Title :
The Hybrid Differential Evolution Algorithm for Optimal Power Flow Based on Simulated Annealing and Tabu Search
Author :
Li, Chunjie ; Zhao, Huiru ; Chen, Tao
Author_Institution :
Inst. of Ind. Econ., North China Electr. Power Univ. (NCEPU), Beijing, China
Abstract :
It is usually imperfect for the traditional algorithm of mathematical programming when it is used to analyze the optimal power flow (OPF) issues. A new optimal power flow model of differential evolutionary algorithm has been developed in this paper through combining modern intelligent optimization algorithms, such as differential evolution (DE), simulated annealing (SA) and tabu search (TS). Concerning IEEE6, IEEE30bus system in the optimal power flow, simulation case study shows that the novel hybrid optimization algorithm has a better global optimization capability.
Keywords :
load flow; mathematical programming; search problems; simulated annealing; IEEE30 bus system; IEEE6 bus system; hybrid differential evolution algorithm; intelligent optimization algorithms; mathematical programming; optimal power flow; simulated annealing; tabu search; Algorithm design and analysis; Floors; Generators; Indexes; Load flow; Simulated annealing;
Conference_Titel :
Management and Service Science (MASS), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5325-2
Electronic_ISBN :
978-1-4244-5326-9
DOI :
10.1109/ICMSS.2010.5578512
