Title :
Decision-making in an energy system: a knowledge-based solution
Author :
Boukerche, Kaddour ; Lounis, Hakim
Author_Institution :
Dept. of Comput. Sci., Univ. de Sherbrooke, Que., Canada
Abstract :
The present work is about a solution implementing a decision-making system in the management of production of a hydroelectric network. An object-oriented rule-based architecture is proposed to ensure an intelligent and automatic management of the knowledge in use in this daily decisional process. An alternate planner-based solution is also discussed. On the other hand and for improving the forecast of natural contributions flow, we described how we exploit machine-learning techniques, including artificial neural networks.
Keywords :
hydroelectric power; knowledge based systems; knowledge management; learning (artificial intelligence); neural nets; object-oriented methods; power engineering computing; power system management; power system planning; artificial neural networks; decision-making; energy system; hydroelectric network; intelligent management; knowledge management; knowledge-based system; machine learning; object-oriented rule-based architecture; production management; Computer network management; Computer science; Decision making; Hydrologic measurements; Knowledge based systems; Object oriented modeling; Power generation; Process planning; Production systems; Weather forecasting;
Conference_Titel :
Systems Engineering, 2005. ICSEng 2005. 18th International Conference on
Print_ISBN :
0-7695-2359-5
DOI :
10.1109/ICSENG.2005.33
