Дисертації з теми "Wind Speed Estimation"
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Piper, Benjamin. "SODAR comparison methods for compatible wind speed estimation." Thesis, University of Salford, 2011. http://usir.salford.ac.uk/16501/.
Повний текст джерелаSimley, Eric J. "Wind Speed Preview Measurement and Estimation for Feedforward Control of Wind Turbines." Thesis, University of Colorado at Boulder, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3721887.
Повний текст джерелаWind turbines typically rely on feedback controllers to maximize power capture in below-rated conditions and regulate rotor speed during above-rated operation. However, measurements of the approaching wind provided by Light Detection and Ranging (lidar) can be used as part of a preview-based, or feedforward, control system in order to improve rotor speed regulation and reduce structural loads. But the effectiveness of preview-based control depends on how accurately lidar can measure the wind that will interact with the turbine.
In this thesis, lidar measurement error is determined using a statistical frequency-domain wind field model including wind evolution, or the change in turbulent wind speeds between the time they are measured and when they reach the turbine. Parameters of the National Renewable Energy Laboratory (NREL) 5-MW reference turbine model are used to determine measurement error for a hub-mounted circularly-scanning lidar scenario, based on commercially-available technology, designed to estimate rotor effective uniform and shear wind speed components. By combining the wind field model, lidar model, and turbine parameters, the optimal lidar scan radius and preview distance that yield the minimum mean square measurement error, as well as the resulting minimum achievable error, are found for a variety of wind conditions. With optimized scan scenarios, it is found that relatively low measurement error can be achieved, but the attainable measurement error largely depends on the wind conditions. In addition, the impact of the induction zone, the region upstream of the turbine where the approaching wind speeds are reduced, as well as turbine yaw error on measurement quality is analyzed.
In order to minimize the mean square measurement error, an optimal measurement prefilter is employed, which depends on statistics of the correlation between the preview measurements and the wind that interacts with the turbine. However, because the wind speeds encountered by the turbine are unknown, a Kalman filter-based wind speed estimator is developed that relies on turbine sensor outputs. Using simulated lidar measurements in conjunction with wind speed estimator outputs based on aeroelastic simulations of the NREL 5-MW turbine model, it is shown how the optimal prefilter can adapt to varying degrees of measurement quality.
Bezerra, Rufino Ferreira Paiva Eduardo. "Wind Velocity Estimation for Wind Farms." Electronic Thesis or Diss., Université Paris sciences et lettres, 2023. http://www.theses.fr/2023UPSLM046.
Повний текст джерелаThis thesis designs algorithms to estimate the wind speed and direction for wind turbines and wind farms.First, we propose data-based methods to estimate the Rotor Effective Wind Speed (REWS) for a single turbine without prior knowledge of certain physical parameters of the turbine that might be unknown to an operator.We provide two data-based methods, based respectively on Gaussian Process Regression (GPR) and on an combination of GPR with high-gain observers.Second, grounding on this REWS estimation at the local level of one turbine, we address the question of estimating the free-flow wind at the level of a wind farm.We start by focusing on wind speed estimation, for a given known wind direction. For a wind farm with a simple geometry, we prove that a local speed measurement disturbed by the presence of the turbines can be used to estimate the free-flow wind speed. We ground our estimation methodology on a simplified wake model, which consists of first-order hyperbolic partial differential equations, the transport speed of which is the free-flow wind speed. We propose to use an analytical solution of these equations, involving transport delays, to perform an estimate of the local measurement and to update the free-flow wind speed estimate. We formally prove the convergence of this estimate and numerically illustrate the efficiency of this method.Finally, we move to a more general setup where both the free-flow wind speed and direction are unknown. We propose to use a two-dimensional wake model and to rely on an optimization-based method. This identification problem reveals to be particularly challenging due to the appearance of transport delays, but we illustrate how to circumvent this issue by considering an average value of the free flow wind speed history. Simulation results obtained with the simulator FAST.Farm illustrate the interest of the proposed method
Tsang, Ho-on Frederick, and 曾可安. "Time variable parameter estimation on the wind speed air quality modelin Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1995. http://hub.hku.hk/bib/B31253283.
Повний текст джерелаTsang, Ho-on Frederick. "Time variable parameter estimation on the wind speed air quality model in Hong Kong /." Hong Kong : University of Hong Kong, 1995. http://sunzi.lib.hku.hk/hkuto/record.jsp?B14723554.
