the output power. Simulation results demonstrate that the implemented control strategies achieve a smoothed generated power in the case of swell disturbances.

  • firefly algorithm based pitch angle control of a Tidal Stream Generator for power limitation mode
    2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET), 2018
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Joseph Haggege, Izaskun Garrido, Aitor J Garrido
    Abstract:

    This paper deals with the modeling and control of a Tidal Stream Generator (TSG) for marine renewable energy. The Power Take Off system consists of a Tidal Stream Turbine coupled to a Doubly Fed Induction Generator with a 1.5 MW power. At any Tidal site, there is a variation in the Tidal current speed with the occurring of maximum velocities. This means that the TSG system needs to be controlled in order to limit the generated power and shedding mechanical load at high current speeds. For this purpose, a Proportional Integral (PI) controller for the blade pitch angle is investigated. A firefly algorithm based-metaheuristic theory is used to tune the gains of the PI. Simulation results show the performance of the implemented control strategy by optimizing the generated power in case of strong flow speeds.

  • modeling and mppt control of a Tidal Stream Generator
    International Conference on Control Decision and Information Technologies, 2017
    Co-Authors: Khaoula Ghefiri, Soufiene Bouallegue, Joseph Haggege, Izaskun Garrido, Aitor J Garrido
    Abstract:

    This paper deals with the design, modeling and control of a Tidal Stream Generator (TSG) system including a Tidal turbine, a rotor shaft and a Doubly Fed Induction Generator (DFIG). Below high Tidal speed the system is regulated so that for every Tidal velocity reaches the maximum power. A rotational speed control based-Maximum Power Point Tracking (MPPT) for a TSG is investigated to provide the suitable rotational speed to the system in order to track the maximum power and thus keeping the pitch angle null. Two study cases were proposed to test the performance of the control strategy. The obtained results show that the proposed control provide satisfactory tracking of the MPPT reference.