Open AccessAdaptive non‐linear neural control of wide‐area power systems
Author(s) -
Meng Wenchao,
Wang Xiaoyu,
Fan Bo,
Yang Qinmin,
Kamwa Innocent
Publication year - 2017
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.0299
Subject(s) - control theory (sociology) , computer science , artificial neural network , controller (irrigation) , adaptive control , electric power system , lyapunov function , power (physics) , control engineering , control (management) , nonlinear system , engineering , artificial intelligence , physics , quantum mechanics , agronomy , biology
In this study, the authors propose an adaptive neural network (NN) excitation control for wide‐area power systems. Compared with most existing approaches, the system dynamics is assumed to be totally unknown, which is approximated by a two‐layer NN in an online manner, i.e. no offline training is required. With the help of NN approximation, it is not necessary to pay much attention to system modelling since this modelling is of great difficulty and inaccurate. In addition, the tuning of controller parameters in most existing control designs is avoided as well, which simplifies the controller design. It is proved that all the signals in the closed loop are bound using Lyapunov analysis. Finally, numerical analysis has been conducted on an IEEE 39 Bus power system to verify the effectiveness of the proposed adaptive controller.