Spelling suggestions: "subject:"synchrophasors."" "subject:"synchrophasor's.""
11 |
Analysis of transmission system events and behavior using customer-level voltage synchrophasor dataAllen, Alicia Jen 31 October 2013 (has links)
The research topics presented in this dissertation focus on validation of customer-level voltage synchrophasor data for transmission system analysis, detection and categorization of power system events as measured by phasor measurement units (PMUs), and identification of the influence of power system conditions (wind power, daily and seasonal load variation) on low-frequency oscillations. Synchrophasor data can provide information across entire power systems but obtaining the data, handling the large dataset and developing tools to extract useful information from it is a challenge. To overcome the challenge of obtaining data, an independent synchrophasor network was created by taking synchrophasor measurements at customer-level voltage. The first objective is to determine if synchrophasor data taken at customer-level voltage is an accurate representation of power system behavior. The validation process was started by installing a transmission level (69 kV) PMU. The customer-level voltage measurements were validated by comparison of long term trends and low-frequency oscillations estimates. The techniques best suited for synchrophasor data analysis were identified after a detailed study and comparison. The same techniques were also applied to detect power system events resulting in the creation of novel categories for numerous events based on shared characteristics. The numerical characteristics for each category and the ranges of each numerical characteristic for each event category are identified. The final objective is to identify trends in power system behavior related to wind power and daily and seasonal variations by utilizing signal processing and statistical techniques. / text
|
12 |
Uma nova metodologia para detecção e identificação de erros grosseiros em sistemas de distribuição de energia elétrica utilizando unidades de medição fasorial sincronizadaMoreira, Tamiris Gomes 10 March 2016 (has links)
Submitted by isabela.moljf@hotmail.com (isabela.moljf@hotmail.com) on 2016-08-12T12:25:16Z
No. of bitstreams: 1
tamiresgomesmoreira.pdf: 4532594 bytes, checksum: 64d45fbe56c5ece94a7586a1d27d46df (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-08-15T13:22:42Z (GMT) No. of bitstreams: 1
tamiresgomesmoreira.pdf: 4532594 bytes, checksum: 64d45fbe56c5ece94a7586a1d27d46df (MD5) / Made available in DSpace on 2016-08-15T13:22:42Z (GMT). No. of bitstreams: 1
tamiresgomesmoreira.pdf: 4532594 bytes, checksum: 64d45fbe56c5ece94a7586a1d27d46df (MD5)
Previous issue date: 2016-03-10 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Esta dissertação apresenta uma nova metodologia para detecção e identificação de erros grosseiros no processo de estimação de estados para sistemas de distribuição de energia elétrica com topologia radial, usando Unidades de Medição Fasorial, conhecidas como PMUs (Phasor Measurement Units). O algoritmo de estimação de estados considera todas as correntes passantes nas linhas do sistema, expressas em coordenadas retangulares, como estadosaseremestimados. Osvaloresmedidosserãofasoresdetensãoecorrenteaquisitados pelas PMUs. A fim de restaurar a observabilidade do sistema com poucas unidades de medição serão considerados dados históricos de potência ativa/reativa demandada para as barras não monitoradas por PMUs, disponibilizados pelas concessionárias de energia elétrica. Esses valores serão considerados como restrições de desigualdade variando entre limites mínimos e máximos em um problema de otimização não linear cujo objetivo é minimizar a soma dos quadrados dos resíduos, sendo esses a diferença entre o valor da grandeza medida pela PMU e o seu correspondente valor estimado, ponderado por suas respectivas covariâncias. Baseado nos valores de corrente estimados, outras grandezas elétricas podem ser calculadas utilizando leis de Kirchhoff. Considerando a topologia radial dos alimentadores de distribuição, a proposta para o processamento de erros grosseiros consiste na divisão da rede elétrica com topologia radial em vários subsistemas, visando reduzir o esforço computacional associado ao processo de estimaçãodeestados. Ametodologiaapresentadaserádivididaeabordadaemduasetapas. A primeira se refere à detecção de erros grosseiros, sendo avaliada pelo valor da FOB para cada subsistema, onde valores acima de um determinado valor limítrofe preestabelecido para cada uma das FOBs indicam a presença de medidas com erros grosseiros. Já a segunda, baseia-se na identificação da PMU responsável por aquisitar medições com erros grosseiros e pauta-se na abordagem por barras fictícias, barras estas em que a potência demandada é nula. Os resultados obtidos são validados através do uso de sistemas testes encontrados na literatura. O problema de otimização é solucionado pelo Método de Pontos Interiores com Barreira de Segurança (Safety Barrier Interior Point Method). / This dissertation presents a novel methodology for bad data detection and identification in the State Estimation process for electrical power distribution systems with radial topology, using Phasor Measurement Units (PMUs). The state estimation algorithm considers all branch currents of the system, expresssed in rectangular coordinates, as states to be estimated. The measured values will be phasors acquisited by the PMUs. In order to make the system fully observable with few measurement units, it will be considered historical data of active/reactive power demand for the non-monitored buses, provided by the electrical utilities. These values will be considered as inequality constraints varying between minimum and maximum limits in a non-linear optimization problem which aims to minimize the sum of the squared of the residuals considering the residual being the difference between the measured values by the PMUs and their corresponding estimated values, weighted by its corresponding covariances. Based on the estimated branch currents values, other electrical quantities can be calculated by Kirchhoff’s laws. Consideringtheradialtopology,theproposedapproachforthebaddataprocessingconsists on the electrical network partitioning into various subsystems, which aims to reduce the computational effort associated to the states estimation process. The methodology presented in this work for bad data processing will be divided and implemented into two steps. The first part refers to the bad data detection and it is evaluated by the objective function value for each subsystem, in which high values indicate the presence of bad data. The second part relies on the identification of the PMU which is responsible for acquisitioningbaddataanditisaddressedintwodifferentways. Thefirstoneisaddressed for a single subsystem (single feeder) and is based on the creation of fictitious buses, which will be buses with null power demand. The obtained results are validated by using test systems found in the literature. The optimization problem is solved by the Safety Barrier Interior Point Method.
|
Page generated in 0.0433 seconds