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1

Distance protection analysis applied for distribution system with distributed generation

Campos J., Sanca H. S., Costa F. B., Souza B. A.

Przegląd Elektrotechniczny

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2018

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R. 94, nr 3

13--17

EN

In power systems, the over-current protection scheme and, optionally with directional function, and distance function are the main protection used, principally, where the power flow is on both sides as in distribution system with distributed generation (DG), for example. However, with the increasing of DG penetration in the distribution system, these protections can not be secure and impacts in the coordination of the protection are caused due to the power flow is on both sides. Therefore, new types of protection as distance protection are candidates to solve the coordination problem in the distribution system with DG. In this paper, is proposed an application of the distance protection in the distribution system with DG, and several cases of faults and the impacts on the distance protection are evaluated in presence of DG. In the simulation and analysis of faults were varied the fault inception angle, fault type, fault resistance, and fault location. The correct and bad trips are analyzed to evaluate the distance relay performance. The distance relay used in the distribution system with DG had good performance in all simulation cases. Besides, the better performance of the distance protection proves which may be used in distribution systems with DG.

PL

W systemach energetycznych zabezpieczenie przed przeciążeniem prądowym (opcjonalnie wraz z funkcją kierunku i odległości) jest główną metoda zabezpieczenia, szczególnie gdy moc może być przekazywana w dwóch kierunkach. W artykule zaproponowano nowy typ zabezpieczenia uwzględniający funkcje odległości. Uwzględniono też możliwość wykrywania błędów i możliwość określania ich położenia.

2

Scalable PP-1 block cipher

Bucholc K., Chmiel K., Grocholewska-Czuryło A., Idzikowska E., Janicka-Lipska I., Stokłosa J.

International Journal of Applied Mathematics and Computer Science

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2010

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Vol. 20, no 2

401-411

EN

A totally involutional, highly scalable PP-1 cipher is proposed, evaluated and discussed. Having very low memory requirements and using only simple and fast arithmetic operations, the cipher is aimed at platforms with limited resources, e.g., smartcards. At the core of the cipher's processing is a carefully designed S-box. The paper discusses in detail all aspects of PP-1 cipher design including S-box construction, permutation and round key scheduling. The quality of the PP-1 cipher is also evaluated with respect to linear cryptanalysis and other attacks. PP-1's concurrent error detection is also discussed. Some processing speed test results are given and compared with those of other ciphers.

3

Przedwyrównawcze wykrywanie błędów grubych w pomiarze środków rzutu dla aerotriangulacji

Ziobro J.

Prace Instytutu Geodezji i Kartografii

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2006

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T. 52, z. 110

89-102

PL

W artykule przedstawiono metodę przedwyrównawczego wykrywania błędów grubych w pomiarze środków rzutu oraz wyniki badań nad skutecznością metody. Metoda opiera się na analizie różnic wyników dwóch niezależnych wyznaczeń: wyniku otrzymanego z wyrównania aerotriangulacji bez uwzględnienia pomiaru środków rzutu i wyniku pomiaru środków rzutu wykonanego podczas nalotu fotogrametrycznego. Metoda została przetestowana na 26 blokach, które opracowano w kraju w ciągu kilku ostatnich lat.

EN

Author presents in the article a method for pre-adjustment detection of gross errors in the measured projection centers. The method is based on analyzing differences of the results of two independent measurements: one obtained from adjustment of aerial triangulation without determining projection center and the second, which considers measurement of projection centers during photogrammetric mission. The technique of measuring projection centers for aerial triangulation with the use of GPS method exists since 1993 and is still improved, as far as precision and reliability is concerned. In standard work real verification of quality of measurement is done only at the stage of adjustment of aerial triangulation. The main aim of adjustment is to obtain the result with the highest probability, and it depends on removing gross errors from calculations. As it can be seen from practice, this condition is difficult to fulfilI; the procedure is time-consuming and not fully efficient. Detection and location of gross errors is difficult due to improper division of GPS measurements into profiles, multiple gross errors, mistakes in GPS measurement, or insufficient reliability level of network. In the proposed method distances between neighboring points of profile are compared, obtained from two independent determinations. In addition, increments of coordinates between neighboring projection centers are also compared. These differences, which prove to be higher than triple mean error, are considered as gross errors. The method has been tested on 26 blocks, which were prepared during last years in Poland. The aim of testing was to verify magnitude and number of gross errors of projection centers, which remain in the network after applying the method. Analysis of non-detected gross errors was done using W. Baarda data snooping method, i.e. the method of standardized residuals. In the test blocks at a, scale of 1 : 13 000 level of detectability of gross errors in the measured projections centers was ca. 6 times mean error of coordinate of projection center, while for 1: 26 000 photographs it was 12 times mean error, respectively. The method enables to detect in one calculation step all mistakes and most of gross errors, which results in decreasing number of adjustment cycles in cases, when many data errors exist.

4

Parameter Estimation Based Fault Detection and Isolation in Wiener and Hammerstein Systems

Janczak A.

