Title :
Research on architecture of intelligent power grid control centre
Author :
Ma, Taotao ; Zhu, Shaohua ; Zheng, Xiao ; Guo, Chuangxin ; Qian, Weizhong ; Yang, Jian
Author_Institution :
Coll. of Electr. Eng., Zhejiang Univ., Hangzhou, China
Abstract :
As the power grid grows larger; the tradition way which relies on human´s judgment to control over power grid becomes useless especially when the grid is in emergency. This paper brings in a new architecture which makes the control center smarter. This architecture uses real time data from EMS and WAMS to describe the current state of power grid. Upon the current state, different intelligent engines will be triggered. The triggered intelligent engine will tell the operator which is happening, how it happened, and how to do with it. The intelligent engines will be produced by both online modern and off line machine learning. And they form a growing knowledge warehouse makes control centre clever. The control centre becomes smart is an important part of smart grid.
Keywords :
energy management systems; learning (artificial intelligence); power control; power grids; control center; energy management system; knowledge warehouse; machine learning; power grid control; real time data; smart grid; triggered intelligent engine; wide area measuring system; Educational institutions; Electrical engineering; Engines; Intelligent control; Learning systems; Machine learning; Observability; Power grids; Power system dynamics; Power system stability; Machine learning; architecture; human experience; power systems control centre;
Conference_Titel :
Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4934-7
DOI :
10.1109/SUPERGEN.2009.5347910