878 resultados para Power system stability


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Työn tavoitteena oli kartoittaa vaihtoehtoisia menetelmiä perinteiselle aikatasossa tapahtuvalle kulmastabiilisuuden mallinnukselle käyttövarmuustarkastelussa. Vaihtoehtoisiin menetelmiin tutustuttiin kirjallisuuden avulla ja valittiin menetelmä testattavaksi pohjoismaisessa yhteiskäyttöjärjestelmässä. Vaihtoehtoisen menetelmän ominaisuusvaatimuksiin kuului nopeampi laskenta, luotettava stabiilien ja epästabiilien tilanteiden seulontakyky ja menetelmän antama indeksi stabiilisuus-/epästabiilisuusasteesta. Pääasiassa menetelmät, joihin tutustuttiin, arvioivat vain transienttia stabiilisuutta. SIME-menetelmä soveltui myös dynaamisen stabiilisuuden arviointiin. Suomessa voi dynaamisella stabiilisuudella olla tulevaisuudessa merkittävä rooli käyttövarmuustarkasteluissa. SIME-menetelmän toimivuutta testattiin osin yksinkertaistetulla Nordel-verkkomallilla, ja saadut tulokset olivat lupaavia. Menetelmä täytti uudelle menetelmälle asetetut vaatimukset, vaikka ongelmiakin esiintyi. Testauksessa käytetyn menetelmän edelleen kehittäminen ja menetelmän testaaminen täydellisellä verkkomallilla on suositeltavaa.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Na presente tese propõe-se uma metodologia de ajuste ótimo dos controladores do conversor interligado ao rotor de aerogeradores de indução duplamente excitados (DFIG), utilizando algoritmos genéticos (AG), com o objetivo de melhorar a segurança e a robustez do sistema elétrico de potência, permitindo que os aerogeradores DFIG participem da gestão técnica do sistema. Para garantir este objetivo, é utilizada uma estratégia de proteção do tipo “crow-bar” durante a falta, mantendo o conversor interligado ao rotor conectado à máquina. Imediatamente após a eliminação da falta, o “crow-bar” é desativado, e simultaneamente os controladores ótimos do conversor interligado ao rotor são acionados, previamente ajustados pelo AG, a fim de melhorar a capacidade de sobrevivência a afundamentos de tensão “ridethrough capability” e a margem de estabilidade global do sistema elétrico. Para validação da metodologia ótima desenvolvida foram realizadas simulações computacionais utilizando uma rede elétrica real, em três condições operacionais distintas.

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Esse trabalho compara os algoritmos C4.5 e MLP (do inglês “Multilayer Perceptron”) aplicados a avaliação de segurança dinâmica ou (DSA, do inglês “Dynamic Security Assessment”) e em projetos de controle preventivo, com foco na estabilidade transitória de sistemas elétricos de potência (SEPs). O C4.5 é um dos algoritmos da árvore de decisão ou (DT, do inglês “Decision Tree”) e a MLP é um dos membros da família das redes neurais artificiais (RNA). Ambos os algoritmos fornecem soluções para o problema da DSA em tempo real, identificando rapidamente quando um SEP está sujeito a uma perturbação crítica (curto-circuito, por exemplo) que pode levar para a instabilidade transitória. Além disso, o conhecimento obtido de ambas as técnicas, na forma de regras, pode ser utilizado em projetos de controle preventivo para restaurar a segurança do SEP contra perturbações críticas. Baseado na formação de base de dados com exaustivas simulações no domínio do tempo, algumas perturbações críticas específicas são tomadas como exemplo para comparar os algoritmos C4.5 e MLP empregadas a DSA e ao auxílio de ações preventivas. O estudo comparativo é testado no sistema elétrico “New England”. Nos estudos de caso, a base de dados é gerada por meio do programa PSTv3 (“Power System Toolbox”). As DTs e as RNAs são treinada e testadas usando o programa Rapidminer. Os resultados obtidos demonstram que os algoritmos C4.5 e MLP são promissores nas aplicações de DSA e em projetos de controle preventivo.

