The Experts below are selected from a list of 792 Experts worldwide ranked by ideXlab platform
Mark Dales - One of the best experts on this subject based on the ideXlab platform.
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simultaneous fault detection algorithm for grid connected photovoltaic plants
Iet Renewable Power Generation, 2017Co-Authors: Mahmoud Dhimish, Violeta Holmes, Bruce Mehrdadi, Mark DalesAbstract:In this work, the authors present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of photovoltaic (PV) measured data. The main focus of this study is, therefore, to outline a PV fault detection algorithm that can diagnose faults on the DC side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the fault detection algorithm can detect accurately different types of faults such as, faulty PV module, faulty PV String, faulty Bypass Diode and faulty maximum power point tracking unit. The proposed PV fault detection algorithm has been validated using 1.98 kWp PV plant installed at the University of Huddersfield, UK.
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Parallel fault detection algorithm for grid-connected photovoltaic plants
Renewable Energy, 2017Co-Authors: Mahmoud Dhimish, Violeta Holmes, Mark DalesAbstract:In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass Diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom.
Mahmoud Dhimish - One of the best experts on this subject based on the ideXlab platform.
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simultaneous fault detection algorithm for grid connected photovoltaic plants
Iet Renewable Power Generation, 2017Co-Authors: Mahmoud Dhimish, Violeta Holmes, Bruce Mehrdadi, Mark DalesAbstract:In this work, the authors present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of photovoltaic (PV) measured data. The main focus of this study is, therefore, to outline a PV fault detection algorithm that can diagnose faults on the DC side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the fault detection algorithm can detect accurately different types of faults such as, faulty PV module, faulty PV String, faulty Bypass Diode and faulty maximum power point tracking unit. The proposed PV fault detection algorithm has been validated using 1.98 kWp PV plant installed at the University of Huddersfield, UK.
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Parallel fault detection algorithm for grid-connected photovoltaic plants
Renewable Energy, 2017Co-Authors: Mahmoud Dhimish, Violeta Holmes, Mark DalesAbstract:In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass Diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom.
Marcello Chiaberge - One of the best experts on this subject based on the ideXlab platform.
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capacitor charging method for i v curve tracer and mppt in photovoltaic systems
Solar Energy, 2015Co-Authors: Filippo Spertino, Jawad Ahmad, Alessandro Ciocia, Paolo Di Leo, Ali Faisal Murtaza, Marcello ChiabergeAbstract:Abstract The capacitor charging method can be used in Photovoltaic (PV) systems for two typical applications: a very simple and cheap way (1) to trace the I–V curve of a PV generator of whatever size and (2) to track the Maximum Power Point (MPP), especially when the partial shading occurs. The problem is the correct sizing of the capacitor in order to achieve accurate, uniform and smooth results. In the first application a simplified calculation to design quickly the capacitor is carried out. This is done only as a function of the main characteristics of the PV array and the most important datasheet parameters of the PV modules. Then, the setup of I–V curve tracers at module, string and array levels is presented: these tracers are useful in the detection of underperformance of PV systems. In the second application a MPPT (MPP Tracker) circuit based on capacitor charging is designed and simulated in partial shading conditions. In these conditions the Power–Voltage (P–V) curve of a PV array is characterized by the presence of multiple maxima for the Bypass Diode action. The PV array is isolated from the load for a negligibly short period and is connected to an external capacitor. During the charging time, the proposed circuit tracks the global MPP. This circuit is easy to implement and shortens the duration needed for scanning the P–V curve of the array.
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a maximum power point tracking technique based on Bypass Diode mechanism for pv arrays under partial shading
Energy and Buildings, 2014Co-Authors: Ali Faisal Murtaza, Filippo Spertino, Marcello Chiaberge, Diego Boero, Mirko De GiuseppeAbstract:Abstract During partial shading conditions, the power-voltage characteristics of photovoltaic (PV) array exhibit multiple local maxima (LMs), one of them is a global maximum (GM). Such conditions are very challenging for maximum power point tracking (MPPT) technique to locate the GM. In this paper, initially, the effects of partial shading on PV array are extensively studied with two comprehensive PV models. From this study, several critical observations regarding the working mechanism of Bypass Diodes (BD) are pointed out. These observations play a vital role in the designing of the proposed technique (BD-MPPT). The main characteristics of BD-MPPT are: (1) new voltage limit mechanism and (2) intelligent calibration of voltage steps. The proposed BD-MPPT shows better performance in comparison with the past-proposed MPPTs. To evaluate the performance, BD-MPPT is programmed in Matlab/Simulink. Simulations are carried out with several partial shading patterns which reveal that BD-MPPT always guarantees convergence to the GM. Furthermore, the proposed technique is tested using the experimental data of 86.24 kW building integrated PV plant. Data collected at different time intervals include different partial shading patterns. Results indicate that in most occasions, the efficiency of the building integrated PV plant reaches more than 96.6% with the aid of proposed BD-MPPT.
