Title :
ANN based dynamic voltage security asessment for a practical power system
Author :
Shang, Jingfu ; Zhang, Jianhua ; Zhao, Weiwei ; LIU, Jun
Author_Institution :
Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing
Abstract :
The process of determining whether a power system is secure or insecure is specially important under power market conditions. Voltage security is an indispensable aspect of power system security. In recent years, more and more researchers have focused theirs eye on dynamic aspect of voltage stability. In order to overcome the time-consuming deficiency of time domain simulation, this paper develops a new method to assess the dynamic voltage security of a practical power system. This method employs artificial neural network (ANN) to replace time- domain simulation for dynamic voltage security assessment. The trained ANN can output the dynamic voltage stability margin (DVSM), what´s more, both the accuracy and speed are satisfying. The method can meet the need of online applications and can be used to assess the transaction under power market conditions.
Keywords :
neural nets; power markets; power system dynamic stability; ANN; artificial neural network; dynamic voltage security assessment; power market; power system security; time domain simulation; time-consuming deficiency; Power engineering; Power system dynamics; Power system security; Voltage; Artificial Neural Network; Dynamic Voltage Stability; Security Assessment;
Conference_Titel :
Power Engineering Conference, 2007. IPEC 2007. International
Conference_Location :
Singapore
Print_ISBN :
978-981-05-9423-7