The Experts below are selected from a list of 141720 Experts worldwide ranked by ideXlab platform
Onder Guler - One of the best experts on this subject based on the ideXlab platform.
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Calculation of Wind Energy Potential and Economic Analysis by Using Weibull Distribution—A Case Study from Turkey. Part 2: Economic Analysis
Energy Sources Part B: Economics Planning and Policy, 2009Co-Authors: Seyit Ahmet Akdag, Onder GulerAbstract:Abstract Capacity factor and economic analysis for 4 selected turbines (1,000, 1,300, 2,000, and 2,300 kW) with 6 different hub heights (50, 60, 70, 80, 90, and 100 m) have been calculated according to 13 different situations by using Real Time Series and Weibull parameters which have been determined for Canakkale region in Part 1. As a result of the study, it has been found that kWh energy cost for the region is between 2.254 and 2.661 kWh/eurocent.
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calculation of wind energy potential and economic analysis by using weibull distribution a case study from turkey part 2 economic analysis
Energy Sources Part B-economics Planning and Policy, 2009Co-Authors: Seyit Ahmet Akdag, Onder GulerAbstract:Abstract Capacity factor and economic analysis for 4 selected turbines (1,000, 1,300, 2,000, and 2,300 kW) with 6 different hub heights (50, 60, 70, 80, 90, and 100 m) have been calculated according to 13 different situations by using Real Time Series and Weibull parameters which have been determined for Canakkale region in Part 1. As a result of the study, it has been found that kWh energy cost for the region is between 2.254 and 2.661 kWh/eurocent.
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calculation of wind energy potential and economic analysis by using weibull distribution a case study from turkey part 1 determination of weibull parameters
Energy Sources Part B-economics Planning and Policy, 2009Co-Authors: Seyit Ahmet Akdag, Onder GulerAbstract:Abstract Wind energy potential of Canakkale region has been analyzed using Real Time Series analysis and Weibull distribution, making use of hourly average wind data of Turkish State Meteorological Service measured in 10 m height between 2001 and 2006. Weibull parameters have been calculated by using graphic, moment, and maximum likelihood methods for 50, 60, 70, 80, 90, and 100 m hub heights. It has been determined that moment method gives better results than other methods according to the R2 and root mean square error (RMSE) analysis.
Seyit Ahmet Akdag - One of the best experts on this subject based on the ideXlab platform.
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Calculation of Wind Energy Potential and Economic Analysis by Using Weibull Distribution—A Case Study from Turkey. Part 2: Economic Analysis
Energy Sources Part B: Economics Planning and Policy, 2009Co-Authors: Seyit Ahmet Akdag, Onder GulerAbstract:Abstract Capacity factor and economic analysis for 4 selected turbines (1,000, 1,300, 2,000, and 2,300 kW) with 6 different hub heights (50, 60, 70, 80, 90, and 100 m) have been calculated according to 13 different situations by using Real Time Series and Weibull parameters which have been determined for Canakkale region in Part 1. As a result of the study, it has been found that kWh energy cost for the region is between 2.254 and 2.661 kWh/eurocent.
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calculation of wind energy potential and economic analysis by using weibull distribution a case study from turkey part 2 economic analysis
Energy Sources Part B-economics Planning and Policy, 2009Co-Authors: Seyit Ahmet Akdag, Onder GulerAbstract:Abstract Capacity factor and economic analysis for 4 selected turbines (1,000, 1,300, 2,000, and 2,300 kW) with 6 different hub heights (50, 60, 70, 80, 90, and 100 m) have been calculated according to 13 different situations by using Real Time Series and Weibull parameters which have been determined for Canakkale region in Part 1. As a result of the study, it has been found that kWh energy cost for the region is between 2.254 and 2.661 kWh/eurocent.
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calculation of wind energy potential and economic analysis by using weibull distribution a case study from turkey part 1 determination of weibull parameters
Energy Sources Part B-economics Planning and Policy, 2009Co-Authors: Seyit Ahmet Akdag, Onder GulerAbstract:Abstract Wind energy potential of Canakkale region has been analyzed using Real Time Series analysis and Weibull distribution, making use of hourly average wind data of Turkish State Meteorological Service measured in 10 m height between 2001 and 2006. Weibull parameters have been calculated by using graphic, moment, and maximum likelihood methods for 50, 60, 70, 80, 90, and 100 m hub heights. It has been determined that moment method gives better results than other methods according to the R2 and root mean square error (RMSE) analysis.
Sarah Kurtz - One of the best experts on this subject based on the ideXlab platform.
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Real Time Series resistance monitoring in pv systems without the need for i v curves
IEEE Journal of Photovoltaics, 2015Co-Authors: Michael G. Deceglie, Timothy J. Silverman, Bill Marion, Sarah KurtzAbstract:We apply the physical principles of a familiar method, suns– $V_\text{oc}$ , to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting I–V curves or constructing full Series-resistance-free I–V curves. RTSR is most readily deployable at the module level on microinverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of Series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.
