Statistical Analysis Of Site Wind Data

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Statistical Analysis Of Site Wind Data

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Author : Ross B. Corotis
language : en
Publisher:
Release Date : 1980

Statistical Analysis Of Site Wind Data written by Ross B. Corotis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1980 with Wind power categories.

Statistical Analysis Of Wind And Rainfall With Functional Data Analysis Technique

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Author : Wan Norliyana Wan Ismail
language : en
Publisher:
Release Date : 2014

Statistical Analysis Of Wind And Rainfall With Functional Data Analysis Technique written by Wan Norliyana Wan Ismail and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Rain and rainfall categories.

A Statistical Analysis And Fuzzy Logic Approach In Assessing The Performance Of Wind Turbine In Ohio

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Author : Suleiman Mikail
language : en
Publisher:
Release Date : 2010

A Statistical Analysis And Fuzzy Logic Approach In Assessing The Performance Of Wind Turbine In Ohio written by Suleiman Mikail and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.

Abstract: The global demand for petroleum products has caused the rise in their cost. In fact, the cost of petroleum products to generate electricity supply to meet the United States' energy demand is on a continuous rise. As a result, this rise in cost of petroleum products has challenged our nation to seek an alternative source of renewable energy generation. Wind energy generation is one of the fastest growing forms of electricity generation in the world today compared to other sources of renewable energy. According to the National Renewable Energy Laboratory, the United States currently generate more than 25,000 megawatts (MW) of electricity from the wind, which is enough to power electricity supply to almost 7 million homes, and experts in wind power development predict that, with proper development, wind energy could provide 20% of the nation's energy needs. To perform an assessment for a feasible wind energy project and wind turbine performance, an empirical analysis using statistical models was performed on wind speed data collected at a proposed site for wind energy development. Because of the variability in wind speed and wind turbine location, a subjective description of wind turbine location using a fuzzy logic approach was used to define the two variables, and quantify the different components and elements of the wind turbine performance and wind turbine location, and subsequently to evaluate the total wind farm development project performance using two forms of fuzzy member. Two software programs were developed using the concept of fuzzy logic, which transforms the linguistic expressions such as "Low", "Fairly Low", "Medium", "Fairly High" and "High", into mathematical representations. The two fuzzy logic models created were the "angular model" and the "triangular model", which were used to complement the statistical models in assessing the wind turbine location and turbine performance. The angular model and triangular model incorporate users' subjective preferences and choices based on the information available to them. This study advances the assessment of a wind energy development project by harnessing the available wind resource to help meet the nation's goal of providing 20% of the nation electricity demand 2030. If properly implemented, wind energy development would help reduce the consumption of 4 trillion gallons of water and reduce CO2 emissions, reduce total natural gas consumption by 11%, reduce electric utility coal consumption by 18%, reduce electric utility natural gas consumption by 50% and avoid construction of 80 GW of new coal power plants through year 2030.

Data Science For Wind Energy

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Author : Yu Ding
language : en
Publisher: CRC Press
Release Date : 2019-06-04

Data Science For Wind Energy written by Yu Ding and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-04 with Business & Economics categories.

Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the author’s book site at https://aml.engr.tamu.edu/book-dswe. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insights

Statistical Analysis Of Extreme Winds

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Author : Emil Simiu
language : en
Publisher:
Release Date : 1975

Statistical Analysis Of Extreme Winds written by Emil Simiu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1975 with Wind-pressure categories.

Statistical Analysis Of Wind Data And Modeling Regulating Reserves

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Author : William James Buchanan
language : en
Publisher:
Release Date : 2012

Statistical Analysis Of Wind Data And Modeling Regulating Reserves written by William James Buchanan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.

The desire to reduce dependence on fossil fuels is resulting in numerous policy incentives for increased renewable energy sources within the power grid. Because wind generation is arguably the most affordable per MWh of the renewable energy sources it is growing nearly as quickly as conventional generation techniques. Due to this significant increase in wind penetration levels, numerous largescale wind integration studies have been produced to determine the reliability impacts of large-scale wind power. Using data from two large US wind interconnection studies, this thesis provides evidence that mesoscale meteorological models under-predict the variability in wind data particularly on short time scales, indicating that data from mesoscale meteorological models need to be used with caution for some types of analyses. These types of analyses include most notably regulating reserves, which are used to rebalance supply and demand on a second-by-second bias. This thesis will also describe and evaluate a new method for jointly quantifying the amount of spinning and regulating reserves required to meet reliability requirements within a balancing area with significant amounts of wind power using high resolution wind data. The method is based on jointly minimizing dispatch costs and reserve allocations, across two time scales (seconds to minutes, and minutes to hours) to satisfy North American Electric Reliability Corporation (NERC) Area Control Error (ACE) requirements.

