Stochastic assessment of unbalanced voltage dips in large transmission systems

Olguin, G.; Bollen, Math

doi:10.1109/ptc.2003.1304795

Cited by 25 publications

(28 citation statements)

References 3 publications

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“…The proposed stochastic approach uses the deterministic results of the short circuit simulation and the stochastic data about the faults. This is similar to existing prediction methods, e.g., fault position methods and the stochastic method presented in [26]. Similar to MC simulation methods, the proposed approach includes numerous uncertainty factors in the network but avoids a large number of simulations required by MC to achieve convergence.…”

Section: B Study Proceduresmentioning

confidence: 77%

“…Similarly, a number of approaches have been proposed to assess single-site indices, including fault positions-based stochastic method [20][21][22][23][24], critical distances [22,23] and Monte Carlo (MC)-based stochastic approaches [15,16,20,25]. A stochastic assessment of voltage sags is used in [26] to get the expected number and characteristics of sags using deterministic short circuit simulations and the stochastic data of the faults. Furthermore, an analytical method which does not consider the stochastic nature of network parameters and calculates sag duration based on mathematical model is used to produce the voltage sag density table in [4].…”

Section: Introductionmentioning

confidence: 99%

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Identification of Weak Areas of Network Based on Exposure to Voltage Sags—Part II: Assessment of Network Performance Using Sag Severity Index

Liao

Abdel-Rahman

Guo

et al. 2015

IEEE Trans. Power Delivery

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Abstract--This paper presents a new stochastic approach to comprehensive assessment of the impact of voltage sags in large scale power networks. The approach takes into account the stochastic nature of power system operation including load variation, uncertainty of fault clearing time by protection relays, fault rates of network components and the variation/uncertainty in equipment sensitivity to voltage sags. A new duration zone division method is used to derive sag duration and occurrence frequency based on stochastic distribution of clearing time required by specific protection systems. The adopted probabilistic representation facilitates estimation of network performance based on a single-event characteristic, sag severity index (SSI), developed in the companion paper (Part I). Based on SSI, a new single-site index with respect to voltage sags (Bus Performance Index, BPI S ) is developed to comprehensively represent the overall bus performance with respect to voltage sags. The index is used to identify the areas of the network, named weak areas of the network in this paper, containing buses that are most exposed to potentially disruptive voltage sags. The application, robustness and sensitivity of BPI S are thoroughly analysed and discussed in the paper.Index Terms-Voltage sags, equipment susceptibility, voltage tolerance curves, sag severity index. I. INTRODUCTIONoltage sags cause frequent disruptions to modern industrial processes and malfunction of electronic equipment, resulting in substantial financial losses [1]. This issue, as one of the most critical power quality problems, has become a major focal point for many utilities and industries [2]. To reduce overall financial consequences of voltage sags, it is necessary to assess voltage sag performance of network buses as accurately as possible and consequently to identify the buses that are most affected by voltage sags. Assessing voltage sag performance at certain location requires two steps: calculating single-event characteristic for each sag event; and then calculating single-site indices based on the single-event characteristics of all sag events occurring at the location [3]. Various single-site indices have been proposed in literature to assess voltage sag performance. Sag severity at certain location can be presented through probability density and distribution functions [3]. Furthermore, the sag information can be compressed into a sag table which groups the sags based on the interval of residual voltage and duration [4][5][6][7][8][9], or by using modified reliability based SAIFI index [10][11][12]. These single-site indices simply give the number of events per year within a certain range of magnitude and duration, resulting in discrete representation of sag characteristics. The aforementioned indices are not suitable for comparing the actual voltage sag performance of different buses as they typically do not include multiple sag characteristics at the same time nor, and more importantly, sensitivity of equipment connected at these buses to vo...

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Section: B Study Proceduresmentioning

confidence: 77%

Section: Introductionmentioning

confidence: 99%

Identification of Weak Areas of Network Based on Exposure to Voltage Sags—Part II: Assessment of Network Performance Using Sag Severity Index

Liao

Abdel-Rahman

Guo

et al. 2015

IEEE Trans. Power Delivery

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show abstract

“…Se o local onde ocorreu a falta possuir uma alta potência de curto-circuito, a severidade do afundamento associado será maior e poderá ser percebida por uma grande extensão do sistema. Por outro lado, se um curto-circuito ocorre em um local com baixa potência de curto-circuito, o afundamento associado será menos severo e, provavelmente, percebido em uma extensão menor do sistema (Olguin e Bollen, 2003b). Neste contexto, a propagação dos afundamentos de tensão remete a dois conceitos importantes: o de área de vulnerabilidade (ou área exposta), e o de área afetada.…”

