Economic emission dispatch of power system based on improved bare-bone multi-objective particle swarm optimization algorithm

被引：0

作者：

Shuai M.-H. ^{[1
]}

Xiong G.-J. ^{[1
]}

Hu X. ^{[1
]}

Chen J.-L. ^{[2
]}

机构：

[1] School of Electrical Engineering, Guizhou University, Guiyang

[2] Guizhou Electric Power Grid Dispatching and Control Center, Guiyang

来源：

Kongzhi yu Juece/Control and Decision | 2022年 / 37卷 / 04期

关键词：

Bare-bones particle swarm; Compromise optimal solution; Crowded distance; Distance evaluation; Economic emission dispatch; Multi-objective optimization;

D O I：

10.13195/j.kzyjc.2020.1440

中图分类号：

学科分类号：

摘要：

Aiming at the insufficient population diversity of the particle swarm optimization algorithm and the problem of falling into local optimization easily, this paper proposes a method for economic emission dispatch of power systems based on the improved bare-bones multi-objective particle swarm optimization(IBBMOPSO). The IBBMOPSO adopts a non-linear decreasing strategy of search weight to improve the position update mode of the bare-bones particle swarm and designs different position update strategies for the worst particles in different search stages to balance the algorithm's global search ability and local search ability. The IBBMOPSO selects the global optimal solution according to the particle crowding distance and uses the distance evaluation index to select the compromise optimal solution. Finally, the 6-machine IEEE30-node standard test system is simulated and compared with other algorithms. The results show that the IBBMOPSO is superior to other algorithms in solving the problem of power system economic emission dispatch, and has good feasibility and effectiveness. Copyright ©2022 Control and Decision.

引用

页码：997 / 1004

页数：7

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