《无线互联科技》杂志社 ›› 2025, Vol. 22 ›› Issue (1): 24-27.

• 智能控制 • 上一篇    下一篇

基于改进粒子群算法的太阳能光伏发电逐日自动控制

姚鹏飞, 陈蒙娜   

  1. 郑州西亚斯学院 电信与智能制造学院,河南 郑州 451100
  • 出版日期:2025-01-10 发布日期:2025-03-21
  • 作者简介:姚鹏飞(1991— ),男,助教,硕士;研究方向:能源管理自动化。

Daily automatic control of solar photovoltaic power generation based on improved particle swarm algorithm

YAO Pengfei, CHEN Mengna   

  1. College of Telecommunications and Intelligent Manufacturing,Sias University, Zhengzhou 451100, China
  • Online:2025-01-10 Published:2025-03-21

摘要: 常规的太阳能光伏发电逐日自动控制监测节点部署多为单节点局部覆盖模式,导致得出的功率损耗比增加。为此,文章提出基于改进粒子群算法的太阳能光伏发电逐日自动控制方法。该方法采用多点位监测,采集实时监测数据,进行太阳跟踪轨迹与角度计算,构建光伏发电改进粒子群测算逐日自动控制模型,采用全局最优对比和反馈调整的方式实现自动控制。结果表明,应用文章方法得出的功率损耗比相对较小,控制效率明显提升。

关键词: 改进粒子群算法, 太阳能, 光伏发电, 逐日测算, 电能调度

Abstract: The conventional daily automatic control monitoring node deployment of solar photovoltaic power generation is mostly single-node local coverage mode, resulting in an increased power loss ratio. Therefore, an automatic daily control method for solar photovoltaic power generation based on improved particle swarm optimization is proposed. In this paper, multi-point monitoring is adopted, real-time monitoring data is collected, solar tracking trajectory and Angle are calculated, and a daily automatic control model for improved particle swarm calculation of photovoltaic power generation is constructed. The global optimal comparison and feedback adjustment are adopted to achieve automatic control. The results show that the power loss ratio obtained by this method is relatively small, and the control efficiency is obviously improved.

Key words: improved particle swarm algorithm, solar energy, photovoltaic power generation, daily measurement, power dispatching

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