Повний текст джерелаNielsen, Mark A. "Parameter Estimation for the Two-Parameter Weibull Distribution." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/2509.
Повний текст джерелаMiguel, José Vítor Pereira. "A influência da duração da campanha de medição anemométrica na avaliação de recursos eólicos com base na aplicação de métodos MCP." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/106/106131/tde-18012017-144634/.
Повний текст джерелаDriven by the energy auctions system, the energetic harnessing of wind resource in Brazil is now going through a phase of expansion in participation in the national electric energy mix. Nevertheless, the performance of power generation of in-operation wind farms was monitored and the results proved to be, on average, below what was initially entrusted to the National Grid System, indicating that the energy production estimations projected by some energy auctions winners could have been overestimated. This scenario has caused the requirements for participating in the energy auctions to be more conservative, with measures such as the adoption of the P90 on the calculation of the physical guarantee and the increase of the wind measurement campaigns time span the latter to be enforced as of 2017. The wind is a stochastic resource, hence there are uncertainties intrinsic to the Wind Resource Assessment that influence a wind farms power generation estimation and that need to be properly identified, quantified and reduced, as far as possible. In this respect, the influence of a wind measurement campaigns time span on the Wind Resource Assessment based on MCP methods an important tool in the process of characterizing the long-term wind regime was studied in order to detect the potential of enhancing the accuracy of wind power generation forecasts. For this purpose, four databases containing time series of wind speed and direction belonging to a target site were used. Firstly, nine different MCP methods were tested and compared, of which the Vertical Slice method implemented on the software Windographer outperformed all the others according to the Mean Absolute Error and Root Mean Square Error metrics. Subsequently, the databases were set to simulate campaigns with time spans varying from 2 to 6 years, in such a way to evaluate the behavior of the uncertainty in the long-term wind speed and to analyze how this uncertainty impacts the calculation of the energy production estimation of an array of wind turbines hypothetically placed on that target site. From the analyzed data and cases, it was verified that, as the wind measurement campaigns time span was increased, the uncertainty in the long-term wind speed was significantly diminished, thereby reducing the overall uncertainty that pervades the wind power harnessing. Furthermore, the energy production estimation of the exemplified hypothetical wind farm also decreased, allowing an improvement on the accuracy of the energy generation prediction and benefiting the reliability of wind power in the Brazilian electric system.
Esmaili, Gholamreza. "Application of advanced power electronics in renewable energy sourcesand hybrid generating systems." The Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=osu1141850833.
Повний текст джерелаHaas, Rabea [Verfasser], Michael [Akademischer Betreuer] Kerschgens, and Andreas [Akademischer Betreuer] Fink. "Estimation of regional-scale wind and gust speeds for Europe by statistical-dynamical downscaling / Rabea Haas. Gutachter: Michael Kerschgens ; Andreas Fink." Köln : Universitäts- und Stadtbibliothek Köln, 2014. http://d-nb.info/1071651358/34.
Повний текст джерелаPradhan, P. P. "Wind speed estimation using neural networks." Thesis, 2014. http://ethesis.nitrkl.ac.in/5637/1/E-70.pdf.
Повний текст джерелаYANG, PO-SHUN, and 楊博舜. "Wind Speed Estimation and Wind Quality Decision based on Kalman Filtering." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/88g5p2.
Повний текст джерела國立高雄科技大學
電腦與通訊工程系
107
Wind speed measurements are used in many environments, such as highways, MRT elevated roads, and wind turbines. Excessive wind power may cause disasters, so detecting wind speed is one of the most important factors for safety. At present, the general wind speed warning system uses the average wind speed or the instantaneous wind speed as the decision-making basis for issuing warnings. It may cause the measurement data to be averaged, so that the average wind speed cannot reflect the current real situation, and the instantaneous wind speed may float near the warning threshold without correctly triggering the warning. Therefore, this thesis proposes a wind quality decision system, using Kalman filter as the wind parameter estimator, and applying new wind parameters to the wind system model for parameter estimation. The results show that the wind quality decision system can provide earlier decisions than the previous system model, and the probability of correctly triggering the warning increases as the instantaneous wind speed floats near the wind speed warning threshold. Therefore, the overall performance may be improved by using the proposed decision system for determining the wind quality.
CHANG, ZONG-YI, and 張榕帟. "Estimation on Wind Speed and Status AssessmentUsing Kalman Filtering." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/65g4v7.
