Multi-objective optimization in the presence of practical constraints using non-dominated sorting hybrid cuckoo search algorithm

被引:49
作者
Balasubbareddy, M. [1 ]
Sivanagaraju, S. [2 ]
Suresh, Chintalapudi V. [2 ]
机构
[1] Prakasam Engn Coll, Dept Elect & Elect Engn, Kandukur 523105, Andhra Prades, India
[2] JNTUK, Univ Coll Engn, Dept Elect & Elect Engn, Kakinada, Andhra Prades, India
来源
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH | 2015年 / 18卷 / 04期
关键词
Hybrid cuckoo search algorithm; Non-dominated sorting; Multi-objective optimization; Generation fuel cost; Emission; Total power loss; Practical constraints;
D O I
10.1016/j.jestch.2015.04.005
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A novel optimization algorithm is proposed to solve single and multi-objective optimization problems with generation fuel cost, emission, and total power losses as objectives. The proposed method is a hybridization of the conventional cuckoo search algorithm and arithmetic crossover operations. Thus, the non-linear, non-convex objective function can be solved under practical constraints. The effectiveness of the proposed algorithm is analyzed for various cases to illustrate the effect of practical constraints on the objectives' optimization. Two and three objective multi-objective optimization problems are formulated and solved using the proposed non-dominated sorting-based hybrid cuckoo search algorithm. The effectiveness of the proposed method in confining the Pareto front solutions in the solution region is analyzed. The results for single and multi-objective optimization problems are physically interpreted on standard test functions as well as the IEEE-30 bus test system with supporting numerical and graphical results and also validated against existing methods. (C) 2015 Karabuk University. Production and hosting by Elsevier B.V.
引用
收藏
页码:603 / 615
页数:13
相关论文
共 64 条
[1]  
Abarghooee R. A., 2011, 2011 IEEE Power Engineering and Automation Conference (PEAM 2011), P158, DOI 10.1109/PEAM.2011.6134825
[2]   Multi-Objective Optimal Power Flow Using Differential Evolution [J].
Abido, M. A. ;
Al-Ali, N. A. .
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2012, 37 (04) :991-1005
[3]   Environmental/economic power dispatch using multiobjective evolutionary algorithms [J].
Abido, MA .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2003, 18 (04) :1529-1537
[4]   A novel multiobjective evolutionary algorithm or environmental/economic power dispatch [J].
Abido, MA .
ELECTRIC POWER SYSTEMS RESEARCH, 2003, 65 (01) :71-81
[5]   Optimal power flow using tabu search algorithm [J].
Abido, MA .
ELECTRIC POWER COMPONENTS AND SYSTEMS, 2002, 30 (05) :469-483
[6]   A niched Pareto genetic algorithm for multiobjective environmental/economic dispatch [J].
Abido, MA .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2003, 25 (02) :97-105
[7]   An improved cuckoo search algorithm for power economic load dispatch [J].
Afzalan, Ehsan ;
Joorabian, Mahmood .
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2015, 25 (06) :958-975
[8]   Non-convex economic dispatch with heuristic load patterns, valve point loading effect, prohibited operating zones, ramp-rate limits and spinning reserve constraints using harmony search algorithm [J].
Arul, R. ;
Ravi, G. ;
Velusami, S. .
ELECTRICAL ENGINEERING, 2013, 95 (01) :53-61
[9]   Coordination of combined heat and power-thermal-wind-photovoltaic units in economic load dispatch using chance-constrained and jointly distributed random variables methods [J].
Azizipanah-Abarghooee, Rasoul ;
Niknam, Taher ;
Bina, Mohammad Amin ;
Zare, Mohsen .
ENERGY, 2015, 79 :50-67
[10]  
Azizipanah-Abarghooee R, 2012, WD SCI P COMP ENG, V7, P388