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Li L.,Huazhong University of Science and Technology | Zhang D.,Dongguan Power Supply Bureau | Xie L.,Huazhong University of Science and Technology | Yu B.,Huazhong University of Science and Technology | Lin F.,Huazhong University of Science and Technology
Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering | Year: 2013

Condition assessment for power transformer requires not only integrating the known artificial intelligence technologies, but also processing the interrelation of the tested status parameters. According to the association rule of information data and the variable weight synthesizing theory of factor spaces, a condition assessment method of power transformer was proposed in this paper. Via analyzing the interrelation of the independent status parameters and transformer fault types, the set of synthetic status parameters can be built up. Association rule theory was used to calculate the constant weight coefficients of the independent status parameters. The variable weight synthesizing was used for the variable weight coefficients of the synthetic status parameters. Then, combining with the existing maintenance procedures, a preferable condition assessing system of power transformer was proposed. Operational example proved the condition assessing system may reflect the real running condition of power transformer. © 2013 Chin. Soc. for Elec. Eng. Source


Xiaoping J.,Dongguan Power Supply Bureau
2013 5th International Conference on Power Electronics Systems and Applications, PESA 2013 | Year: 2013

For the industry development of electric vehicles, apart from concerns on the development of electric vehicles, we also need to consider the issue of the construction of charging facilities. Firstly, this paper describes the importance of AC charging piles for electric vehicle development. And then, the structure and the problems of the current AC charging pile are discussed. After that, a new charging system for electric vehicles is given and its structure, functional block diagram, charging payment process and system reliability are discussed in detail. By studying existing AC charging piles on the market, the paper presents a smart, low-cost AC charging system to reduce the cost investigated by power grid companies and operational bodies when constructing a large number of AC charging piles. Compared with the conventional one, the proposed system has prominent features of low cost, small footprint and low investment. © 2013 IEEE. Source


Li Y.,Hunan Institute of Engineering | Huang S.,Hunan Institute of Engineering | Xu Z.,Hunan Institute of Engineering | Zhang Y.,Dongguan Power Supply Bureau
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2010

The unbalanced current caused by the asymmetry of un-transposed transmission lines increases the loss of the transmission components of a power grid. Moreover, the negative sequence current may lead to cascading tripping of a number of generators as well. Based on the individual phase modeling of 220 kV un-transposed transmission lines, a simplified model of un-transposed transmission lines is proposed. It can be used for unbalanced current research, and its applicability is proven by theoretical calculation and simulation studies using EMTDC. Based on the asymmetry of mutual inductance matrix of transmission lines, the analytical relation between mutual inductance matrix and sequence currents can be derived. Furthermore, the possibilities of reducing the negative sequence current by adjusting the elements of mutual inductance matrix are studied as well. The results from calculation and simulation show that the proposed method can effectively restrain the negative sequence voltage and current caused by unbalanced parameters of transmission lines. © 2010 State Grid Electric Power Research Institute Press. Source


Bai J.,Nanjing Southeast University | Gu W.,Nanjing Southeast University | Yuan X.,Jiangsu Electric Power Company | Li Q.,Jiangsu Electric Power Company | And 2 more authors.
Energies | Year: 2015

Wind farms can affect the power quality (PQ) of the power supply grid, with subsequent impacts on the safe and stable operation of other electrical equipment. A novel PQ prediction, early warning, and control approach for the common coupling points between wind farms and the network is proposed in this paper. We then quantify PQ problems and provide rational support measures. To obtain predicted PQ data, we first establish a trend analysis model. The model incorporates a distance-based cluster analysis, probability distribution analysis based on polynomial fitting, pattern matching based on similarity, and Monte Carlo random sampling. A data mining algorithm then uses the PQ early warning flow to analyze limit-exceeding and abnormal data, quantify their severity, and output early warning prompts. Finally, PQ decision support is applied to inform both the power suppliers and users of anomalous changes in PQ, and advise on corresponding countermeasures to reduce relevant losses. Case studies show that the proposed approach is effective and feasible, and it has now been applied to an actual PQ monitoring platform. © 2015 by the authors. Source


Xiaoping J.,Dongguan Power Supply Bureau
2013 5th International Conference on Power Electronics Systems and Applications, PESA 2013 | Year: 2013

Electric vehicles are becoming more and more popular in the world. In China, many companies have begun to invest in charging facilities. Firstly, the current AC charging system is discussed and according to its existing problems, a new charging structure is proposed, which is different from that of the current charging pile. And then a charging system based on the new structure is designed. This type of charging system is used to reduce significantly investment cost and maintenance cost. Finally, the new charging system with orderly charging control is discussed, and the orderly charging control is based on the load of power grid, state of charge of battery and user's requirements. It is the future trend for the charging system for electric vehicles © 2013 IEEE. Source

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