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You searched for subject:(Harmonic allocation). Showing records 1 – 2 of 2 total matches.

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1. Cho, Namhun. Allocation of individual harmonic emission limits in accordance with the principles of IEC/TR 61000-3-6.

Degree: PhD, Electrical and Computer Engineering, 2013, Georgia Tech

A model of the accurate harmonic allocation methods is developed to improve the current emission limits of IEEE Std.519. IEC 61000-3-6 and IEEE Std. 519 have by now been accepted as two well known standards for interconnecting the MV and HV-EHV customers to utility systems and widely adopted as standards to many power utilities. It is worth noting that the harmonic current emission limits of both standards have not been compared and justified with analytical proofs because there is still no explanation that discusses the origin of the emission limits in IEEE Std. 519, or the complex feature of IEC 61000-3-6. Two new novel methods of allocating the harmonic current emission limits for MV customers and HV-EHV customers have been proposed. Both methods have been developed in accordance with the principles of IEC 61000-3-6. Task II has compared and investgated the emission limits of both IEC 61000-3-6 and IEEE Std. 519. The difference, inconsistency and inaccuracy have been proven with the perspective of practical evaluations based on their own principles. The investigations focus on the specific numerical proofs of the resulting voltage distortions and the current emission limits in the MV and HV-EHV systems rather than on the philosophies. The proposed methods strongly support IEC 61000-3-6 and IEEE Std. 519, and add to their value; these methods could also help utilities allocate fairly and accurately harmonic emission limits to their MV and HV-EHV customers. Advisors/Committee Members: Begovic, Miroslav (advisor), Habetler, Thomas (committee member), Harley, Ronald (committee member), Ghovanloo, Maysam (committee member), Pan, Ronghua (committee member).

Subjects/Keywords: Harmonic allocation; Harmonic emission limits; Distribution automation systems; Power quality; Harmonics (Electric waves); Electric waves; Electric standards

harmonic allocation methods for medium voltage (MV), high voltage (HV) and… …x29; below the limits specified by the utility. Allocation of harmonic emissions to MV and… …harmonic allocation. The evaluation procedure is designed in such a way that harmonic emissions… …x5B;2] are two types of well-known harmonic allocation standards. Their philosophies in… …primary objective of this PhD research is to propose the exact harmonic allocation methods… 

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

APA (6th Edition):

Cho, N. (2013). Allocation of individual harmonic emission limits in accordance with the principles of IEC/TR 61000-3-6. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/49075

Chicago Manual of Style (16th Edition):

Cho, Namhun. “Allocation of individual harmonic emission limits in accordance with the principles of IEC/TR 61000-3-6.” 2013. Doctoral Dissertation, Georgia Tech. Accessed October 20, 2019. http://hdl.handle.net/1853/49075.

MLA Handbook (7th Edition):

Cho, Namhun. “Allocation of individual harmonic emission limits in accordance with the principles of IEC/TR 61000-3-6.” 2013. Web. 20 Oct 2019.

Vancouver:

Cho N. Allocation of individual harmonic emission limits in accordance with the principles of IEC/TR 61000-3-6. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/1853/49075.

Council of Science Editors:

Cho N. Allocation of individual harmonic emission limits in accordance with the principles of IEC/TR 61000-3-6. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/49075


University of Florida

2. Chen, Zhe. Inference for the Number of Topics in the Latent Dirichlet Allocation Model via Bayesian Mixture Modelling.

Degree: PhD, Statistics, 2015, University of Florida

Latent Dirichlet Allocation (LDA) is a model that is used for automatically organizing, understanding, searching, and summarizing a corpus of documents. Let V be the set of all words that appear at least once in at least one document. By definition, a topic is a distribution on V. LDA posits that for every word in every document, there is a latent topic from which that word is drawn. In standard LDA, the number of topics, T, must be specified in advance. A prior distribution is placed on the T topics, and also on the latent word-specific topic-indicator variables that are associated with each word in the corpus. The need to specify T in advance is restrictive. One way of dealing with this problem is to put a prior on T, but unfortunately the distribution on the latent variables is then a mixture of distributions on spaces of different dimensions, and estimating this mixture distribution by MCMC is very difficult. We present a variant of the Metropolis-Hastings algorithm that can be used to estimate this mixture distribution, and in particular the posterior distribution of the number of topics. We evaluate our methodology on synthetic data, and compare it with a procedure given in Griffiths and Steyvers (2004). We also give an illustration on two collections of articles from Wikipedia. ( en ) Advisors/Committee Members: DOSS,JOHN (committee chair), MICHAILIDIS,GEORGE (committee member), BANERJEE,ARUNAVA (committee member).

Subjects/Keywords: Ergodic theory; Estimation methods; Estimators for the mean; Harmonic mean; Integers; Linear discriminant analysis; Markov chains; Normalizing; Statistical models; Wikipedia; allocation  – carlor  – chain  – dirichlet  – ergodicity  – latent  – markov  – mixture  – model  – modelling  – monte  – topic  – uniform

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

APA (6th Edition):

Chen, Z. (2015). Inference for the Number of Topics in the Latent Dirichlet Allocation Model via Bayesian Mixture Modelling. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0049399

Chicago Manual of Style (16th Edition):

Chen, Zhe. “Inference for the Number of Topics in the Latent Dirichlet Allocation Model via Bayesian Mixture Modelling.” 2015. Doctoral Dissertation, University of Florida. Accessed October 20, 2019. http://ufdc.ufl.edu/UFE0049399.

MLA Handbook (7th Edition):

Chen, Zhe. “Inference for the Number of Topics in the Latent Dirichlet Allocation Model via Bayesian Mixture Modelling.” 2015. Web. 20 Oct 2019.

Vancouver:

Chen Z. Inference for the Number of Topics in the Latent Dirichlet Allocation Model via Bayesian Mixture Modelling. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2019 Oct 20]. Available from: http://ufdc.ufl.edu/UFE0049399.

Council of Science Editors:

Chen Z. Inference for the Number of Topics in the Latent Dirichlet Allocation Model via Bayesian Mixture Modelling. [Doctoral Dissertation]. University of Florida; 2015. Available from: http://ufdc.ufl.edu/UFE0049399

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