Optimal Power Flow Using Differential Search Algorithm

被引:43
作者
Bouchekara, Houssem Rafik El-Hana [1 ]
Abido, Mohamed Ali [2 ]
机构
[1] Univ Constantine 1, Dept Elect Engn, LEC, Constantine Elect Engn Lab, Constantine 25000, Algeria
[2] King Fahd Univ Petr & Minerals, Dept Elect Engn, Dhahran 31261, Saudi Arabia
关键词
power system optimization; optimal power flow; voltage profile; metaheuristic; differential search algorithm; voltage stability; BIOGEOGRAPHY-BASED OPTIMIZATION; VOLTAGE STABILITY; EVOLUTION; OPF;
D O I
10.1080/15325008.2014.949912
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
-In this article, a new nature-inspired metaheuristic technique called the differential search algorithm is proposed to solve the optimal power flow problem. The proposed differential search algorithm has been developed and tested under normal and contingency power system conditions. To show the effectiveness of the proposed method, it has been demonstrated on the standard IEEE 30-bus and IEEE 118-bus test systems with different objectives that reflect performance indices of the power system. Obtained results using the proposed technique indicate that the proposed differential search algorithm provides an effective, a robust, and a high-quality solution for the optimal power flow problem. The comparisons of the proposed differential search algorithm results with those reported in the literature reveal the potential and superiority of the proposed algorithm in terms of the optimal solution quality and robustness.
引用
收藏
页码:1683 / 1699
页数:17
相关论文
共 37 条
[1]   Optimal power flow using particle swarm optimization [J].
Abido, MA .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2002, 24 (07) :563-571
[2]   Optimal power flow using tabu search algorithm [J].
Abido, MA .
ELECTRIC POWER COMPONENTS AND SYSTEMS, 2002, 30 (05) :469-483
[3]   Optimal power flow using differential evolution algorithm [J].
Abou El Ela, A. A. ;
Abido, M. A. ;
Spea, S. R. .
ELECTRIC POWER SYSTEMS RESEARCH, 2010, 80 (07) :878-885
[4]   Applications of computational intelligence techniques for solving the revived optimal power flow problem [J].
AlRashidi, M. R. ;
El-Hawary, M. E. .
ELECTRIC POWER SYSTEMS RESEARCH, 2009, 79 (04) :694-702
[5]  
[Anonymous], 1962, B SOC FRAN ELEC
[6]   Solving Optimal Power Flow Problems Using Chaotic Self-adaptive Differential Harmony Search Algorithm [J].
Arul, R. ;
Ravi, G. ;
Velusami, S. .
ELECTRIC POWER COMPONENTS AND SYSTEMS, 2013, 41 (08) :782-805
[7]   Optimal Power Flow Using Adapted Genetic Algorithm with Adjusting Population Size [J].
Attia, Abdel-Fattah ;
Al-Turki, Yusuf A. ;
Abusorrah, Abdullah M. .
ELECTRIC POWER COMPONENTS AND SYSTEMS, 2012, 40 (11) :1285-1299
[8]   Stability Constrained Optimal Power Flow in Deregulated Power Systems [J].
Azadani, E. Nasr ;
Hosseinian, S. H. ;
Divshali, P. Hasanpor ;
Vahidi, B. .
ELECTRIC POWER COMPONENTS AND SYSTEMS, 2011, 39 (08) :713-732
[9]   Optimal power flow by enhanced genetic algorithm [J].
Bakirtzis, AG ;
Biskas, PN ;
Zoumas, CE ;
Petridis, V .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2002, 17 (02) :229-236
[10]  
Belhadj C. A., 1999, PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376), DOI 10.1109/PTC.1999.826510