TY - GEN
T1 - Multiobjective optimization scheduling based on fuzzy genetic algorithm in cascaded hydroelectric stations
AU - Hu, Guoqiang
AU - He, Renmu
AU - Ma, Rui
AU - Wang, Peng
AU - Yang, Huachun
PY - 2005
Y1 - 2005
N2 - The multi-objective fuzzy optimal method based on the fuzzified optimal solutions of single objectives need not list all non-inferior solution sets, which can optimize directly objectives in value area of variables. This method can reflect the interrelation between individual objective optimal solutions and multi-objective optimal solution. On the basis of fundamental principle of multi-objective fuzzy optimization and genetic algorithm, combing with the concept of objective relative subject degree, this paper presents a multi-objective optimization approach for the hydroelectric power system with contradictory objectives. The proposal method considers the satisfied degree of various characters and contradictory objectives and seeks an appropriate optimized solution to make each objective optimal as possible considering each objective comprehensively. The simulation results of example show that the fuzzy genetic algorithm is an effective method for multi-objective optimization problem in the cascaded hydroelectric plants.
AB - The multi-objective fuzzy optimal method based on the fuzzified optimal solutions of single objectives need not list all non-inferior solution sets, which can optimize directly objectives in value area of variables. This method can reflect the interrelation between individual objective optimal solutions and multi-objective optimal solution. On the basis of fundamental principle of multi-objective fuzzy optimization and genetic algorithm, combing with the concept of objective relative subject degree, this paper presents a multi-objective optimization approach for the hydroelectric power system with contradictory objectives. The proposal method considers the satisfied degree of various characters and contradictory objectives and seeks an appropriate optimized solution to make each objective optimal as possible considering each objective comprehensively. The simulation results of example show that the fuzzy genetic algorithm is an effective method for multi-objective optimization problem in the cascaded hydroelectric plants.
KW - Cascaded hydroelectric plant
KW - Fuzzy
KW - Genetic algorithm
KW - Multi-objective optimization
UR - http://www.scopus.com/inward/record.url?scp=33751383091&partnerID=8YFLogxK
U2 - 10.1109/TDC.2005.1547075
DO - 10.1109/TDC.2005.1547075
M3 - Conference contribution
AN - SCOPUS:33751383091
SN - 0780391144
SN - 9780780391147
T3 - Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference
SP - 1
EP - 4
BT - Proceedings - 2005 IEEE/PES Transmission and DistributionConference and Exhibition - Asia and Pacific
T2 - 2005 IEEE/PES Transmission and DistributionConference and Exhibition - Asia and Pacific
Y2 - 15 August 2005 through 18 August 2005
ER -