Title :
Power system stabiliser using energy storage
Author :
Tsang, M.W. ; Sutanto, D.
Author_Institution :
Dept. of Electr. Eng., Hong Kong Polytech., Hung Hom, Hong Kong
Abstract :
A fuzzy logic controller (FLC) and an artificial neural network (ANN) controller are designed for a battery energy storage system (BESS) to improve the stability of power systems. Both single-machine-to-infinite-bus and interconnected multi-machine power systems are considered in this study. A detailed model of BESS is used for accurate dynamic assessment. The model takes into account the switching actions of the converter as well as the battery characteristics. Another novel aspect of this paper is the use of hysteresis technique to control directly the BESS output current. This reduces the complexity of the control system while at the same time provides a tight control of the BESS output. Test results under different disturbances and operating conditions show the proposed BESS is effective in damping out power system oscillations
Keywords :
battery storage plants; damping; electric current control; fuzzy control; neurocontrollers; oscillations; power system control; power system stability; artificial neural network; battery energy storage system; converter switching actions; dynamic assessment; fuzzy logic controller; hysteresis technique; interconnected multi-machine power system; output current control; power system oscillations damping; power system stabiliser; power systems stability; single-machine-to-infinite-bus system; Artificial neural networks; Batteries; Control systems; Energy storage; Fuzzy logic; Power system dynamics; Power system interconnection; Power system modeling; Power system stability; Power systems;
Conference_Titel :
Power Engineering Society Winter Meeting, 2000. IEEE
Print_ISBN :
0-7803-5935-6
DOI :
10.1109/PESW.2000.850156
