Open AccessSelf-adaptive improved PSO algorithm to solve optimal operation of cascade reservoir systems
Author(s) -
Yue Xiang,
Lianguang Mo
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/344/1/012110
Subject(s) - cascade , particle swarm optimization , mathematical optimization , computer science , nonlinear system , scheduling (production processes) , algorithm , mathematics , engineering , chemical engineering , physics , quantum mechanics
The optimal scheduling problem of cascade reservoirs is an optimal control problem for a dynamic complex nonlinear system with a large number of constraints, which has not been satisfactorily solved so far. This paper presents a new improved particle swarm optimization (PSO) algorithm, which based on self-adaptive improvement of relative progress, to solve the problem of optimal scheduling of cascade reservoirs. The results obtained by the improved PSO algorithm are found to be encouraging when compared with PSO algorithm under similar test condition.