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Characteristics of Indicators for Insulation Deterioration in 26 kV Generator Stator Windings
Soo-hoh Lee,
Hee-dong Kim,
Tae-sik Kong
Issue:
Volume 8, Issue 6, November 2019
Pages:
145-151
Received:
23 September 2019
Accepted:
16 October 2019
Published:
4 November 2019
Abstract: This study conducted and analyzed the results of non-destructive tests (AC current, dissipation factor, and partial discharge tests) and a destructive test (overvoltage test) on 26 kV-generator stator windings with a ground fault. The target generator was a steam turbine generator in operation for over 30 years, and ground fault in windings occurred because of the rapid and instantaneous temperature rise in the copper conductor owing to the partial loss of generator cooling water. By comparing the non-destructive test data measured during the planned preventive maintenance period two years before the ground fault and the data gathered just after the ground fault, the study conducted an in-depth analysis of the effect of moisture on insulation diagnosis factors. If both the dissipation factor and capacitance data increased when compared to those of previously estimated values at same applied AC voltage level, it represented that the insulation materials absorbed moisture. Moreover, it was further developed that both of the dissipation factor and capacitance surge voltage were detected when the discharge started whereas the concerned surge voltage for AC current was detected when the discharge was proceeded in some extent. It is expected that a wider understanding of insulation diagnosis factors developed from this study will contribute not only to a more reliable diagnosis data analysis but also a stable power supply by preventing accidents in advance.
Abstract: This study conducted and analyzed the results of non-destructive tests (AC current, dissipation factor, and partial discharge tests) and a destructive test (overvoltage test) on 26 kV-generator stator windings with a ground fault. The target generator was a steam turbine generator in operation for over 30 years, and ground fault in windings occurre...
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Thermal Power Plant Steam Turbine Output Operational Characteristics Change Probabilistic Model Driven by the Second Derivation Control Actions
Sultanov Makhsud Mansurovich,
Trukhanov Vladimir Mikhailovich,
Gorban Yuliya Anatolyevna
Issue:
Volume 8, Issue 6, November 2019
Pages:
152-157
Received:
1 August 2019
Accepted:
29 October 2019
Published:
25 November 2019
Abstract: The subject of the research is thermal station power equipment, in particular steam turbines and steam turbine plant support equipment. In the modern context, when working lifespan of the power equipment outreached the limit, thus the goal is to assure it performance and availability for producing enough energy and heat. To reach the goal it’s necessary to design and implement the probabilistic models and techniques for power equipment reliability under present day conditions. The probabilistic second derivative output parameters change model of power equipment is first developed by the authors and is the scientific novelty of the research. In the paper the assumptions and suppostitions on which the model is based are described. The practical implication of the model consists of capability of rational maintenance and repair operation term estimation of thermal power plant steam turbines. The model is based on the mathematical statistics methods, probability theory and matrix calculus. The probabilistic model allows forecasting the output characteristics change in time and control actions explicitly. The example of output characteristics change for long term utilization is given. During the research the statistical power equipment elements failure and error material has been acquired and presented in relative failure and error share diagram. The internal and external technical and operational factors influencing the failure statistics are determined. For quantitive reliability estimation of power equipment the set of primary indices, influencing turbine performance and reliability, is presented.
Abstract: The subject of the research is thermal station power equipment, in particular steam turbines and steam turbine plant support equipment. In the modern context, when working lifespan of the power equipment outreached the limit, thus the goal is to assure it performance and availability for producing enough energy and heat. To reach the goal it’s nece...
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The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System
Arakelian Edik Koyrunovich,
Sultanov Makhsud Mansurovich,
Evseev Kirill Viktorovich
Issue:
Volume 8, Issue 6, November 2019
Pages:
158-164
Received:
1 August 2019
Accepted:
26 November 2019
Published:
24 December 2019
Abstract: The problem of power generating equipment reliability and safety of thermal (TPP), hydro (HPP) and nuclear (NPP) power plants at each its life cycle stage is set and the solution approach is proposed. The blockchain distributed data storage system to unite different members of the energy system is described. It is shown that the suggested technology allows decentralized data storage reliability increase due to the data exists till its last participant leaves and safety is ensured by the electric market participant consensus algorithm. The algorithm for the decentralized blockchain system is developed. The new technique for reliability design calculation based on using both constant and time-varying failure rate is introduced. It is suggested to use control action method expressed as the design, technological and operational parameters from the normative documents. The generalized model of reliability design calculation representing product of three components of failure free operation probability is developed. It is shown that developing new algorithms of statistical data obtaining and designing full repair processes allow planning equipment repair, obtaining and analyzing the corresponding reliability indeces when the equipment is in operation and then choose the most fitting repair time and amount optimization, operation mode selection and power plant long term equipment time in operation forecasting solutions. The technique for the power equipment condition forecasting by archival data stored in the distributed system, the data can be used to predict equipment failures and decide whether it should be repaired. It is shown that the desired prediction accuracy can be achived by using neural network due to its feature to reveal complex relations between input and output values.
Abstract: The problem of power generating equipment reliability and safety of thermal (TPP), hydro (HPP) and nuclear (NPP) power plants at each its life cycle stage is set and the solution approach is proposed. The blockchain distributed data storage system to unite different members of the energy system is described. It is shown that the suggested technolog...
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Color Influence and Genetic Algorithm Optimization in Interior Lighting Building
Merim´e Souffo Tagueu,
Benoˆıt Ndzana
Issue:
Volume 8, Issue 6, November 2019
Pages:
165-175
Received:
28 October 2019
Accepted:
20 November 2019
Published:
30 December 2019
Abstract: The energy consumed by the lighting of the buildings represents a not negligible part of the total energy. The use of low-energy luminaires such as LEDs has significantly reduced this consumption, in addition to the reduction of greenhouse gases and the extended life of the lamps. To satisfy the basic principles of optimal lighting system design (i.e., maximizing uniformity and reducing the level of illumination by staying within the required normative range), many researches using optimization algorithms have been conducted with interesting results. This article proposes a multi-objective optimization model integrating the influence of the colors (in particular primary colors), of the different compartments of a room on the level of total illumination of the piece. The reduction of energy consumption is demonstrated by considering a specific model of illumination in which we introduced the reflection factor related to the colors of the surrounding environment. The subsequent use of genetic algorithms (NSGA III) makes it possible to find the optimal coefficient of variation of the LEDs or any other variable luminaires to have the desired energy value while keeping the same comfort for the users. The proposed model is implemented for the case of an office room. The results show an energy savings of up to 39% with red color. Of particular, results are obtained while maintaining regular illumination and changing the color of the pieces.
Abstract: The energy consumed by the lighting of the buildings represents a not negligible part of the total energy. The use of low-energy luminaires such as LEDs has significantly reduced this consumption, in addition to the reduction of greenhouse gases and the extended life of the lamps. To satisfy the basic principles of optimal lighting system design (i...
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