The Experts below are selected from a list of 54768 Experts worldwide ranked by ideXlab platform
Susanne Lehner - One of the best experts on this subject based on the ideXlab platform.
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Ocean Wave integral parameter measurements using envisat asar Wave mode data
IEEE Transactions on Geoscience and Remote Sensing, 2011Co-Authors: Susanne Lehner, Thomas BrunsAbstract:An empirical algorithm to retrieve integral Ocean Wave parameters such as significant Wave height (SWH), mean Wave period, and Wave height of Waves with period larger than 12 s (H12) from synthetic aperture radar (SAR) images over sea surface is presented. The algorithm is an extension to the Envisat Advanced SAR (ASAR) Wave mode data based on the CWave approach developed for ERS-2 SAR Wave mode data and is thus called CWave_ENV (CWave for Envisat). Calibrated ASAR images are used as the only source of input without needing prior information from an Ocean Wave model (WAM) as the standard algorithms used in weather centers. This algorithm makes SAR an independent instrument measuring integrated Wave parameters like SWH and mean Wave period to altimeter quality. A global data set of 25 000 pairs of ASAR Wave mode images and collocated reanalysis WAM results from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used to tune CWave_ENV model coefficients. Validation conducted by comparing the retrieved SWH to in situ buoy measurements shows a scatter index of 0.24 and 0.16 when compared to the ECMWF reanalysis WAM. Two case studies are presented to evaluate the performance of the CWave_ENV algorithm for high sea state. A North Atlantic storm during which SWH is above 18 m as observed by SAR and Radar Altimeter simultaneously is analyzed. For an extreme swell case that occurred in the Indian Ocean, the potential of using SWH measurements from ASAR Wave mode data derived by the CWave_ENV algorithm is demonstrated.
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an empirical approach for the retrieval of integral Ocean Wave parameters from synthetic aperture radar data
Journal of Geophysical Research, 2007Co-Authors: Johannes Schulzstellenfleth, Thomas Konig, Susanne LehnerAbstract:[1] In this study a new empirical approach to retrieve integral Ocean Wave parameters from synthetic aperture radar (SAR) data is presented. The idea behind this computationally efficient technique is to estimate integral Ocean Wave parameters without the intermediate step of retrieving the two-dimensional Ocean Wave spectrum. The method has the radiometrically calibrated SAR image as the only source of information and is based on a quadratic model function with 22 input parameters. These parameters include the radar cross section, the image variance, and 20 parameters computed from the SAR image variance spectrum using a set of orthonormal functions. The coefficients of the quadratic function were fitted for the estimation of Hs, the mean periods Tm01, Tm02, T−10, the Wave power, and the Wave heights associated with different spectral bands. The fit procedure is based on a stepwise regression method. A data set of 12,000 globally distributed ERS-2 Wave mode image spectra and colocated WAM Ocean Wave spectra was available for the study. Two separate subsets of 6000 collocation pairs each were used to fit the model and to carry out comparisons of the retrieved Wave parameters with numerical model results. Additional comparisons were performed using NDBC buoy measurements. Scatterplots and global maps with the derived parameters are presented. It is shown that the rms of the SAR derived Hs with respect to the WAM Hs is about 0.5 m. For the mean period Tm−10 an rms of 0.72 s with a high-frequency cutoff period of about 6 s is achieved.
Qingping Zou - One of the best experts on this subject based on the ideXlab platform.
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Ocean Wave spectra from a linear polarimetric SAR
IEEE Transactions on Geoscience and Remote Sensing, 2004Co-Authors: William Perrie, Tao Xie, Qingping ZouAbstract:Conventional horizontal or vertical polarization synthetic aperture radar (SAR) images seldom perform well in detecting azimuthally traveling Ocean Waves. However, theoretical analyses suggest that linear-polarimetric backscatter measurements may be more sensitive to these Waves and, therefore, that a SAR with linear polarization is expected to give a better measurement of azimuthally traveling Ocean Waves. We derive the polarization-orientation modulation transform function and tilt modulation transform function of the linear-polarimetric SAR. Through numerical simulations based on these formulations, we examine the effects of radar and Ocean Wave parameters on linear-polarimetric SAR image spectra. We suggest a method to eliminate the 180/spl deg/ directional ambiguity in determining the true Wave direction. Our numerical simulations show that the correlation between Ocean Wave spectra and SAR image spectra is improved for larger radar incidence angles and longer Ocean Waves. For real aperture radar, we suggest that the polarimetric modulation allows measurement of Waves traveling in the azimuth direction. Moreover, as suggested by Schuler et al., this may be the dominant modulation for many SAR aircraft measurements, particularly for moderate sea states.
