The Experts below are selected from a list of 58485 Experts worldwide ranked by ideXlab platform

M A Hannan - One of the best experts on this subject based on the ideXlab platform.

  • intelligent Maximum Power Point tracking for pv system using hopfield neural network optimized fuzzy logic controller
    Energy and Buildings, 2012
    Co-Authors: Subiyanto Subiyanto, Azah Mohamed, M A Hannan
    Abstract:

    Abstract This paper presents a new method for Maximum Power Point tracking of photovoltaic (PV) energy harvesting system by using the Hopfield neural network (HNN) optimized fuzzy logic controller (FLC). In the proposed method, HNN is utilized to automatically tune the FLC membership functions instead of adopting the trial-and-error approach. A complete simulation model of a PV system using the MATLAB/Simulink software is developed to validate the HNN optimized FLC. A hardware prototype of the PV Maximum Power Point tracking controller was also implemented using the dSPACE DS1104 controller. Simulation and experimental results show the performance and effectiveness of the HNN optimized FLC. It is proven that the proposed HNN optimized FLC can provide accurate tracking of the PV Maximum Power Point and improve the efficiency of PV systems.

  • intelligent Maximum Power Point tracking for pv system using hopfield neural network optimized fuzzy logic controller
    Energy and Buildings, 2012
    Co-Authors: Subiyanto Subiyanto, Azah Mohamed, M A Hannan
    Abstract:

    Abstract This paper presents a new method for Maximum Power Point tracking of photovoltaic (PV) energy harvesting system by using the Hopfield neural network (HNN) optimized fuzzy logic controller (FLC). In the proposed method, HNN is utilized to automatically tune the FLC membership functions instead of adopting the trial-and-error approach. A complete simulation model of a PV system using the MATLAB/Simulink software is developed to validate the HNN optimized FLC. A hardware prototype of the PV Maximum Power Point tracking controller was also implemented using the dSPACE DS1104 controller. Simulation and experimental results show the performance and effectiveness of the HNN optimized FLC. It is proven that the proposed HNN optimized FLC can provide accurate tracking of the PV Maximum Power Point and improve the efficiency of PV systems.

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

  • intelligent Maximum Power Point tracking for pv system using hopfield neural network optimized fuzzy logic controller
    Energy and Buildings, 2012
    Co-Authors: Subiyanto Subiyanto, Azah Mohamed, M A Hannan
    Abstract:

    Abstract This paper presents a new method for Maximum Power Point tracking of photovoltaic (PV) energy harvesting system by using the Hopfield neural network (HNN) optimized fuzzy logic controller (FLC). In the proposed method, HNN is utilized to automatically tune the FLC membership functions instead of adopting the trial-and-error approach. A complete simulation model of a PV system using the MATLAB/Simulink software is developed to validate the HNN optimized FLC. A hardware prototype of the PV Maximum Power Point tracking controller was also implemented using the dSPACE DS1104 controller. Simulation and experimental results show the performance and effectiveness of the HNN optimized FLC. It is proven that the proposed HNN optimized FLC can provide accurate tracking of the PV Maximum Power Point and improve the efficiency of PV systems.

  • intelligent Maximum Power Point tracking for pv system using hopfield neural network optimized fuzzy logic controller
    Energy and Buildings, 2012
    Co-Authors: Subiyanto Subiyanto, Azah Mohamed, M A Hannan
    Abstract:

    Abstract This paper presents a new method for Maximum Power Point tracking of photovoltaic (PV) energy harvesting system by using the Hopfield neural network (HNN) optimized fuzzy logic controller (FLC). In the proposed method, HNN is utilized to automatically tune the FLC membership functions instead of adopting the trial-and-error approach. A complete simulation model of a PV system using the MATLAB/Simulink software is developed to validate the HNN optimized FLC. A hardware prototype of the PV Maximum Power Point tracking controller was also implemented using the dSPACE DS1104 controller. Simulation and experimental results show the performance and effectiveness of the HNN optimized FLC. It is proven that the proposed HNN optimized FLC can provide accurate tracking of the PV Maximum Power Point and improve the efficiency of PV systems.

Necmi Altin - One of the best experts on this subject based on the ideXlab platform.