Section: Conceitos Básicos Relacionados à Qualidade Da Energia Elétricaunclassified

Modelagem multiobjetivo para o problema da alocação de monitores de qualidade da energia em sistemas de distribuição de energia elétrica

Branco¹

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Trata-se da versão corrigida da tese. A versão original se encontra disponível na EESC/USP que aloja o Programa Problemas ocasionados por perturbações na qualidade da energia elétrica (QEE) podem provocar sérios prejuízos, tanto de cunho social, quanto financeiros, aos clientes conectados ao sistema elétrico de potência como um todo. Neste contexto, os clientes que mais sofrem são os clientes industriais, pois estes possuem cargas sensíveis a vários distúrbios associados à falta da QEE. Sendo assim, para adoções de medidas preventivas, ou corretivas, que melhorem os índices de QEE, faz-se necessário um monitoramento dos sistemas elétricos que permita um melhor acompanhamento da ocorrência dos distúrbios. Nesta pesquisa é proposta a modelagem do problema de alocação ótima de monitores de QEE em sistemas de distribuição com múltiplos objetivos, os quais são: minimização do custo do monitoramento, minimização da ambiguidade topológica, maximização do monitoramento das cargas, maximização da quanti- Problems arising from disturbances in power quality (PQ) can cause serious damage, both social, and financial, to customers connected to the electrical power distribution systems as a whole. In this context, the customers who suffer most are industrial customers, as they have loads sensitive to various disturbances associated with the lack of PQ. Thus, in order to adopt preventive or corrective measures to improve PQ rates, it is necessary to monitor electrical systems to allow better oversight of the occurrence of disturbances. In this research, the proposal is to model the problem of optimal allocation of power quality monitors in distribution systems with multiple objectives. The multiple objectives are: minimizing the monitoring cost, minimizing ambiguities in topology, maximizing the load monitoring, maximizing the area monitoring, minimizing the voltage sag unmonitored, and maximizing the redundancy in the sag monitoring. In solving the problem, a Multiobjective Evolutionary Algorithm with Tables (MEAT) was adopted due to ability to deal with many objectives. The results show that the AMET finds a set of efficient solutions that are diversified and well-distributed along the Pareto Front, and that they are highly relevant for planning of PQ monitoring systems in electrical power distribution systems. The main contribution of this thesis is to provide a model that allows utilities better evaluate investments that they will make in their monitoring systems comprising six different criteria, allowing greater flexibility in establishing the monitoring plan and a better analysis of cost/benefit considering the six aspects.

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“…Sendo assim, a literatura atual sugere que seja feita a instalação de instrumentos de medição dedicados em todos os pontos do sistema de potência em que se deseja monitorar a ocorrência das VTCDs ( [09], [10], [11] e [12]). O inconveniente desse método é a quantidade de equipamentos necessários, uma vez que medições locais em múltiplos pontos fazem com que a avaliação seja uma atividade bastante onerosa, devido à quantidade de equipamentos necessários para a detecção das perturbações, e ao tratamento do elevado volume de dados registrados, inviabilizando, por muitas vezes, o próprio sistema de monitoração.…”

Section: Considerações Geraisunclassified

“…( ( [10] r e adiciona-se a ele o valor obtido com a função-objetivo. Como a finalidade do problema é de minimizar o número de medidores, definiu-se a função de avaliação de cada indivíduo como o inverso dessa soma, como é ilustrado pela expressão [11], de maneira que os indivíduos sem posições nulas no Vetor-Redundância e com o menor número de medidores sugeridos para a instalação adquirissem um elevado valor para a sua avaliação.…”

Section: Avaliação Utilizando Algoritmo Genético Clássicounclassified

Metodologia para a monitoração eficiente de variações de tensão de curta duração em sistemas elétricos de potência.

Almeida¹

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Stochastic assessment of unbalanced voltage dips in large transmission systems

Cited by 25 publications

References 3 publications

Identification of Weak Areas of Network Based on Exposure to Voltage Sags—Part II: Assessment of Network Performance Using Sag Severity Index

Identification of Weak Areas of Network Based on Exposure to Voltage Sags—Part II: Assessment of Network Performance Using Sag Severity Index

Modelagem multiobjetivo para o problema da alocação de monitores de qualidade da energia em sistemas de distribuição de energia elétrica

Metodologia para a monitoração eficiente de variações de tensão de curta duração em sistemas elétricos de potência.

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