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Power‐system stabilizing control by SMES using fuzzy techniques and neural networks
Author(s) -
Kawakita Yasuhiro,
Ohsawa Yasuharu,
Arai Kenji
Publication year - 1994
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.4391140202
Subject(s) - control theory (sociology) , fuzzy logic , artificial neural network , fuzzy control system , fault (geology) , superconducting magnetic energy storage , control engineering , electric power system , power (physics) , control (management) , computer science , control system , engineering , artificial intelligence , electromagnetic coil , physics , superconducting magnet , quantum mechanics , seismology , geology , electrical engineering
Abstract It has been clarified that a superconducting magnetic energy storage (SMES) is very effective for power system stabilization. The control methods proposed for power system stabilization by SMES include the pole assignment, the optimum control, and so on, each of which, however, has its drawbacks. The application of fuzzy control is considered to overcome these drawbacks. This paper considers the power system stabilization by fuzzy control of the active and reactive power of SMES. First, the adequate fuzzy control rules of an SMES for the model power system is derived. Then, to alleviate the dependence of the fuzzy control on the operating condition and the fault, a method is proposed which adjusts the fuzzy parameter according to the operating condition and the fault using a neural network. The validity of the proposed method is examined by computer simulations.