  • interval type 2 fuzzy logic controller based Maximum Power Point tracking in photovoltaic systems
    Advances in Electrical and Computer Engineering, 2013
    Co-Authors: Necmi Altin
    Abstract:

    In this paper, interval type-2 fuzzy logic controller based Maximum Power Point tracking method is proposed for photovoltaic systems. The proposed interval type-2 fuzzy logic controlle ...

  • three phase three level grid interactive inverter with fuzzy logic based Maximum Power Point tracking controller
    Energy Conversion and Management, 2013
    Co-Authors: Necmi Altin, Saban Ozdemir
    Abstract:

    In this study, three-phase single stage grid interactive inverter with Maximum Power Point tracking capability is proposed. The proposed system consists of three-level neutral Point clamped inverter, LCL output filter, line frequency transformer, PI current regulator and fuzzy logic based Maximum Power Point tracking algorithm. Rate of change of photovoltaic Power and voltage are defined as input variables, and the change in reference current is defined as output variable for the fuzzy logic controller. The proposed Maximum Power Point tracking algorithm is robust with respect to parameter variations of photovoltaic system with adaptive feature of fuzzy logic controller. Maximum Power Point tracking algorithm determines the inverter current reference depending on the system conditions such as irradiation level and temperature, and PI regulator shapes the inverter output current. Two capacitors’ voltages of neutral Point clamped inverter are also balanced. Simulation and experimental results show that the proposed inverter system has fast transient response and can track the Maximum Power Point of PV system even if atmospheric condition changes rapidly. Also, the inverter output current is in sinusoidal waveform and in phase with line frequency and phase. In addition, total harmonic distortion level of the inverter output current is in the limits of international standards (<5%) and efficiencies of Maximum Power Point tracking algorithm and total system are measured as 98.78% and 93.12%, respectively.

Patrick L. Chapman - One of the best experts on this subject based on the ideXlab platform.

  • Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques
    IEEE Transactions on Energy Conversion, 2007
    Co-Authors: Trishan Esram, Patrick L. Chapman
    Abstract:

    The many different techniques for Maximum Power Point tracking of photovoltaic (PV) arrays are discussed. The techniques are taken from the literature dating back to the earliest methods. It is shown that at least 19 distinct methods have been introduced in the literature, with many variations on implementation. This paper should serve as a convenient reference for future work in PV Power generation.

  • dynamic Maximum Power Point tracking of photovoltaic arrays using ripple correlation control
    IEEE Transactions on Power Electronics, 2006
    Co-Authors: Trishan Esram, Patrick L. Chapman, Jonathan W Kimball, Philip T Krein, Pallab Midya
    Abstract:

    A dynamically rapid method used for tracking the Maximum Power Point of photovoltaic arrays, known as ripple correlation control, is presented and verified against experiment. The technique takes advantage of the signal ripple, which is automatically present in Power converters. The ripple is interpreted as a perturbation from which a gradient ascent optimization can be realized. The technique converges asymptotically at Maximum speed to the Maximum Power Point without the benefit of any array parameters or measurements. The technique has simple circuit implementations

Trishan Esram - One of the best experts on this subject based on the ideXlab platform.

  • Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques
    IEEE Transactions on Energy Conversion, 2007
    Co-Authors: Trishan Esram, Patrick L. Chapman
    Abstract:

    The many different techniques for Maximum Power Point tracking of photovoltaic (PV) arrays are discussed. The techniques are taken from the literature dating back to the earliest methods. It is shown that at least 19 distinct methods have been introduced in the literature, with many variations on implementation. This paper should serve as a convenient reference for future work in PV Power generation.

  • dynamic Maximum Power Point tracking of photovoltaic arrays using ripple correlation control
    IEEE Transactions on Power Electronics, 2006
    Co-Authors: Trishan Esram, Patrick L. Chapman, Jonathan W Kimball, Philip T Krein, Pallab Midya
    Abstract:

    A dynamically rapid method used for tracking the Maximum Power Point of photovoltaic arrays, known as ripple correlation control, is presented and verified against experiment. The technique takes advantage of the signal ripple, which is automatically present in Power converters. The ripple is interpreted as a perturbation from which a gradient ascent optimization can be realized. The technique converges asymptotically at Maximum speed to the Maximum Power Point without the benefit of any array parameters or measurements. The technique has simple circuit implementations