使用新的控制策略来提高基于电池存储系统的混合动力系统的有效性和效率
Karima Boutaghane1, Habib Benbouhenni2, Nedjoua Bennecib1
1Department of Electrical Engineering, Laboratory of Electrical Engineering of Constantine (LGEC), Brothers Mentouri University, 25000, Constantine, Algeria.
Scientific reports
|February 8, 2025
概括
本研究介绍了混合能源系统 (HES) 的先进控制策略,以提高功率输出和稳定性. 新的方法显著改善了可再生能源整合的性能指标,如上升时间和稳定状态误差.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 控制系统 控制系统
背景情况:
- 混合能源系统 (HES) 对于满足不断增长的电力需求至关重要.
- 在HES的主要挑战包括能源质量,稳定性和耐用性.
- 集成风能和光伏 (PV) 系统的基于电池的HES需要先进的控制.
研究的目的:
- 开发和评估基于电池的混合能源系统的新型控制策略.
- 为了增强光伏和风力系统的最大功率点跟踪 (MPPT).
- 为了提高电池存储系统的稳定性和性能.
主要方法:
- 实现了基于自适应神经模糊推理系统 (ANFIS) 的MPPT用于光伏和基于神经网络的MPPT用于风力系统.
- 组合分数顺序比例积分 (FOPI) 调节器与集成滑动模式控制 (ISMC) 用于电池存储.
- 使用粒子群集优化 (PSO) 来调整电池系统的控制器收益.
- 在各种操作条件下模拟了MATLAB中的HES.
主要成果:
- 神经MPPT策略在12m/s风速下提高了上升时间99.32%,稳定状态误差提高了60%.
- 在1000W/m2辐射下,ANFIS-MPPT策略提高了最大功率点 (MPP) 18%,并减少了60%的响应时间.
- 与传统方法相比,PSO-FOPI-ISMC战略将当前波扭曲率降低了高达72.90%.
结论:
- 提出的先进控制策略显示了HES的卓越性能和稳定性.
- 这些方法在能源效率,稳定性和电力质量方面提供了显著的改进.
- 开发的方法为混合能源系统的未来工业应用提供了巨大的潜力.
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