Ted K.a. Brekken - One of the best experts on this subject based on the ideXlab platform.
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maximum power point tracking for Ocean Wave energy conversion
IEEE Transactions on Industry Applications, 2012Co-Authors: Ean Amon, Ted K.a. Brekken, Alphonse SchacherAbstract:Many forms of renewable energy exist in the world's Oceans, with Ocean Wave energy showing great potential. However, the Ocean environment presents many challenges for cost-effective renewable energy conversion, including optimal control of a Wave energy converter (WEC). This paper presents a maximum power point tracking (MPPT) algorithm for control of a point absorber WEC. The algorithm and testing hardware are presented in detail, as well as simulated and laboratory test results. The results show that MPPT applied to Ocean Wave energy is an effective and promising control strategy.
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a power analysis and data acquisition system for Ocean Wave energy device testing
Renewable Energy, 2011Co-Authors: Ean Amon, Ted K.a. Brekken, Annette Von JouanneAbstract:In the testing of Ocean Wave energy devices, the demand for a portable and robust data acquisition and electrical loading system has become apparent. This paper investigates the development of a 30 kW inclusive system combining loading capabilities, real-time power analysis, and data acquisition for the testing of deployed Ocean Wave energy devices. Hardware results for Ocean testing are included.
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reserve requirement impacts of large scale integration of wind solar and Ocean Wave power generation
IEEE Transactions on Sustainable Energy, 2011Co-Authors: D A Halamay, Ted K.a. Brekken, Asher Simmons, Shaun McarthurAbstract:Many sources of renewable energy, including solar, wind, and Ocean Wave, offer significant advantages such as no fuel costs and no emissions from generation. However, in most cases these renewable power sources are variable and nondispatchable. The utility grid is already able to accommodate the variability of the load and some additional variability introduced by sources such as wind. However, at high penetration levels, the variability of renewable power sources can severely impact the utility reserve requirements. This paper presents an analysis of the interaction between the variability characteristics of the utility load, wind power generation, solar power generation, and Ocean Wave power generation. The results show that a diversified variable renewable energy mix can reduce the utility reserve requirement and help reduce the effects of variability.
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Ocean Wave power data generation for grid integration studies
Power and Energy Society General Meeting, 2010Co-Authors: Shaun Mcarthur, Ted K.a. BrekkenAbstract:Ocean Wave power is a promising renewable energy source that offers several attractive qualities, including high power density, low variability, and excellent forecastability. Within the next few years, several utility-scale Wave energy converters are planned for grid connection (e.g., Pelamis Power in Portugal and Ocean Power Technologies in Oregon, USA), with plans for more utility-scale development to follow soon after. Presently, there is little research on the impact of large Wave parks on utility operation. This paper presents a methodology for generating large-scale Wave park power time-series data that can be used for utility integration studies. In addition, this paper presents a broad, brief introduction to Ocean Wave energy fundamentals, history, and state of the art.
