Currently and in the last few years, the subject of integrating FACTS in a power system will have more importance within industrial scientific research. This is mainly due to the liberalization of the electricity sector and the development of power electronics. Very often, the quality of electrical transmission is restricted by constraints of voltage setting and the maximum transmissible power of the lines. These constraints can be overcome by the creation of new lines. However, creating new lines is not always possible for various reasons. The implementation of FACTS devices and more particularly of the BtB STATCOM system constitute an alternative to the creation of new lines. It can lead to the strengthening of the power system and the improvement of the energy quality. It is this solution that we have examined in this work which shows that the BtB STATCOM device improves, in steady state conditions, the performances of a power system such as the reduction of voltage drops and power losses in the electrical transmission lines.
PL
Obecnie iw ostatnich latach temat integracji FACTS w systemie elektroenergetycznym będzie miał coraz większe znaczenie w przemysłowych badaniach naukowych. Wynika to głównie z liberalizacji sektora elektroenergetycznego i rozwoju energoelektroniki. Bardzo często jakość przesyłu energii elektrycznej jest ograniczona ograniczeniami nastawy napięcia i maksymalnej dopuszczalnej mocy linii. Te ograniczenia można przezwyciężyć, tworząc nowe linie. Jednak tworzenie nowych linii nie zawsze jest możliwe z różnych powodów. Wdrożenie urządzeń FACTS, aw szczególności systemu BtB STATCOM, stanowi alternatywę dla tworzenia nowych linii. Może prowadzić do wzmocnienia systemu elektroenergetycznego i poprawy jakości energii. Właśnie to rozwiązanie, które zbadaliśmy w niniejszej pracy, pokazuje, że urządzenie BtB STATCOM poprawia w warunkach stanu ustalonego działanie systemu elektroenergetycznego, takie jak redukcja spadków napięć i strat mocy w liniach elektroenergetycznych.
In the industrial sector, transmission lines are an important part of the electrical grid. Thus it is important to protect it from all the different faults that may occur as soon as possible to supply the electric power continuously. This paper presents a modern solutions and a comparative study of fault detection and identification in electrical transmission lines using artificial neural network (ANN) compare to the fuzzy logic. Faults in transmission line of various types have been created using simulation model. An intelligent monitoring system (IFD: Intelligent Fault Diagnosis) was used at both ends of a 230 kV overhead transmission line, voltage and current measurements exploited as indicator data for this system. Both approaches were found to be robust, accurate and reliable to detect the fault when it occurs, to determine the fault type short circuit or opening of a power line (open circuit), to locate the fault and to determine which phase was faulted.
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This paper provides a model of the human respiratory system by taking into account the fractal structure of the airways and the viscoelastic properties of the tissue. The self-similarity of airway distribution is admitted up to the 24th generation. Due to periodic breathing which results in sinusoidal excitation of the respiratory system, an electrical equivalent model is developed. The periodic current in this electrical network, that preserves the geometry of the human respiratory tree, is equivalent to the oscillatory air-flow. The model is expressed by Navier-Stokes equations under cylindrical symmetry, linked with an equation responsible for the motion of viscoelastic tissue of airway walls. By use of both electro-mechanical analogies, the total impedance of the respiratory system is determined and compared to the measured data in the clinical range of 4-48 Hz, as well as in the low-frequency range of 0.1-5 Hz. We propose also a lumped model of fractional orders, which is able to capture frequency-dependent variations in both clinical as well as in the low-frequency ranges. The models proposed in this paper can be further used to determine the effects of disease on the lung morphology.
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