Forecasting Of The Wind Speed Under Uncertainty

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Author : Muhammad Aslam
language : en
Publisher: Infinite Study
Release Date :

Forecasting Of The Wind Speed Under Uncertainty written by Muhammad Aslam and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.

In this paper, the semi-average method under neutrosophic statistics is introduced. The trend regression line for the semi-average method is given in the presence of Neutrosophy in the data. The application of the semi-average method under indeterminacy is given with the help of wind speed data. The efficiency of the semi-average method under the neutrosophic statistics is discussed over the semi-average method under classical statistics. From the analysis, it is concluded that the proposed method is effective, informative, and flexible for the forecasting of wind speed.

Statistical Analysis To Validate Full Scale Wind And Structural Response Data

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Author : Marc Lloyd Levitan
language : en
Publisher:
Release Date : 1988

Statistical Analysis To Validate Full Scale Wind And Structural Response Data written by Marc Lloyd Levitan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Electric lines categories.

Spatial Variation And Interpolation Of Wind Speed Statistics And Its Implication In Design Wind Load

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Author : Wei Ye
language : en
Publisher:
Release Date : 2013

Spatial Variation And Interpolation Of Wind Speed Statistics And Its Implication In Design Wind Load written by Wei Ye and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.

Consideration of wind load is important for design of engineered structures. Codification of wind load for structural design requires the estimation of the quantiles or return period values of the annual maximum wind speed. The extreme wind speeds are estimated based on the measured wind records at different meteorological stations and affected by the length of the wind record (i.e., sample size) and other factors such as the surrounding terrain and so on. This study is focused on 1) the spatial interpolation of wind speed statistics, 2) the potential of using regional frequency analysis in estimating the extreme wind speed, and 3) the reliability of designed structure at sites with and without sample size effects. For the spatial interpolation, both code recommended values of the wind speed as well as those based on at-site analysis are used, and commonly used spatial interpolation methods including 8 deterministic methods and 6 geostatistical methods have been applied. The preferred methods for each data set are determined based on the (leave-one-out) cross validation analyses. It is shown that the preferred method depends on the considered data set; the use of the ordinary kriging is preferred if a single method is to be selected for all considered data sets. The historical wind records and available meteorological stations are often short and insufficient or unavailable, and the limited sample size will cause the uncertainty in the estimated quantiles. To deal with the data insufficiency in the wind speed records at the meteorological stations, the regional frequency analysis was applied to the data from the same 235 Canadian meteorological stations as mentioned above to calculate the quantiles of the annual maximum wind speed for iii Canada. The obtained estimates of the quantiles of the extreme wind speed based on the regional frequency analysis are compared with those obtained based directly on the at-site analysis. The analysis uses the k-means, hierarchical and self-organizing map clustering to explore potential clusters or regions; statistical tests are then applied to identify homogeneous regions for subsequent regional frequency analysis. Results indicate that the k-means is the preferred exploratory tool for the considered data and the generalized extreme value distribution provides a better fit to the data than the Gumbel distribution for regional frequency analysis. However, the former is associated with low values of the upper bound that do not influence the estimation of 10-to 50-year return period values of annual maximum wind speed but do influence the return period values with return period greater than 500 years. Based on these observations, regional frequency analysis may not be needed as an alternative to the at-site analysis. Furthermore, since the estimated quantiles of the extreme wind speed at a site are uncertain due to the limited sample size, the effect of this statistical uncertainty on the estimated return period value of the wind speed and structural reliability is investigated and two strategies (i .e. (i) a low return period for the nominal wind speed combined with a wind load factor greater than one and (ii) a high return period for the nominal wind speed combined with unity wind load factor) for specifying the factored design wind load are also evaluated to determine the optimal one. Results indicate that at least 20 years of useable data are needed for a station to be included in the extreme value analysis, and the first strategy is preferred to cope with sample size effect for the design at a particular site or in a region with statistically homogeneous wind climate, while the second strategy is recommended for the code making for a country with spatially varying coefficient of variation of annual maximum wind speed since it leads to better reliab ility consistency.

Wind Statistics 1972 1980

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Author : M. J. Boyd
language : en
Publisher:
Release Date : 1982

Wind Statistics 1972 1980 written by M. J. Boyd and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1982 with Winds categories.