改进MOPSO在微电网优化调度中的应用研究

邢毓华, 任甜甜

太阳能学报 ›› 2024, Vol. 45 ›› Issue (6) : 191-200.

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (6) : 191-200. DOI: 10.19912/j.0254-0096.tynxb.2023-0197

改进MOPSO在微电网优化调度中的应用研究

  • 邢毓华, 任甜甜
作者信息 +

APPLICATION RESEARCH OF IMPROVED MOPSO IN MICROGRID OPTIMAL DISPATCH

  • Xing Yuhua, Ren Tiantian
Author information +
文章历史 +

摘要

针对传统多目标粒子群算法(MOPSO)在求解并网模式下微电网优化调度模型时易陷入局部最优等问题,提出线性微分递减权重并引入变异策略改进MOPSO,以增强算法的寻优能力。结合系统功率平衡、各机组出力限制、储能装置等约束条件,以系统运维和污染治理的成本最小为目标,建立包含风力发电机、光伏、柴油发电机、微型燃气轮机和蓄电池的微电网多目标优化调度模型,采用改进前后的MOPSO对所建优化模型进行求解。结果表明该文提出的改进MOPSO有效降低了微电网运行的综合成本,合理优化了微电网的运行效益。

Abstract

In order to solve the problem that the traditional multi-objective particle swarm optimization (MOPSO) is easy to fall into the local optimal solution when solving the optimal scheduling model of microgrid in grid-connected mode, a linear differential decreasing weight is proposed and a mutation strategy is introduced to improve MOPSO to enhance the optimization ability of the algorithm. Combined with the constraints of system power balance, output limitation of each unit, energy storage device, etc., with the goal of minimizing the cost of system operation and maintenance and pollution control, a multi-objective optimal scheduling model of microgrid including wind turbine, photovoltaic, diesel generator, micro gas turbine and storage battery was established, and the improved MOPSO was used to solve the optimized model. The results show that the improved MOPSO proposed in this paper can effectively reduce the comprehensive cost of microgrid operation and reasonably optimize the operation efficiency of microgrid.

关键词

可再生能源 / 微电网 / 粒子群算法 / 多目标优化 / 调度

Key words

renewable energy / microgrid / particle swarm optimization / multi-objective optimization / scheduling

引用本文

导出引用
邢毓华, 任甜甜. 改进MOPSO在微电网优化调度中的应用研究[J]. 太阳能学报. 2024, 45(6): 191-200 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0197
Xing Yuhua, Ren Tiantian. APPLICATION RESEARCH OF IMPROVED MOPSO IN MICROGRID OPTIMAL DISPATCH[J]. Acta Energiae Solaris Sinica. 2024, 45(6): 191-200 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0197
中图分类号: TM73   

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