Online Assessment for Transient Stability Based on Response Time Series of Wide-area Measurement System

被引：0

作者：

Huang D. ^{[1
]}

Chen S. ^{[1
,2
]}

Zhang Y. ^{[2
]}

机构：

[1] School of Electrical Engineering, Beijing Jiaotong University, Haidian District, Beijing

[2] China Electric Power Research Institute, Haidian District, Beijing

来源：

Dianwang Jishu/Power System Technology | 2019年 / 43卷 / 03期

关键词：

Angular velocity deviation; Largest Lyapunov exponent index (LLEI); Response time series; Transient stability; Wide area measurement system(WAMS);

D O I：

10.13335/j.1000-3673.pst.2018.0960

中图分类号：

学科分类号：

摘要：

Based on real-time wide area measurement information, a detection method for power system transient rotor angle stability, combining the largest Lyapunov exponent index (LLEI) of response time series of rotor angel and angular velocity, is proposed. Based on model-free LLEI calculation method, a mathematical equation for LLEI and angular velocity deviation is established. Using stability dynamical characteristics of phase trajectories, a transient rotor angle stability criterion based on LLEI and angular velocity is proposed. The proposed stability criterion does not need predefined optimal time window and long-time LLEI data to identify LLEI final sign and can give exact stability assessment time. To reduce computational cost and calculation time, an online detection scheme for transient stability of multi-machine power system based on critical generator pairs is proposed. Simulation results of IEEE 39-bus system verify accuracy and rapidity of the proposed method. For the algorithm calculating LLEI, only a small amount of measured data from WAMS is needed, and the algorithm is simple and easy with low computation cost. This method can realize online detection, showing excellent application prospects. © 2019, Power System Technology Press. All right reserved.

引用

页码：1016 / 1025

页数：9

共 22 条

[1]

Wu W., Tang Y., Sun H., Et al., A survey on research of power system transient stability based on wide-area measurement information, Power System Technology, 36, 9, pp. 81-87, (2012)

[2]

Chen Q., Zhang F., Zhang R., Communication technology for wind power and hydropower coordinated operation control, Power Generation Technology, 39, 1, pp. 53-57, (2018)

[3]

Zhou B., Chen Q., Yang D., On the power system large-scale blackout in Brazil, Power Generation Technology, 39, 2, pp. 97-105, (2018)

[4]

Qiu J., Zhou X., Yu H., Et al., A methodology for generator dominant parameter identification based on dynamic characteristics of power grid, Proceedings of the CSEE, 36, 14, pp. 3699-3706, (2016)

[5]

Nie X., Zhan Q., Duan G., Et al., A new type interconnection scheme and key technology for WAMS dynamic data of trans-dispatching center, Power System Technology, 38, 10, pp. 2839-2844, (2014)

[6]

Gu Z., Tang Y., Sun H., Et al., An identification method for power system transient angle stability based on the trend of rotor speed difference-rotor angle difference, Proceedings of the CSEE, 33, 31, pp. 65-72, (2013)

[7]

Zhang B., Yang S., Wang H., Et al., Closed-loop control of power system transient stability(2): transient instability detection method of multi-machine power system, Electric Power Automation Equipment, 34, 9, pp. 1-6, (2014)

[8]

Cen B., Tang F., Liao Q., Et al., Transient stability detection using phase trajectory obtained by dimension reduction transform of power angles, Proceedings of the CSEE, 35, 11, pp. 2726-2734, (2015)

[9]

Dai Y., Chen L., Zhang W., Et al., Support vector machine ensemble classifier and its confidence evaluation for transient stability prediction of power systems, Proceedings of the CSEE, 36, 5, pp. 1173-1180, (2016)

[10]

Zhou Y., Wu J., Yu Z., Et al., Electric power system transient stability on-line prediction based on least squares support vector machine, Power System Technology, 41, 4, pp. 1188-1196, (2017)

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