Design and Simulation Study of Neural Adaptive Power System Stabilizer of DFIG

Authors

Yuguang Niu, 1. State Key Laboratory for Alternate Electric Power System with Renewable Energy Source, North China Electric Power University,Beijing 102206, China; ;
Yang Wei, 2. School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; ;3. North China Power Engineering CO. LTD., China Power Consulting Group, Beijing 100120, China;
Xiaoming Li, 2. School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; ;
Shilin Wang, 2. School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; ;
Zhongwei Lin, 1. State Key Laboratory for Alternate Electric Power System with Renewable Energy Source, North China Electric Power University,Beijing 102206, China; ;

Abstract

Abstract: A Flux Magnitude Angle Control (FMAC) strategy based Neural Adaptive Power System Stabilizer (NPSS) was designed to improve the transient stability of grid-connected Double Fed Induction Generators (DFIGs). An online training algorithm based Elman artificial neural network was adopted to achieve adaptive control. For releasing computing burden and improving computing speed, a simplified method was used, where the calculation of jacobian matrix was replaced by the sign of itself. A simplified and generic renewable power system demonstrates the control performance contributions. The results of both dominant eigenvalue analysis and time response simulation illustrate contributions to system damping that the NPSS can make. Performance capabilities superior to those provided by Synchronous Generation (SG) with Automatic Voltage Regulator (AVR) and PSS control demonstrate that NPSS installed DFIG has better performances of system damping, voltage regulation and transient stability.

Recommended Citation

Niu, Yuguang; Wei, Yang; Li, Xiaoming; Wang, Shilin; and Lin, Zhongwei (2020) "Design and Simulation Study of Neural Adaptive Power System Stabilizer of DFIG," Journal of System Simulation: Vol. 29: Iss. 1, Article 22.
DOI: 10.16182/j.issn1004731x.joss.201701022
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss1/22

First Page

162

Revised Date

2015-09-17

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201701022

Last Page

169

CLC

TP13

Recommended Citation

Niu Yuguang, Yang Wei, Li Xiaoming, Wang Shilin, Lin Zhongwei. Design and Simulation Study of Neural Adaptive Power System Stabilizer of DFIG[J]. Journal of System Simulation, 2017, 29(1): 162-169.

DOI

10.16182/j.issn1004731x.joss.201701022