Sizing a Hybrid Renewable Energy System by a Coevolutionary Multiobjective Optimization Algorithm

被引:9
作者
Li, Wenhua [1 ]
Zhang, Guo [1 ]
Yang, Xu [1 ]
Tao, Zhang [1 ,2 ]
Xu, Hu [3 ]
机构
[1] Natl Univ Def Technol, Coll Syst Engn, Changsha 410073, Peoples R China
[2] Hunan Key Lab Multienergy Syst Intelligent Interc, Changsha 410073, Peoples R China
[3] State Key Lab Astronaut Dynam, Xian 710043, Peoples R China
基金
中国国家自然科学基金;
关键词
MANY-OBJECTIVE OPTIMIZATION; MODEL; HRES;
D O I
10.1155/2021/8822765
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
Hybrid renewable energy system (HRES) arises regularly in real life. By optimizing the capacity and running status of the microgrid (MG), HRES can decrease the running cost and improve the efficiency. Such an optimization problem is generally a constrained mixed-integer programming problem, which is usually solved by linear programming method. However, as more and more devices are added into MG, the mathematical model of HRES refers to nonlinear, in which the traditional method is incapable to solve. To address this issue, we first proposed the mathematical model of an HRES. Then, a coevolutionary multiobjective optimization algorithm, termed CMOEA-c, is proposed to handle the nonlinear part and the constraints. By considering the constraints and the objective values simultaneously, CMOEA-c can easily jump out of the local optimal solution and obtain satisfactory results. Experimental results show that, compared to other state-of-the-art methods, the proposed algorithm is competitive in solving HRES problems.
引用
收藏
页数:9
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