New approach for power transformer protection based on intelligent hybrid systems

A power transformer needs continuous monitoring and fast protection as it is a very expensive piece of equipment and an essential element in an electrical power system. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can mislead the conventional protection affecting the power system stability negatively. This study proposes the development of a new algorithm to improve the protection performance by using fuzzy logic, artificial neural networks and genetic algorithms. An electrical power system was modelled using Alternative Transients Program software to obtain the operational conditions and fault situations needed to test the algorithm developed, as well as a commercial differential relay. Results show improved reliability, as well as a fast response of the proposed technique when compared with conventional ones.FAPESP (Fundacao de Amparo a Pesquisa do Estado de Sao Paulo)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)CAPES (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior

Algorítmos genéticos aplicados a uma mais rápida proteção de distância de linhas de transmissão

The main purpose of this paper is to implement a new methodology based on Genetic Algorithms (GAs) to extract the fundamental voltage and current phasors from noisy waves in power systems to be applied to a faster distance protection. GAs solve optimization problems based on natural selection principles. This application was then formulated as an optimization problem, and the aim was to minimize the estimation error. A 440 kV, 150 km transmission line was simulated using the ATP (Alternative Transients Program) software in order to show the efficiency of the new method. The results from this application show that the global performance of GAs was highly satisfactory concerning speed and accuracy of response, if compared to the traditional Discrete Fourier Transform (DFT).O principal objetivo deste trabalho é implementar uma nova metodologia baseada em Algorítmos Genéticos (AGs) para extração de fasores fundamentais de tensão e corrente em sistemas que possibilite uma proteção de distância mais rápida. Os AGs resolvem problemas de otimização baseados nos princípios da seleção natural. Esta aplicação foi formulada como um problema de otimização, tendo como principal objetivo o de minimizar a estimação do erro entre as formas de ondas em análise. Uma linha de transmissão de 440 kV, com 150 km de extensão foi simulada através do software ATP (Alternative Transients Program) para testar a eficiência do novo método. Os resultados desta aplicação mostram que o desempenho geral do AG foi altamente satisfatório no que diz respeito a velocidade e a precisão na resposta quando comparado ao método tradicional utilizando a Transformada Discreta de Fourier

Digital frequency relaying based on the modified least mean square method

This research presents a method for frequency estimation in power systems using an adaptive filter based on the Least Mean Square Algorithm (LMS). In order to analyze a power system, three-phase voltages were converted into a complex signal applying the alpha beta-transform and the results were used in an adaptive filtering algorithm. Although the use of the complex LMS algorithm is described in the literature, this paper deals with some practical aspects of the algorithm implementation. In order to reduce computing time, a coefficient generator was implemented. For the algorithm validation, a computing simulation of a power system was carried Out using the ATP software. Many different situations were Simulated for the performance analysis of the proposed methodology. The results were compared to a commercial relay for validation, showing the advantages of the new method. (C) 2009 Elsevier Ltd. All rights reserved.CAPES (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior)CNPQ (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico)FAPESP (Fundacao de Amparo a Pesquisa do Estado de Sao Paulo

Power Transformer Differential Protection Based on Clarke`s Transform and Fuzzy Systems

The power transformer is a piece of electrical equipment that needs continuous monitoring and fast protection since it is very expensive and an essential element for a power system to perform effectively. The most common protection technique used is the percentage differential logic, which provides discrimination between an internal fault and different operating conditions. Unfortunately, there are some operating conditions of power transformers that can affect the protection behavior and the power system stability. This paper proposes the development of a new algorithm to improve the differential protection performance by using fuzzy logic and Clarke`s transform. An electrical power system was modeled using Alternative Transients Program (ATP) software to obtain the operational conditions and fault situations needed to test the algorithm developed. The results were compared to a commercial relay for validation, showing the advantages of the new method.Department of Electrical Engineering, Engineering School of Sao Carlos, University of Sao Paulo (USP), BrazilFundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES

Artificial neural network model of discharge lamps in the power quality context

This paper presents a methodology for modeling high intensity discharge lamps based on artificial neural networks. The methodology provides a model which is able to represent the device operating in the frequency of distribution systems, facing events related to power quality. With the aid of a data acquisition system to monitor the laboratory experiment, and using $$\text{ MATLAB }^{\textregistered }$$ software, data was obtained for the training of two neural networks. These neural networks, working together, were able to represent with high fidelity the behavior of a discharge lamp. The excellent performance obtained by these models allowed the simulation of a group of lamps in a distribution system with shorter simulation time when compared to mathematical models. This fact justified the application of this family of loads in electric power systems. The representation of the device facing power quality disturbances also proved to be a useful tool for more complex studies in distribution systems. © 2013 Brazilian Society for Automatics - SBA

Power quality analysis applying a hybrid methodology with wavelet transforms and neural networks

A hybrid system to automatically detect, locate and classify disturbances affecting power quality in an electrical power system is presented in this paper. The disturbances characterized are events from an actual power distribution system simulated by the ATP (Alternative Transients Program) software. The hybrid approach introduced consists of two stages. In the first stage, the wavelet transform (WT) is used to detect disturbances in the system and to locate the time of their occurrence. When such an event is flagged, the second stage is triggered and various artificial neural networks (ANNs) are applied to classify the data measured during the disturbance(s). A computational logic using WTs and ANNs together with a graphical user interface (GU) between the algorithm and its end user is then implemented. The results obtained so far are promising and suggest that this approach could lead to a useful application in an actual distribution system. (C) 2009 Elsevier Ltd. All rights reserved.CAPES (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior)CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico)FAPESP (Fundacao de Amparo a Pesquisa do Estado de Sao Paulo