TY - JOUR
T1 - Intelligent coordinators for automatic voltage regulator and power system stabiliser in a multi-machine power system
AU - Khezri, Rahmat
AU - Oshnoei, Arman
AU - Yazdani, Amirmehdi
AU - Mahmoudi, Amin
PY - 2020/12/4
Y1 - 2020/12/4
N2 - This study presents the design of intelligent coordinators for the automatic voltage regulator (AVR) and power system stabiliser (PSS) in a multi-machine power system. The intelligent coordinators are designed to update the gains of AVR and PSS in severe disturbances to guarantee the stability of the studied power system. Three potent intelligent coordinators are proposed: (a) fuzzy logic coordinator, (b) artificial neural network coordinator, and (c) brain emotional learning coordinator. Since the intelligent coordinators are based on the knowledge of the experts, desirable scaling factors are considered in the output signals of the coordinators to achieve optimal results. The scaling factors are optimised using a new evolutionary approach known as the sine-cosine algorithm. To evaluate the efficiency of the proposed intelligent approaches, the performances of coordinators are analysed on a two-area four-machine power system. A range of power system signals, such as rotor speed, terminal voltages, acceleration power and rotor angle of generators are demonstrated to approve and compare the performance of the intelligent coordinators. The simulation results indicate that the intelligent coordinators can guarantee the stability of the power system and satisfy performance objectives, such as desired transient and steady-state errors.
AB - This study presents the design of intelligent coordinators for the automatic voltage regulator (AVR) and power system stabiliser (PSS) in a multi-machine power system. The intelligent coordinators are designed to update the gains of AVR and PSS in severe disturbances to guarantee the stability of the studied power system. Three potent intelligent coordinators are proposed: (a) fuzzy logic coordinator, (b) artificial neural network coordinator, and (c) brain emotional learning coordinator. Since the intelligent coordinators are based on the knowledge of the experts, desirable scaling factors are considered in the output signals of the coordinators to achieve optimal results. The scaling factors are optimised using a new evolutionary approach known as the sine-cosine algorithm. To evaluate the efficiency of the proposed intelligent approaches, the performances of coordinators are analysed on a two-area four-machine power system. A range of power system signals, such as rotor speed, terminal voltages, acceleration power and rotor angle of generators are demonstrated to approve and compare the performance of the intelligent coordinators. The simulation results indicate that the intelligent coordinators can guarantee the stability of the power system and satisfy performance objectives, such as desired transient and steady-state errors.
KW - intelligent coordinators
KW - automatic voltage regulator
KW - power system stabiliser
KW - multi-machine power system
KW - aVR
KW - Scaling regimes
UR - http://www.scopus.com/inward/record.url?scp=85095722367&partnerID=8YFLogxK
U2 - 10.1049/iet-gtd.2020.0504
DO - 10.1049/iet-gtd.2020.0504
M3 - Article
AN - SCOPUS:85095722367
SN - 1751-8687
VL - 14
SP - 5480
EP - 5490
JO - IET Generation, Transmission and Distribution
JF - IET Generation, Transmission and Distribution
IS - 23
ER -