Title : 
The research of united optimal operation aid decision system for cascade hydropower plants in local power network
         
        
            Author : 
Zhong Wei ; Song Yang
         
        
            Author_Institution : 
Sch. of Manage., Tianjin Univ. of Technol., Tianjin, China
         
        
        
        
        
        
            Abstract : 
The decision-making support system for optimal operation of cascaded hydropower plants in local electric power network, which includes system structure build up, and module design methods, is studied and designed in order to satisfy the demands of cascade hydropower plants optimal management in local electric power network. The system function include data management, hydrological forecast, long-time optimal operation planning, short-term optimal operation planning, and daily operation scheming. The system can provide decision support for optimal operation of small cascade hydropower plants in local power network. The system is applied in one local power network, and the results show that it is efficient.
         
        
            Keywords : 
hydroelectric power; hydroelectric power stations; power distribution planning; cascade hydropower plants; daily operation scheming; data management; decision-making support system; hydrological forecast; local power network; long-time optimal operation planning; short-term optimal operation planning; united optimal operation aid decision system; Decision making; Economic forecasting; Energy management; Engineering management; Hydroelectric power generation; Power generation economics; Power system management; Power system planning; Rain; Technology management; aid decision system; cascaded hydropower plants; optimal operation; system integration;
         
        
        
        
            Conference_Titel : 
Industrial Engineering and Engineering Management, 2009. IE&EM '09. 16th International Conference on
         
        
            Conference_Location : 
Beijing
         
        
            Print_ISBN : 
978-1-4244-3671-2
         
        
            Electronic_ISBN : 
978-1-4244-3672-9
         
        
        
            DOI : 
10.1109/ICIEEM.2009.5344582