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You searched for subject:(Circular time series). Showing records 1 – 3 of 3 total matches.

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1. Gonçalves, João Silva Nunes. Avaliação do potencial eólico para geração de energia eléctrica.

Degree: 2015, Repositório Científico do Instituto Politécnico de Lisboa

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Mecânica /Energia

A importância da energia eólica no contexto das políticas ambientais associadas à produção de energia eléctrica tem vindo a crescer nos últimos anos. No entanto, devido à natureza aleatória deste tipo de geração, a integração da energia eólica nos sistemas de energia constitui um desafio, dado que a potência injectada na rede poderá sofrer oscilações bruscas resultando num desequilíbrio da mesma. Com o objectivo de compreender este tipo de fenómenos, selecionou-se um parque eólico localizado na Freita que se encontra em operação desde 2006, contabilizando uma potência instalada de 18.4 MW distribuída por oito turbinas eólicas (NOrdex N90/2300). O conjunto de dados provenientes do sistema SCADA resulta de uma frequência de amostragem de dez minutos, contendo informação relativa às variáveis, velocidade do vento, orientação das turbinas, potência activa e velocidade de rotação das pás. Através da elaboração do presente documento foram feitas duas contribuições: (1) foi proposto um modelo para o cálculo da potência activa, através da interpolação do coeficiente de potência, rendimento da caixa de velocidades e rendimento do gerador; (2) a análise da distribuição diária e anual da diferença entre a potência activa observada e a potência activa teórica com base em métodos de estatística circular. Assim, o âmbito trabalho aqui apresentado consiste na análise e tratamento de dados eólicos recorrendo a ferramentas de estatística circular como: histogramas circulares, séries temporais circulares, boxplots circulares e testes de inferência circular, tanto de ajustamento como de comparação. Além disso, foram ainda utilizados métodos de interpolação polinomiais e Gaussianos de modo a obter um método interpolativo para a potência activa da turbina Nordex N90/2300. Foram ainda utilizadas funções de densidade de probabilidade acumulada não paramétricas, de modo a caracterizar a distribuição local do vento com o fim de prever a produção anual de energia électrica do parque. Os principais resultados extraídos ao longo de todos os estudos efectuados foram: 6% da amostra de potência observada apresenta valores acima dos 2300 kW, potência nominal anunciada para a turbina Nordex N90/2300; maioritariamente a diferença positiva de potências ocorre nos meses de inverno e de maneira uniforme ao longo do dia; relativamente à diferença negativa de potências estas ocorrem com maior frequência nas horas nocturnas e entre os meses de Julho e Agosto; por fim, obtiveram-se erros relativos na estimação de energia anual do parque de 2.6% e 13% para os anos de 2012 e 2013, respectivamente.

The importance of wind energy in the contexto of environmental policies related to the production of electricity has been growing in recente years. However, due to the random nature of this type of generation, the integration of the wind energy systems is a challenge, since the power injected into the network can suffer sudden fluctuations resulting in na imbalance…

Advisors/Committee Members: Henriques, Nuno Paulo Ferreira, Carvalho, Alda Cristina Jesus Valentim Nunes de.

Subjects/Keywords: Estatística circular; Série temporal circular; Energia eólica; Parque eólico da Freita; Interpolação de potência activa; Circular statistics; Circular time series; Wind energy; Freita wind farm; Active power interpolation

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APA (6th Edition):

Gonçalves, J. S. N. (2015). Avaliação do potencial eólico para geração de energia eléctrica. (Thesis). Repositório Científico do Instituto Politécnico de Lisboa. Retrieved from http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ipl.pt:10400.21/5530

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Gonçalves, João Silva Nunes. “Avaliação do potencial eólico para geração de energia eléctrica.” 2015. Thesis, Repositório Científico do Instituto Politécnico de Lisboa. Accessed February 16, 2020. http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ipl.pt:10400.21/5530.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Gonçalves, João Silva Nunes. “Avaliação do potencial eólico para geração de energia eléctrica.” 2015. Web. 16 Feb 2020.

Vancouver:

Gonçalves JSN. Avaliação do potencial eólico para geração de energia eléctrica. [Internet] [Thesis]. Repositório Científico do Instituto Politécnico de Lisboa; 2015. [cited 2020 Feb 16]. Available from: http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ipl.pt:10400.21/5530.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Gonçalves JSN. Avaliação do potencial eólico para geração de energia eléctrica. [Thesis]. Repositório Científico do Instituto Politécnico de Lisboa; 2015. Available from: http://www.rcaap.pt/detail.jsp?id=oai:repositorio.ipl.pt:10400.21/5530

