SUMMARY

This article presents a new approach for power transformer protection based on a hybrid pattern recognition scheme. The hyperbolic S-transform (HST) is a very powerful tool for analysis of the nonstationary waveforms because it is able to extract the information from transient signals simultaneously in both time and frequency domains. Magnitude, frequency, and HST contours are the main attributes obtained from the output matrix of HST. At first, differential current waveforms of different conditions such as normal, internal and external faults, inrush, and over-excitation conditions are analyzed by HST and some potential useful features are extracted from the abovementioned contours. To decrease the dimension of feature vector and to increase the classification accuracy of the proposed algorithm, the most effective features are selected by using well-known feature selection methods namely sequential forward selection, sequential backward selection, and genetic algorithm. Selected features are trained by a probabilistic neural network as an effective classifier core, which has advantages regarding learning speed and generalization capability compared with feed-forward neural network. The classification accuracy of the proposed algorithm has been used as a criterion function for the selection of the best subset features. The proposed protection scheme is evaluated for various operating conditions of three different transformers using the PSCAD/EMTDC package. Extensive simulation results show that the proposed algorithm relies only on the waveshape properties, and it is independent of the value of transformer parameters and consumed power. Copyright © 2012 John Wiley & Sons, Ltd.

Power transformer protection scheme based on time‐frequency analysis

This paper presents the experimental study of advanced interactive power systems analysis using a-personal scientific computer. The personal scientific computer has new powerful displaying and operating capabilities. Our workstation, called the Advanced Analyzer of Power System (ADAPOS), intends to utilize these capabilities for power systems analysis. In addition our workstation has three features to perform effective human interaction: a supervisory system, database and graphic human interface. The supervisory system controls start and stop of application programs selected from a menu and guides a user to run them successfully according to the rules of analytical procedures. The database facilitates handling of both input and output data of application programs. The graphic human interface is the most important part of our system. Iconic and text menus, instead of a conventional command language, improve operational performance. Graphical presentations of analytical outputs, for example the color animation of power swings, aid understanding of power systems. The experimental results show that the new workstation highly contributes to effective power system analysis, although the computing speed is a little slow for large power systems.

User-Friendly Workstation for Power Systems Analysis

This paper describes the data base approach to power system analysis studies, contrasts it with the traditional stand-alone application approach and discusses the issues which should be considered in developing a data base management system. The discussion is based on the experience gained in developing and implementing a power system data base management system at the Electricity Supply Commission (South Africa). The practical use of a central data base management system, together with a library of application programs and an interactive computing environment contributed significantly to the power system planning process in which individual engineers can work efficiently and interact among themselves using common data and analysis tools.

Data Base Environmennt for Power System Simulation Models

https://iopscience.iop.org/article/10.1088/1757-899X/767/1/012004/pdf

Simulation of differential relay for transformer protection

The key problem that affects the performance of the differential protection for transformers is how to precisely identify the inrush of the transformers. Several types of schemes are currently in use for this purpose, most of which still have inevitable drawbacks. New principles based on various mechanisms are proposed in this section to distinguish between inrush and fault currents. The experimental results validate the proposed method and show that it is superior to conventional blocking schemes.

Novel Magnetizing Inrush Identification Schemes

The Integrated Information System for Power Planning Studies -SIIPEP- is an interactive Data Base that automatically Prepares information for Power System Planning models, reducing manual data handling when updating certain Parameters that are representative of a studs case. Information retrieval from SIIPEP to user application is realized in a simple was by a user interface that avoids modifications to existing models. This interface is supported by SIIPEP functions. This Paper describes the results and experiences of the first stage of its design and Presents the theoretical basis for the second stage.

An Integrated Information System for Power Planning Studies -SIIPEP-

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An Integrated Information System for Power Planning Studies -SIIPEP-