Filippo Spertino - One of the best experts on this subject based on the ideXlab platform.
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capacitor charging method for i v curve tracer and mppt in photovoltaic systems
Solar Energy, 2015Co-Authors: Filippo Spertino, Jawad Ahmad, Alessandro Ciocia, Paolo Di Leo, Ali Faisal Murtaza, Marcello ChiabergeAbstract:Abstract The capacitor charging method can be used in Photovoltaic (PV) systems for two typical applications: a very simple and cheap way (1) to trace the I–V curve of a PV generator of whatever size and (2) to track the Maximum Power Point (MPP), especially when the partial shading occurs. The problem is the correct sizing of the capacitor in order to achieve accurate, uniform and smooth results. In the first application a simplified calculation to design quickly the capacitor is carried out. This is done only as a function of the main characteristics of the PV array and the most important datasheet parameters of the PV modules. Then, the setup of I–V curve tracers at module, string and array levels is presented: these tracers are useful in the detection of underperformance of PV systems. In the second application a MPPT (MPP Tracker) circuit based on capacitor charging is designed and simulated in partial shading conditions. In these conditions the Power–Voltage (P–V) curve of a PV array is characterized by the presence of multiple maxima for the Bypass Diode action. The PV array is isolated from the load for a negligibly short period and is connected to an external capacitor. During the charging time, the proposed circuit tracks the global MPP. This circuit is easy to implement and shortens the duration needed for scanning the P–V curve of the array.
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a maximum power point tracking technique based on Bypass Diode mechanism for pv arrays under partial shading
Energy and Buildings, 2014Co-Authors: Ali Faisal Murtaza, Filippo Spertino, Marcello Chiaberge, Diego Boero, Mirko De GiuseppeAbstract:Abstract During partial shading conditions, the power-voltage characteristics of photovoltaic (PV) array exhibit multiple local maxima (LMs), one of them is a global maximum (GM). Such conditions are very challenging for maximum power point tracking (MPPT) technique to locate the GM. In this paper, initially, the effects of partial shading on PV array are extensively studied with two comprehensive PV models. From this study, several critical observations regarding the working mechanism of Bypass Diodes (BD) are pointed out. These observations play a vital role in the designing of the proposed technique (BD-MPPT). The main characteristics of BD-MPPT are: (1) new voltage limit mechanism and (2) intelligent calibration of voltage steps. The proposed BD-MPPT shows better performance in comparison with the past-proposed MPPTs. To evaluate the performance, BD-MPPT is programmed in Matlab/Simulink. Simulations are carried out with several partial shading patterns which reveal that BD-MPPT always guarantees convergence to the GM. Furthermore, the proposed technique is tested using the experimental data of 86.24 kW building integrated PV plant. Data collected at different time intervals include different partial shading patterns. Results indicate that in most occasions, the efficiency of the building integrated PV plant reaches more than 96.6% with the aid of proposed BD-MPPT.
Violeta Holmes - One of the best experts on this subject based on the ideXlab platform.
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simultaneous fault detection algorithm for grid connected photovoltaic plants
Iet Renewable Power Generation, 2017Co-Authors: Mahmoud Dhimish, Violeta Holmes, Bruce Mehrdadi, Mark DalesAbstract:In this work, the authors present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of photovoltaic (PV) measured data. The main focus of this study is, therefore, to outline a PV fault detection algorithm that can diagnose faults on the DC side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the fault detection algorithm can detect accurately different types of faults such as, faulty PV module, faulty PV String, faulty Bypass Diode and faulty maximum power point tracking unit. The proposed PV fault detection algorithm has been validated using 1.98 kWp PV plant installed at the University of Huddersfield, UK.
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Parallel fault detection algorithm for grid-connected photovoltaic plants
Renewable Energy, 2017Co-Authors: Mahmoud Dhimish, Violeta Holmes, Mark DalesAbstract:In this work, we present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of PV measured data. The main focus of this paper is, therefore, to outline a parallel fault detection algorithm that can diagnose faults on the DC-side and AC-side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module's temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the parallel fault detection algorithm can detect and locate accurately different types of faults such as, faulty PV module, faulty PV String, Faulty Bypass Diode, Faulty Maximum power point tracking (MPPT) unit and Faulty DC/AC inverter unit. The parallel fault detection algorithm has been validated using an experimental data climate, with electrical parameters based on a 1.98 and 0.52 kWp PV systems installed at the University of Huddersfield, United Kingdom.
