Open AccessNonlinear T‐S fuzzy stabilizer design for power systems including random loads and static synchronous compensator
Author(s) -
Abolmasoumi Amir Hossein,
Moradi Mohammad
Publication year - 2018
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.2468
Subject(s) - control theory (sociology) , electric power system , nonlinear system , fuzzy logic , stabilizer (aeronautics) , markov chain , power (physics) , computer science , stability (learning theory) , engineering , physics , mechanical engineering , control (management) , quantum mechanics , artificial intelligence , machine learning
Summary The operational conditions of power systems change constantly as a result of load variations. Most conventional power system stabilizers do not tolerate the variations of operational conditions. Also, a power system containing flexible AC transmission system devices like static synchronous compensator (STATCOM) requires more accurate modeling and stabilizing methods. In this paper, the problem of designing a power system stabilizer by Takagi‐Sugeno (T‐S) fuzzy method for power systems including STATCOM and random load changes is investigated. Load variations are modeled as a continuous‐time finite‐state Markovian chain. The suggested T‐S fuzzy stabilizer contains 2 levels: a surface explaining the Markov jump stochastic processes and a fuzzy surface dealing with the nonlinear power system dynamics. The sufficient conditions for the stochastic stability of the power system are expressed as linear matrix inequalities (LMIs), and the stabilizer gains are obtained via solving LMIs. The proposed stabilizer is tested on both single and multiple machine power systems including stochastic load variations and STATCOM. Simulation results show the efficiency of the proposed stabilizer in comparison with the conventional stabilizers.