Повний текст джерела國立高雄第一科技大學
電腦與通訊工程系碩士班
106
Wind speed measuring are used in many environments where winds are too large to cause disasters, so detecting wind speed is one of the most important factors for safety. Current warning system works out with an average or instant maximum wind speed as a parameter. The measurement data might be desalinated or activated by detecting maximum wind speed and lead to tragedy without making a current decision. To improve the accuracy or lower the probability of misjudgment, we use Kalman Filter to estimate wind speed and wind acceleration on its recursive estimation and correction formula. Average wind speed estimation might have credibility problem by averaging critical values. It could cause the detention and inappropriate to the warning system and make a unsuitable decision of current situation. After Kalman Filtering, wind speed and wind acceleration were used as decision parameter. We observed the untness using average or instant maximum wind speed as a decision parameter from different experiment. The wind parameter after Kalman Filtering can be suitable to different kinds of situations. The results show three different kinds of wind parameter processed by Kalman Filter and combined with sliding window signal processing giving suitable feedback to reduce the probability of misjudgment, avoiding the dangerous to drive from strong wind. By using the proposed decision assisted system, we can improve the accuracy of warning system and improve the safety factors of related applications.
Chen, Ching-Yi, and 陳卿翊. "Statistical Estimation of the Characteristics of Wind Speed & Generation in Taiwan." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/83129779496014061087.
Повний текст джерела南台科技大學
電機工程系
97
It is an important issue to master the characteristics of wind speed distribution exactly during estimating the wind energy. To evaluate the goodness of fit for the wind speed distribution in Taiwan,statistical inference is used to conduct four different probability density functions (pdf) of wind speed. The statistical characteristics of wind speed are analyzed from the histograms. The thesis tests the impact of variations of histogram interval number to the Root Mean Square probability error. The Monte Carlo based simulation, modified from maximum likelihood method, is proposed to conduct the best shape and scale parameters in the pdf of wind speed. The wind speed data form eight weather stations of the Central Weather Bureau during year of 2003-2008 are used to test. Results show that the Weibull distribution may be not the best pdf in the all eight testing locations in Taiwan. The Gamma pdf is more suitable to represent the characteristics of wind speed in the Chengkung & Tungchitao terrain. The most potential wind resource in Taiwan, Lanyu, Gamma or Rayleigh pdf are suitable than Weibull model. The capacity & available factor are used as index to verify the most suitable wind unit in Taiwan from the 22 chosen popular wind generators. The wind speed estimated at 100 meter height in the testing locations are evaluated the capacity factor of 22 wind generators. Results show that the Vestas V90_1.8M site is the appropriate choice in the seven testing locations, expect for YungKang.
Prajapat, Ganesh Prasad. "Advanced modeling and control of DFIG based wind turbine systems." Thesis, 2018. http://localhost:8080/xmlui/handle/12345678/7602.
Повний текст джерелаYum, Sang Guk. "Extreme Storm Surge Return Period Prediction Using Tidal Gauge Data and Estimation of Damage to Structures from Storm-Induced Wind Speed in South Korea." Thesis, 2019. https://doi.org/10.7916/d8-44c4-3150.
Повний текст джерелаGah, Shr Je, and 高士哲. "Estimation of Extreme Wind Speeds by Synthetic Wind Speeds Time Histories." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/03868640929886279146.
Повний текст джерела國立臺灣科技大學
營建工程系
92
Many typhoons attack Taiwan, in Autumn and Summer. Raids of typhoons frequently damage buildings and cause the loss of lives and fortunes. Derivation of extreme wind speeds is an important factor in Wind Resistant Design. It is very difficult to estimate extreme wind speeds accurately based on short-time wind speed data. Many statistical methods used to compute n-year return period wind speeds and n-year maximum wind speeds. This study adjusts the wind speed data of Central Weather Bureau according to the prescribed criteria. Unified wind speed data are grouped into normal-speed data and typhoon-speed data; their relevant probability distribution function are studied. Monte Carlo Simulation method, in conjunction with Latin Hypercube Sampling, are used to generate synthetic wind speeds time histories in which each sample is the respective daily maximum wind speed. Finally, we use Taipei wind speeds as example. It is found that the synthetic time series yield reasonable estimates of the year-means and year-standard of the observed series. The proposed method in used to find n-year (n=10, 50, 100, 475, 1000) return period wind speeds and probability distribution statistic of n-year maximum wind speeds.