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


North Carolina State University

2. Ravindran, Palanikumar. Bayesian Analysis of Circular Data Using Wrapped Distributions.

Degree: PhD, Statistics, 2003, North Carolina State University

Circular data arise in a number of different areas such as geological, meteorological, biological and industrial sciences. We cannot use standard statistical techniques to model circular data, due to the circular geometry of the sample space. One of the common methods used to analyze such data is the wrapping approach. Using the wrapping approach, we assume that, by wrapping a probability distribution from the real line onto the circle, we obtain the probability distribution for circular data. This approach creates a vast class of probability distributions that are flexible to account for different features of circular data. However, the likelihood-based inference for such distributions can be very complicated and computationally intensive. The EM algorithm used to compute the MLE is feasible, but is computationally unsatisfactory. Instead, we use Markov Chain Monte Carlo (MCMC) methods with a data augmentation step, to overcome such computational difficulties. Given a probability distribution on the circle, we assume that the original distribution was distributed on the real line, and then wrapped onto the circle. If we can "unwrap" the distribution off the circle and obtain a distribution on the real line, then the standard statistical techniques for data on the real line can be used. Our proposed methods are flexible and computationally efficient to fit a wide class of wrapped distributions. Furthermore, we can easily compute the usual summary statistics. We present extensive simulation studies to validate the performance of our method. We apply our method to several real data sets and compare our results to parameter estimates available in the literature. We find that the Wrapped Double Exponential family produces robust parameter estimates with good frequentist coverage probability. We extend our method to the regression model. As an example, we analyze the association between ozone data and wind direction. A major contribution of this dissertation is to illustrate a technique to interpret the circular regression coefficients in terms of the linear regression model setup. Regression diagnostics can be developed after augmenting wrapping numbers to the circular data (refer Section 3.5). We extend our method to fit time-correlated data. We can compute other statistics such as circular autocorrelation functions and their standard errors very easily. We use the Wrapped Normal model to analyze the hourly wind directions, which is an example of the time series circular data. Advisors/Committee Members: Dr. John Monahan, Committee Member (advisor), Dr. Sastry Pantula, Committee Member (advisor), Dr. Peter Bloomfield, Committee Member (advisor), Dr. Sujit K. Ghosh, Committee Chair (advisor).

Subjects/Keywords: Bayesian; Circular Data; Wrapped Normal; time series; regression

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ravindran, P. (2003). Bayesian Analysis of Circular Data Using Wrapped Distributions. (Doctoral Dissertation). North Carolina State University. Retrieved from http://www.lib.ncsu.edu/resolver/1840.16/3022

Chicago Manual of Style (16th Edition):

Ravindran, Palanikumar. “Bayesian Analysis of Circular Data Using Wrapped Distributions.” 2003. Doctoral Dissertation, North Carolina State University. Accessed February 16, 2020. http://www.lib.ncsu.edu/resolver/1840.16/3022.

MLA Handbook (7th Edition):

Ravindran, Palanikumar. “Bayesian Analysis of Circular Data Using Wrapped Distributions.” 2003. Web. 16 Feb 2020.

Vancouver:

Ravindran P. Bayesian Analysis of Circular Data Using Wrapped Distributions. [Internet] [Doctoral dissertation]. North Carolina State University; 2003. [cited 2020 Feb 16]. Available from: http://www.lib.ncsu.edu/resolver/1840.16/3022.

Council of Science Editors:

Ravindran P. Bayesian Analysis of Circular Data Using Wrapped Distributions. [Doctoral Dissertation]. North Carolina State University; 2003. Available from: http://www.lib.ncsu.edu/resolver/1840.16/3022

3. Lan, Tian, active 2013. Analysis of circular data in the dynamic model and mixture of von Mises distributions.

Degree: MSin Statistics, Statistics, 2013, University of Texas – Austin

Analysis of circular data becomes more and more popular in many fields of studies. In this report, I present two statistical analysis of circular data using von Mises distributions. Firstly, the maximization-expectation algorithm is reviewed and used to classify and estimate circular data from the mixture of von Mises distributions. Secondly, Forward Filtering Backward Smoothing method via particle filtering is reviewed and implemented when circular data appears in the dynamic state-space models. Advisors/Committee Members: Carvalho, Carlos Marinho, 1978- (advisor).

Subjects/Keywords: Circular data; Von Mises distribution; Mixture of distributions; Time series; Dynamic model; Expectation-maximization algorithm; Particle filter

…may be regarded as circular measurements, with an arrival time of m minutes after midnight… …corresponding to a circular measurement of degrees; thus 1 degree corresponds to 4 minutes of time… …independent. By observing the circular data at each time point, assuming the knowledge of all the… …Smoothing for Nonlinear Time Series. Journal of the American Statistical Association 99(465… …Distances between Estimated Latent Variables and Simulated Ones at Each Time Point after One… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Lan, Tian, a. 2. (2013). Analysis of circular data in the dynamic model and mixture of von Mises distributions. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/22608

Chicago Manual of Style (16th Edition):

Lan, Tian, active 2013. “Analysis of circular data in the dynamic model and mixture of von Mises distributions.” 2013. Masters Thesis, University of Texas – Austin. Accessed February 16, 2020. http://hdl.handle.net/2152/22608.

MLA Handbook (7th Edition):

Lan, Tian, active 2013. “Analysis of circular data in the dynamic model and mixture of von Mises distributions.” 2013. Web. 16 Feb 2020.

Vancouver:

Lan, Tian a2. Analysis of circular data in the dynamic model and mixture of von Mises distributions. [Internet] [Masters thesis]. University of Texas – Austin; 2013. [cited 2020 Feb 16]. Available from: http://hdl.handle.net/2152/22608.

Council of Science Editors:

Lan, Tian a2. Analysis of circular data in the dynamic model and mixture of von Mises distributions. [Masters Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/22608

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