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Shenzhen, China

Xiao X.,Tsinghua University | Xu Q.,CYG SUNRI CO. | Wang Y.,Power Economic Research Institute of Jiangxi Power Company | Shi Y.,Tsinghua University
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | Year: 2014

On account of the reverse salient pole characteristic and defects of the traditional parameter identification method, this article puts forward a parameter identification method based on genetic algorithms combine with the mathematical model of the motor. This method can identify the four parameters in same time such as the stator resistance, the d-axis inductance, the q-axis inductance and the permanent magnet flux. The signal used in the method are all can be directly detected the state variables so it can reduce the influence of the other disturbance on the motor parameters identification and improve the accuracy of the parameter identification. Simulation and experimental results show that the genetic algorithm to identify the parameters has a strong robustness and convergence. Four pending identification parameters can converge to the true value in a relatively short time and has a high accuracy no matter in the different speeds, loads and control strategies. It also overcomes the drawback of high requirements in the initial parameter values which in the commen genetic algorithm to identify. Source


Meng J.-T.,CAS Shenzhen Institutes of Advanced Technology | Meng J.-T.,CAS Institute of Computing Technology | Meng J.-T.,University of Chinese Academy of Sciences | Yuan J.-R.,CYG SUNRI CO. | And 2 more authors.
Journal of Computer Science and Technology | Year: 2013

In wireless sensor networks, a clustering scheme is helpful in reducing the energy consumption by aggregating data at intermediate sensors. This paper discusses the important issue of energy optimization in hierarchically-clustered wireless sensor networks to minimize the total energy consumption required to collect data. We propose a comprehensive energy consumption model for multi-tier clustered sensor networks, in which all the energy consumptions not only in the phase of data transmissions but also in the phase of cluster head rotations are taken into account. By using this new model, we are able to obtain the solutions of optimal tier number and the resulted optimal clustering scheme on how to group all the sensors into tiers by the suggested numerical method. This then enables us to propose an energy-efficiency optimized distributed multi-tier clustering algorithm for wireless sensor networks. This algorithm is theoretically analyzed in terms of time complexity. Simulation results are provided to show that, the theoretically calculated energy consumption by the new model matches very well with the simulation results, and the energy consumption is indeed minimized at the optimal number of tiers in the multi-tier clustered wireless sensor networks. © 2013 Springer Science+Business Media New York & Science Press, China. Source


Xi X.,Tsinghua University | Qingsong X.,CYG SUNRI CO. | Peigen T.,Tsinghua University
2013 15th European Conference on Power Electronics and Applications, EPE 2013 | Year: 2013

On account of the reverse salient pole characteristic and defects of the traditional parameter identification method, this article put forward a parameter identification method based on particle swarm optimization(PSO) combine with the mathematical model of the motor. And even made an improvement of PSO. The improvement of PSO can identify the four parameters in same time such as the stator resistance, the d-axis inductance, the q-axis inductance and the permanent magnet flux. The signal used in the method are all can be directly detected the state variables so it can reduce the influence of the other disturbance on the motor parameters identification and improve the accuracy of the parameter identification. Simulation and experimental results shows that the PSO to identify the parameters has a strong robustness and convergence. Four pending identification parameters can converge to the true value in a relatively short time and has a high accuracy no matter in the different speed, load and control strategy. It also overcomes the drawback of high requirements in the initial parameter values which in the basic PSO to identify and the improvement of PSO is better. © 2013 IEEE. Source


Peng X.,CYG SUNRI CO. | Jiang H.,CYG SUNRI CO. | Li Q.,CYG SUNRI CO. | Zhang D.-N.,China Power Engineering Consulting Group Corporation
POWERCON 2014 - 2014 International Conference on Power System Technology: Towards Green, Efficient and Smart Power System, Proceedings | Year: 2014

In 2011, the American Institute of Electrical and Electronics Engineers (IEEE) published the standard of synchronized phasor measurement in power system. In the first part, which is named IEEE Std C37.118.1™-2011, put forward the algorithm reference model BSEM-(Basic Synchrophasor Estimation Model) and each performance index of various testing environments. This paper analyzed the requirements of measurement accuracy and response time of the test case like low frequency oscillation, out-of-band frequency proposed in the criterion, put forward the effect of phase oscillation to the measurement algorithm and the restriction on parameters of digital low-pass filter design when the send rate is 25Hz. According to the corresponding measurement error and computational overhead from the simulation results, it provides guidance for practical research of PMU-(Phasor Measurement Unit). © 2014 IEEE. Source


Wu W.,CYG SUNRI CO. | Zhan J.,CYG SUNRI CO.
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2015

Flying spot results in a lot of protection malfunctions. Few researches are focusing on the flying spot. In practice, most abnormal samples detection algorithms are with ambiguous pertinence, insensitivity, ambiguous threshold and easy wrong ruling. Some detection algorithms only carry out simple latch-up protection, which decrease the malfunction rate while delay the protection action time. To solve these difficulties, a new sampling flying spot algorithm is proposed, which is based on removable discontinuous spot in continuous function. At the same time, a remedy algorithm based on predicting sine curve is proposed. The proposed algorithm can detect the flying spot effectively, and the remedy sampling algorithm can correct the flying spot without latch-up protection. The proposed algorithms can remove the malfunctions for flying spot. The simulation results show the proposed algorithms are effective. ©, 2015, Power System Protection and Control Press. All right reserved. Source

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