A Multitasking Electric Power Dispatch Approach With Multi-Objective Multifactorial Optimization Algorithm

被引:17
|
作者
Liu, Junwei [1 ,2 ]
Li, Peiling [1 ]
Wang, Guibin [1 ]
Zha, Yongxing [1 ]
Peng, Jianchun [1 ]
Xu, Gang [3 ]
机构
[1] Shenzhen Univ, Coll Mechatron & Control Engn, Shenzhen 518060, Peoples R China
[2] Shenzhen Univ, Coll Optoelect Engn, Minist Educ & Guangdong Prov, Key Lab Optoelect Devices & Syst, Shenzhen 518060, Peoples R China
[3] Shenzhen Technol Univ, Coll Urban Transportat & Logist, Shenzhen 518118, Peoples R China
来源
IEEE ACCESS | 2020年 / 8卷
关键词
Electric power dispatch; multifactorial; multitasking; optimization; EVOLUTIONARY ALGORITHMS; ECONOMIC-DISPATCH;
D O I
10.1109/ACCESS.2020.3018484
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Electric power dispatch issue mainly consists of two optimization tasks: active and reactive power dispatches, each of which is a non-linear multi-objective optimization problem with a series of constraints. Traditional evolutionary algorithms are focused on single-task optimization for active or reactive power dispatch and they are not able to deal with several (single- or multi-objective) optimization tasks simultaneously. In this paper, to solve this problem, a multitasking electric power dispatch approach is proposed by introducing the multi-objective multifactorial optimization (MO-MFO) algorithm and integrating it with the characteristics of power system. The approach exhibits the great potential to be developed as a cloud-computing solver or platform for future large-scale smart grid applications involving different market entities because of its implicit parallel computation mechanism. The multitasking approach is thoroughly tested and benchmarked with IEEE-30-bus and IEEE-118-bus standard systems and exhibits generally better performances as compared to previously proposed Pareto heuristic approaches for electric power dispatch.
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页码:155902 / 155911
页数:10
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