International Journal of Applied Mathematics and Computer Science

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1999

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Vol. 9, no 3

711-735

EN

Fault detection and isolation in Wiener and Hammerstein systems via generation and processing of residual sequences is considered. We assume that some models of the unfaulty Wiener and Hammerstein systems under consideration are known. For Wiener systems, we also assume that their static nonlinear subsystems are invertible. Then, based on a serial-parallel definition of the residual error, new fault detection and isolation methods are proposed.To detect and identify all the changes in both the Wiener and Hammerstein system parameters, the sequences of residuals are processed by using linear regression methods or a neural network approach.

5

Neural Network Evaluation of Model-Based Residuals in Fault Detection of Time Delay Systems

Zitek P., Mankova R., Hlava J.

International Journal of Applied Mathematics and Computer Science

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1999

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Vol. 9, no 3

599-617

EN

Model-based fault detection becomes rather questionable if a supervised plant belongs to the class of systems with distributed parameters and significant delays. Two methods of fault detection have been developed for this class of plants, namely a method of functional (anisochronic) state observer and a modified internal model control scheme adopted for that purpose. Both these model schemes are employed to generate residuals, i.e. differences suitable to watch whether a malfunction of the control operation has occurred. Continuous evaluation of residuals is provided by means of a dynamic application of artificial neural networks (ANNs). This evaluation is carried out on the basis of prediction of time series evolution, where the accordance obtained between the prediction and measured outputs is used as a classification criterion. Implementation of both the methods is demonstrated on a laboratory-scale heat transfer set-up, making use of the Real-Time Matlab software.

6

Fuzzy-Logic Fault Diagnosis of Industrial Process Actuators

Kościelny J. M., Syfert M., Bartyś M.

International Journal of Applied Mathematics and Computer Science

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1999

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Vol. 9, no 3

653-666

EN

The paper presents an idea of decomposition of diagnostic tasks in complex systems. Such decomposition consists in splitting basic diagnostic functions into lower-level units existing in decentralised structures of automatic control and supervision of the process. An example of a unit that realises this concept and includes a positioner that controls and diagnoses an assembly consisting of a servomotor and a pneumatic control valve is also given. An application of fuzzy logic to the actuator diagnosing algorithm is presented and results of the corresponding fault detection tests in an industrial environment are discussed.

7

Dynamic Neural Networks for Process Modelling in Fault Detection and Isolation Systems

Korbicz J., Patan K., Obuchowicz A.

International Journal of Applied Mathematics and Computer Science

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1999

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Vol. 9, no 3

519-546

EN

A fault diagnosis scheme for unknown nonlinear dynamic systems with modules of residual generation and residual evaluation is considered. Main emphasis is placed upon designing a bank of neural networks with dynamic neurons that model a system diagnosed at normal and faulty operating points.To improve the quality of neural modelling, two optimization problems are included in the construction of such dynamic networks: searching for an optimal network architecture and the network training algorithm. To find a good solution, the effective well-known cascade-correlation algorithm is adapted here. The residuals generated by a bank of neural models are then evaluated by means of pattern classification. To illustrate the effectiveness of our approach, two applications are presented: a neural model of Narendra's system and a fault detection and identification system for the two-tank process.

8

Development of Dynamic Neural Networks With Application to Observer-Based Fault Detection and Izolation

Marcu T., Mirea L., Frank P. M.

International Journal of Applied Mathematics and Computer Science

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1999

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Vol. 9, no 3

547-570

EN

The paper suggests a neural-network approach to the design of robust fault diagnosis systems. The main emphasis is placed upon the development of neural observer schemes. They are built based on dynamic neural networks, i.e. dynamic multi-layer perceptrons with mixed structure. The goal is to achieve an adequate approximation of process outputs for known classes of the process behaviour. The obtained symptoms are then classified by means of static artificial nets. Appropriate decision mechanisms are designed for each type of observer schemes. An application to a laboratory process is included. It refers to component and instrument fault detection and isolation in a three-tank system.

9

An Expert System Coupled With a Hierarchical Structure of Fuzzy Neural Networks for Fault Diagnosis

Calado J. M. F., Costa I. S.

International Journal of Applied Mathematics and Computer Science

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1999

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Vol. 9, no 3

667-687

EN

An on-line fault diagnosis system, designed to be robust to the normal transient behaviour of the process, is described. The overall system consists of an expert system cascade with a hierarchical structure of fuzzy neural networks, corresponding to a multi-stage fault detection and isolation system. The fault detection is performed through the expert system by means of fault detection heuristic rules, generated from deep and shallow knowledge of the process under consideration. If a fault is detected, the hierarchical structure of fuzzy neural networks starts and it performs the fault isolation task. The structure of this diagnosis system was designed to allow for the diagnosis of single and multiple simultaneous abrupt and incipient faults from only single abrupt fault symptoms. Also, it combines the advantages of both fuzzy reasoning and neural networks learning capacity. A continuous binary distillation column has been used as a test bed of the current approach. Single, double and triple simultaneous abrupt faults, as well as incipient faults, have been considered. The preliminary results obtained show a good accuracy, even in the case of multiple faults.