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Real-Time Series Resistance Monitoring in PV Systems Without the Need for I–V Curves
2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC), 2015Co-Authors: Michael G. Deceglie, Timothy J. Silverman, Bill Marion, Sarah KurtzAbstract:We apply the physical principles of a familiar method, suns– $V_\text{oc}$ , to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting I–V curves or constructing full Series-resistance-free I–V curves. RTSR is most readily deployable at the module level on microinverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of Series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.
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Real-Time Series resistance monitoring in PV systems without the need for IV curves
2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC), 2015Co-Authors: Michael G. Deceglie, Timothy J. Silverman, Bill Marion, Sarah KurtzAbstract:We apply the physical principles of a familiar method, suns-Voc, to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting IV curves or constructing full Series-resistance-free IV curves. RTSR is most readily deployable at the module level on micro-inverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of Series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.
Michael G. Deceglie - One of the best experts on this subject based on the ideXlab platform.
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Real Time Series resistance monitoring in pv systems without the need for i v curves
IEEE Journal of Photovoltaics, 2015Co-Authors: Michael G. Deceglie, Timothy J. Silverman, Bill Marion, Sarah KurtzAbstract:We apply the physical principles of a familiar method, suns– $V_\text{oc}$ , to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting I–V curves or constructing full Series-resistance-free I–V curves. RTSR is most readily deployable at the module level on microinverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of Series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.
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Real-Time Series Resistance Monitoring in PV Systems; NREL (National Renewable Energy Laboratory)
2015Co-Authors: Michael G. Deceglie, Timothy J. Silverman, Bill Marion, S. R. KurtzAbstract:We apply the physical principles of a familiar method, suns-Voc, to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting IV curves or constructing full Series-resistance-free IV curves. RTSR is most readily deployable at the module level on apply the physical principles of a familiar method, suns-Voc, to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting IV curves or constructing full Series-resistance-free IV curves. RTSR is most readily deployable at the module level on micro-inverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of Series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.
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Real-Time Series Resistance Monitoring in PV Systems Without the Need for I–V Curves
2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC), 2015Co-Authors: Michael G. Deceglie, Timothy J. Silverman, Bill Marion, Sarah KurtzAbstract:We apply the physical principles of a familiar method, suns– $V_\text{oc}$ , to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting I–V curves or constructing full Series-resistance-free I–V curves. RTSR is most readily deployable at the module level on microinverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of Series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.
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Real-Time Series resistance monitoring in PV systems without the need for IV curves
2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC), 2015Co-Authors: Michael G. Deceglie, Timothy J. Silverman, Bill Marion, Sarah KurtzAbstract:We apply the physical principles of a familiar method, suns-Voc, to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting IV curves or constructing full Series-resistance-free IV curves. RTSR is most readily deployable at the module level on micro-inverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of Series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.
Bill Marion - One of the best experts on this subject based on the ideXlab platform.
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Real Time Series resistance monitoring in pv systems without the need for i v curves
IEEE Journal of Photovoltaics, 2015Co-Authors: Michael G. Deceglie, Timothy J. Silverman, Bill Marion, Sarah KurtzAbstract:We apply the physical principles of a familiar method, suns– $V_\text{oc}$ , to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting I–V curves or constructing full Series-resistance-free I–V curves. RTSR is most readily deployable at the module level on microinverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of Series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.
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Real-Time Series Resistance Monitoring in PV Systems; NREL (National Renewable Energy Laboratory)
2015Co-Authors: Michael G. Deceglie, Timothy J. Silverman, Bill Marion, S. R. KurtzAbstract:We apply the physical principles of a familiar method, suns-Voc, to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting IV curves or constructing full Series-resistance-free IV curves. RTSR is most readily deployable at the module level on apply the physical principles of a familiar method, suns-Voc, to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting IV curves or constructing full Series-resistance-free IV curves. RTSR is most readily deployable at the module level on micro-inverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of Series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.
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Real-Time Series Resistance Monitoring in PV Systems Without the Need for I–V Curves
2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC), 2015Co-Authors: Michael G. Deceglie, Timothy J. Silverman, Bill Marion, Sarah KurtzAbstract:We apply the physical principles of a familiar method, suns– $V_\text{oc}$ , to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting I–V curves or constructing full Series-resistance-free I–V curves. RTSR is most readily deployable at the module level on microinverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of Series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.
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Real-Time Series resistance monitoring in PV systems without the need for IV curves
2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC), 2015Co-Authors: Michael G. Deceglie, Timothy J. Silverman, Bill Marion, Sarah KurtzAbstract:We apply the physical principles of a familiar method, suns-Voc, to a new application: the Real-Time detection of Series resistance changes in modules and systems operating outside. The Real-Time Series resistance (RTSR) method that we describe avoids the need for collecting IV curves or constructing full Series-resistance-free IV curves. RTSR is most readily deployable at the module level on micro-inverters or module-integrated electronics, but it can also be extended to full strings. Automated detection of Series resistance increases can provide early warnings of some of the most common reliability issues, which also pose fire risks, including broken ribbons, broken solder bonds, and contact problems in the junction or combiner box. We describe the method in detail and describe a sample application to data collected from modules operating in the field.