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Pós-graduação em Engenharia Elétrica - FEIS

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In the doctoral dissertation, low-voltage direct current (LVDC) distribution system stability, supply security and power quality are evaluated by computational modelling and measurements on an LVDC research platform. Computational models for the LVDC network analysis are developed. Time-domain simulation models are implemented in the time-domain simulation environment PSCAD/EMTDC. The PSCAD/EMTDC models of the LVDC network are applied to the transient behaviour and power quality studies. The LVDC network power loss model is developed in a MATLAB environment and is capable of fast estimation of the network and component power losses. The model integrates analytical equations that describe the power loss mechanism of the network components with power flow calculations. For an LVDC network research platform, a monitoring and control software solution is developed. The solution is used to deliver measurement data for verification of the developed models and analysis of the modelling results. In the work, the power loss mechanism of the LVDC network components and its main dependencies are described. Energy loss distribution of the LVDC network components is presented. Power quality measurements and current spectra are provided and harmonic pollution on the DC network is analysed. The transient behaviour of the network is verified through time-domain simulations. DC capacitor guidelines for an LVDC power distribution network are introduced. The power loss analysis results show that one of the main optimisation targets for an LVDC power distribution network should be reduction of the no-load losses and efficiency improvement of converters at partial loads. Low-frequency spectra of the network voltages and currents are shown, and harmonic propagation is analysed. Power quality in the LVDC network point of common coupling (PCC) is discussed. Power quality standard requirements are shown to be met by the LVDC network. The network behaviour during transients is analysed by time-domain simulations. The network is shown to be transient stable during large-scale disturbances. Measurement results on the LVDC research platform proving this are presented in the work.

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This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

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This work presents a methodology to analyze transient stability for electric energy systems using artificial neural networks based on fuzzy ARTMAP architecture. This architecture seeks exploring similarity with computational concepts on fuzzy set theory and ART (Adaptive Resonance Theory) neural network. The ART architectures show plasticity and stability characteristics, which are essential qualities to provide the training and to execute the analysis. Therefore, it is used a very fast training, when compared to the conventional backpropagation algorithm formulation. Consequently, the analysis becomes more competitive, compared to the principal methods found in the specialized literature. Results considering a system composed of 45 buses, 72 transmission lines and 10 synchronous machines are presented. © 2003 IEEE.

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The complexity of power systems has increased in recent years due to the operation of existing transmission lines closer to their limits, using flexible AC transmission system (FACTS) devices, and also due to the increased penetration of new types of generators that have more intermittent characteristics and lower inertial response, such as wind generators. This changing nature of a power system has considerable effect on its dynamic behaviors resulting in power swings, dynamic interactions between different power system devices, and less synchronized coupling. This paper presents some analyses of this changing nature of power systems and their dynamic behaviors to identify critical issues that limit the large-scale integration of wind generators and FACTS devices. In addition, this paper addresses some general concerns toward high compensations in different grid topologies. The studies in this paper are conducted on the New England and New York power system model under both small and large disturbances. From the analyses, it can be concluded that high compensation can reduce the security limits under certain operating conditions, and the modes related to operating slip and shaft stiffness are critical as they may limit the large-scale integration of wind generation.

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This paper introduces a method to analyze and predict stability and transient performance of a distributed system where COTS (Commercial-off-the-shelf) modules share an input filter. The presented procedure is based on the measured data from the input and output terminals of the power modules. The required information for the analysis is obtained by performing frequency response measurements for each converter. This attained data is utilized to compute special transfer functions, which partly determine the source and load interactions within the converters. The system level dynamic description is constructed based on the measured and computed transfer functions introducing cross-coupling mechanisms within the system. System stability can be studied based on the well-known impedance- related minor-loop gain at an arbitrary interface within the system.