The Experts below are selected from a list of 3015 Experts worldwide ranked by ideXlab platform
Joshua S. Stein - One of the best experts on this subject based on the ideXlab platform.
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A wavelet-based variability model (WVM) for solar PV power plants
IEEE Transactions on Sustainable Energy, 2013Co-Authors: Matthew Lave, Jan Kleissl, Joshua S. SteinAbstract:A wavelet variability model (WVM) for simulating solar photovoltaic (PV) power plant output given a single irradiance Point Sensor timeseries using spatio-temporal correlations is presented. The variability reduction (VR) that occurs in upscaling from the single Point Sensor to the entire PV plant at each timescale is simulated, then combined with the wavelet transform of the Point Sensor timeseries to produce a simulated power plant output. The WVM is validated against measurements at a 2-MW residential rooftop distributed PV power plant in Ota City, Japan and at a 48-MW utility-scale power plant in Copper Mountain, NV. The WVM simulation matches the actual power output well for all variability timescales, and the WVM compares well against other simulation methods. © 2010-2012 IEEE.
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Analyzing and simulating the reduction in PV powerplant variability due to geographic smoothing in Ota City, Japan and Alamosa, CO
2012 IEEE 38th Photovoltaic Specialists Conference (PVSC) PART 2, 2012Co-Authors: Matthew Lave, Joshua S. Stein, Abraham EllisAbstract:Ota City, Japan and Alamosa, Colorado present contrasting cases of a small rooftop distributed PV plant versus a large central PV plant. We examine the effect of geographic smoothing on the power output of each plant. 1-second relative maximum ramp rates are found to be reduced 6–10 times for the total plant output versus a single Point Sensor, though smaller reductions are seen at longer timescales. The relative variability is found to decay exponentially at all timescales as additional houses or inverters are aggregated. The rate of decay depends on both the geographic diversity within the plant and the meteorological conditions (such as cloud speed) on a given day. The Wavelet Variability Model (WVM) takes into account these geographic smoothing effects to produce simulated PV powerplant output by using a Point Sensor as input. The WVM is tested against Ota City and Alamosa, and the WVM simulation closely matches the distribution of ramp rates of actual power output.
Matthew Lave - One of the best experts on this subject based on the ideXlab platform.
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A wavelet-based variability model (WVM) for solar PV power plants
IEEE Transactions on Sustainable Energy, 2013Co-Authors: Matthew Lave, Jan Kleissl, Joshua S. SteinAbstract:A wavelet variability model (WVM) for simulating solar photovoltaic (PV) power plant output given a single irradiance Point Sensor timeseries using spatio-temporal correlations is presented. The variability reduction (VR) that occurs in upscaling from the single Point Sensor to the entire PV plant at each timescale is simulated, then combined with the wavelet transform of the Point Sensor timeseries to produce a simulated power plant output. The WVM is validated against measurements at a 2-MW residential rooftop distributed PV power plant in Ota City, Japan and at a 48-MW utility-scale power plant in Copper Mountain, NV. The WVM simulation matches the actual power output well for all variability timescales, and the WVM compares well against other simulation methods. © 2010-2012 IEEE.
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Testing a wavelet-based variability model (WVM) for solar PV power plants
2012 IEEE Power and Energy Society General Meeting, 2012Co-Authors: Matthew Lave, Jan KleisslAbstract:A wavelet variability model (WVM) for simulating photovoltaic (PV) power plant output given a single irradiance Point Sensor as input is tested at the 48MW Copper Mountain solar PV plant. 4 days with different amounts of variability are chosen for validation of the model. Comparisons of wavelet fluctuation power index (fpi) and power output ramp rates (RRs) between the input Point Sensor, WVM simulated power output, and actual power output are presenwavelet fluctuation power indexted for the 4 test days. At all timescales, the WVM simulated power output is found to match the variability of the actual power output well, and to be a strong improvement over the input Point Sensor.
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Analyzing and simulating the reduction in PV powerplant variability due to geographic smoothing in Ota City, Japan and Alamosa, CO
2012 IEEE 38th Photovoltaic Specialists Conference (PVSC) PART 2, 2012Co-Authors: Matthew Lave, Joshua S. Stein, Abraham EllisAbstract:Ota City, Japan and Alamosa, Colorado present contrasting cases of a small rooftop distributed PV plant versus a large central PV plant. We examine the effect of geographic smoothing on the power output of each plant. 1-second relative maximum ramp rates are found to be reduced 6–10 times for the total plant output versus a single Point Sensor, though smaller reductions are seen at longer timescales. The relative variability is found to decay exponentially at all timescales as additional houses or inverters are aggregated. The rate of decay depends on both the geographic diversity within the plant and the meteorological conditions (such as cloud speed) on a given day. The Wavelet Variability Model (WVM) takes into account these geographic smoothing effects to produce simulated PV powerplant output by using a Point Sensor as input. The WVM is tested against Ota City and Alamosa, and the WVM simulation closely matches the distribution of ramp rates of actual power output.
Jan Kleissl - One of the best experts on this subject based on the ideXlab platform.
