Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/31323
Title: Hybrid algorithm of differential evolution and evolutionary programming for optimal reactive power flow
Authors: Chung, CY
Liang, CH
Wong, KP
Duan, XZ
Issue Date: 2010
Publisher: Institution of Engineering and Technology
Source: IET generation, transmission & distribution, 2010, v. 4, no. 1, igtdaw000004000001000084000001, p. 84-93 How to cite?
Journal: IET generation, transmission & distribution 
Abstract: Differential evolution (DE) is a promising evolutionary algorithm for solving the optimal reactive power flow (ORPF) problem, but it requires relatively large population size to avoid premature convergence, which will increase the computational time. On the other hand, evolutionary programming (EP) has been proved to have good global search ability. Exploiting this complementary feature, a hybrid algorithm of DE and EP, denoted as DEEP, is proposed in this study to reduce the required population size. The hybridisation is designed as a novel primary-auxiliary model to minimise the additional computational cost. The effectiveness of DEEP is verified by the serial simulations on the IEEE 14-, 30-, 57-bus system test cases and the parallel simulations on the IEEE 118-bus system test case.
URI: http://hdl.handle.net/10397/31323
ISSN: 1751-8687
EISSN: 1751-8695
DOI: 10.1049/iet-gtd.2009.0007
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