Premium
Identification of power system dynamics due to combined use of mathematical model and neural network
Author(s) -
Takahashi Norio,
Takeno Hiromasa,
Ohsawa Yasuharu
Publication year - 2001
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.1109
Subject(s) - artificial neural network , generator (circuit theory) , electric power system , computer science , terminal (telecommunication) , identification (biology) , voltage , electrical network , power (physics) , mathematical model , system identification , control theory (sociology) , artificial intelligence , engineering , data modeling , mathematics , electrical engineering , control (management) , telecommunications , statistics , physics , botany , quantum mechanics , database , biology
In order to obtain a reliable model of power systems, identification of power system dynamics by employing a neural network is studied. A new method of combined use of a mathematical model and a neural network is proposed. The effectiveness of the proposed method is verified by applying to two kinds of one‐machine infinite‐bus system—an experimental system and a numerical simulation model system. In the conventional method, the neural network learns the generator terminal voltage of the system directly. On one hand, in the new method, the neural network is trained to learn errors between the generator terminal voltage of the system and that produced by the mathematical model. The results of the test show that good performance is obtained for the proposed method. Construction of a more reliable model is demonstrated by combined use of the mathematical model and the neural network. © 2001 Scripta Technica, Electr Eng Jpn, 138(1): 42–48, 2002