Title :
Monitoring and control strategy of power system stability based on the restoration characteristics index
Author :
Tamura, Y. ; Huang, Y. ; Tsukao, S.
Author_Institution :
Dept. of Electr. Eng., Waseda Univ., Tokyo, Japan
Abstract :
The authors discuss a knowledge base for power system stability in an AI/expert system environment. With the knowledge on parametric resonance, a power system is interpreted as a restoration characterized system, in which the ´jump phenomena´ could occur due to the ill-combination of the system parameters. A stability index, called the restoration characteristics index (RCI), is derived by considering the specific combination of parameters to make the resonance curve triple-valued. And considerations on the monitoring and control strategy for AI/expert system approach are discussed.
Keywords :
computerised monitoring; expert systems; power system computer control; power system restoration; power system stability; AI; control strategy; expert system; jump phenomena; knowledge base; monitoring; parametric resonance; power system stability; restoration characteristics index; restoration characterized system; stability index; Artificial intelligence; Control systems; Expert systems; Frequency; Monitoring; Nonlinear equations; Power system control; Power system restoration; Power system stability; Resonance;
Conference_Titel :
Neural Networks to Power Systems, 1993. ANNPS '93., Proceedings of the Second International Forum on Applications of
Conference_Location :
Yokohama, Japan
Print_ISBN :
0-7803-1217-1
DOI :
10.1109/ANN.1993.264339