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A wavelet-based variability model (WVM) for solar PV power plants
IEEE Transactions on Sustainable Energy, 2013Co-Authors: Matthew Lave, Jan Kleissl, Joshua S. SteinAbstract:A wavelet variability model (WVM) for simulating solar photovoltaic (PV) power plant output given a single irradiance Point Sensor timeseries using spatio-temporal correlations is presented. The variability reduction (VR) that occurs in upscaling from the single Point Sensor to the entire PV plant at each timescale is simulated, then combined with the wavelet transform of the Point Sensor timeseries to produce a simulated power plant output. The WVM is validated against measurements at a 2-MW residential rooftop distributed PV power plant in Ota City, Japan and at a 48-MW utility-scale power plant in Copper Mountain, NV. The WVM simulation matches the actual power output well for all variability timescales, and the WVM compares well against other simulation methods. © 2010-2012 IEEE.
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Testing a wavelet-based variability model (WVM) for solar PV power plants
2012 IEEE Power and Energy Society General Meeting, 2012Co-Authors: Matthew Lave, Jan KleisslAbstract:A wavelet variability model (WVM) for simulating photovoltaic (PV) power plant output given a single irradiance Point Sensor as input is tested at the 48MW Copper Mountain solar PV plant. 4 days with different amounts of variability are chosen for validation of the model. Comparisons of wavelet fluctuation power index (fpi) and power output ramp rates (RRs) between the input Point Sensor, WVM simulated power output, and actual power output are presenwavelet fluctuation power indexted for the 4 test days. At all timescales, the WVM simulated power output is found to match the variability of the actual power output well, and to be a strong improvement over the input Point Sensor.
Jaejoong Kwon - One of the best experts on this subject based on the ideXlab platform.
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Multiplexed strain Sensor using fiber grating-tuned fiber laser\nwith a semiconductor optical amplifier
IEEE Photonics Technology Letters, 2001Co-Authors: Jaejoong Kwon, Sungchul Kim, Byoungho LeeAbstract:A novel fiber Bragg grating Sensor system using a fiber laser with\na semiconductor optical amplifier as a gain medium is proposed. The\ninhomogeneous broadening property of the semiconductor optical amplifier\nis used to generate multiple wavelength operation, which was not\npossible in an erbium-doped fiber laser due to the homogeneous\nbroadening property. Using a semiconductor optical amplifier, the Sensor\nsystem can involve multiple Point Sensor heads, which is an eight-Point\nSensor in the initial experiment
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Multiplexed strain Sensor using fiber grating-tuned fiber laser with a semiconductor optical amplifier
IEEE Photonics Technology Letters, 2001Co-Authors: Jaejoong KwonAbstract:A novel fiber Bragg grating Sensor system using a fiber laser with a semiconductor optical amplifier as a gain medium is proposed. The inhomogeneous broadening property of the semiconductor optical amplifier is used to generate multiple wavelength operation, which was not possible in an erbium-doped fiber laser due to the homogeneous broadening property. Using a semiconductor optical amplifier, the Sensor system can involve multiple Point Sensor heads, which is an eight-Point Sensor in the initial experiment.
Stewart D. Cusworth - One of the best experts on this subject based on the ideXlab platform.
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Wavelength division multiplexed optical Point-Sensor networks using injection laser diode sources
Optics and Laser Technology, 1996Co-Authors: John M. Senior, Steven E. Moss, Stewart D. CusworthAbstract:Abstract Wavelength division multiplexing (WDM) offers an elegant solution to the problem of increasing Sensor numbers on an optical Point-Sensor network. In this paper the provision of WDM optical Point-Sensor networks is examined by determining the optical power budgets required for their implementation. A substantial increase in the number of distributed optical Point-senors is demonstrated when using injection laser diode sources in conjunction with two new power-efficient WDM Sensor network topologies.
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Improved performance of power-efficient topologies for wdm optical Sensor networks using an extended spectral-width broadband led
Microwave and Optical Technology Letters, 1993Co-Authors: John M. Senior, Steven E. Moss, Stewart D. CusworthAbstract:The provision of WDM multiple optical Point-Sensor networks is examined by modeling the power budgets required for their implementation. A larger number of distributed optical Point Sensors are indicated than previously obtained by using an extended spectral width broadband LED together with two power-efficient WDM Sensor network topologies. © 1993 John Wiley & Sons, Inc.
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Use of extended-spectral-width broadband LEDs within WDM Point-Sensor networks
Fibers, 1993Co-Authors: John M. Senior, Steven E. Moss, Stewart D. CusworthAbstract:Spectral slicing of a broadband LED source is an efficient method for providing multiple wavelength channels for WDM Sensor networking. However, optical power budgetary considerations limit the numbers that can be accommodated even with the use of power efficient topologies. Very recently, extended spectral width broadband LEDs have become available which provide spectral widths greater than 120 nm. Such LED devices exhibit both power output and spectral width capabilities comparable with the combined effect of two or three conventional LEDs. This paper reports on an investigation of the performance of such devices in relation to their utilization within WDM Point-Sensor networks. Furthermore, specific available device characteristics are utilized within a WDM Sensor network modeling process in order to determine the maximum number of Sensors that can be accommodated on various power efficient topologies. Hence, it is demonstrated that the use of these very broadband LED sources can facilitate significantly larger numbers of Sensors than may be accommodated by employing spectral slicing of conventional LEDs.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