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Ocean Wave Energy Overview and Research at
2009Co-Authors: Ted K.a. Brekken, Annette Von Jouanne, Hai Yue HanAbstract:The solutions to today's energy challenges need to be explored through alternative, renewable and clean energy sources to enable a diverse national energy resource plan. An extremely abundant and promising source of energy exists in the world's Oceans. Ocean energy exists in the forms of Wave, tidal, marine currents, thermal (temperature gradient) and salinity. Among these forms, significant opportunities and benefits have been identified in the area of Ocean Wave energy extraction, i.e., harnessing the motion of the Ocean Waves, and converting that motion into electrical energy. This paper presents the fundamentals of Ocean Wave energy, and also a summary of the Wave energy research being conducted at Oregon State University. This paper is intended to serve as an introduction to Wave energy for scientists and engineers, particularly those with a wind energy background. I. INTRODUCTION Significant opportunities and benefits have been identified in the area of Ocean Wave energy extraction, i.e., harnessing the motion of the Ocean Waves, and converting that motion into electrical energy. Wave energy is in actuality a concentrated form of solar energy in that it is the uneven heating of the Earth's surface that creates the winds, and it is the wind that generates the Waves. With the west to east traveling global winds, it is the west coasts of land masses that see the greatest Wave energy potential, and those potentials increase toward the Earth's poles. Waves have several advantages over other forms of renew- able energy such as wind and solar, in that the Waves are more available (seasonal, but more constant) and more predictable with better demand matching. Wave energy also offers higher energy densities, enabling devices to extract more power from a smaller volume at consequent lower costs and reduced visual impact. The Electric Power Research Institute (EPRI) has estimated that the Wave energy resource potential that could be credibly harnessed in the U.S. is equivalent to the nation's existing hydro power resource (about 6.5% of the total U.S. electricity supply). These estimates correspond to 260 TWh/yr, or an average power of 30,000 MW. Considering that 50% of the U.S. population lives within 50 miles of the coastline, Wave energy presents a promising addition to the nation's renewable energy portfolio, by providing power where it is needed (1). Ocean Wave energy technologies are in the preliminary
Peter A. E. M. Janssen - One of the best experts on this subject based on the ideXlab platform.
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Progress in Ocean Wave forecasting
Journal of Computational Physics, 2008Co-Authors: Peter A. E. M. JanssenAbstract:Progress in Ocean Wave forecasting is described in the context of the fundamental law for Wave prediction: the energy balance equation. The energy balance equation gives the rate of change of the sea state caused by adiabatic processes such as advection, and by the physical source functions of the generation of Ocean Waves by wind, the dissipation due to white-capping and the nonlinear four-Wave interactions. In this paper we discuss the formulation of the physics source functions and we discuss the numerical scheme that is used to solve the energy balance equation (with special emphasis on the so-called Garden-Sprinkler effect). Improvement in Ocean Wave forecasting skill is illustrated by comparing forecasts results with buoy observations for different years. Finally, the promising new development of the forecasting of extreme events is discussed as well.
Johannes Schulzstellenfleth - One of the best experts on this subject based on the ideXlab platform.
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an empirical approach for the retrieval of integral Ocean Wave parameters from synthetic aperture radar data
Journal of Geophysical Research, 2007Co-Authors: Johannes Schulzstellenfleth, Thomas Konig, Susanne LehnerAbstract:[1] In this study a new empirical approach to retrieve integral Ocean Wave parameters from synthetic aperture radar (SAR) data is presented. The idea behind this computationally efficient technique is to estimate integral Ocean Wave parameters without the intermediate step of retrieving the two-dimensional Ocean Wave spectrum. The method has the radiometrically calibrated SAR image as the only source of information and is based on a quadratic model function with 22 input parameters. These parameters include the radar cross section, the image variance, and 20 parameters computed from the SAR image variance spectrum using a set of orthonormal functions. The coefficients of the quadratic function were fitted for the estimation of Hs, the mean periods Tm01, Tm02, T−10, the Wave power, and the Wave heights associated with different spectral bands. The fit procedure is based on a stepwise regression method. A data set of 12,000 globally distributed ERS-2 Wave mode image spectra and colocated WAM Ocean Wave spectra was available for the study. Two separate subsets of 6000 collocation pairs each were used to fit the model and to carry out comparisons of the retrieved Wave parameters with numerical model results. Additional comparisons were performed using NDBC buoy measurements. Scatterplots and global maps with the derived parameters are presented. It is shown that the rms of the SAR derived Hs with respect to the WAM Hs is about 0.5 m. For the mean period Tm−10 an rms of 0.72 s with a high-frequency cutoff period of about 6 s is achieved.
