全球MPPT的性能验证,用于通过光伏系统在复杂的部分遮阳效应下高效地提取电力.
Muhammad Abu Bakar Siddique1, Dongya Zhao2, Khmaies Ouahada3
1College of New Energy, China University of Petroleum (East China), Qingdao, 266580, China.
Scientific reports
|May 16, 2025
概括
本研究引入了一种适应的基于扰动和观测的模型预测控制 (APO-MPC) 用于光伏最大功率点跟踪. APO-MPC算法在复杂的部分遮阳条件下有效地跟踪全球最大功率点 (GMPP).
科学领域:
- 可再生能源系统可再生能源系统
- 电气工程 电气工程
- 控制系统 控制系统
背景情况:
- 光伏 (PV) 能源对于可持续发展至关重要.
- 传统的最大功率点跟踪 (MPPT) 算法与部分遮阳作斗争,导致功率损失.
- 现有的方法通常被困在局部最大功率点 (LMPPs) 中,在非均的辐射下.
研究的目的:
- 开发和评估一个先进的MPPT算法,用于增强光伏能源提取.
- 在部分阴影条件下解决传统MPPT算法的局限性.
- 确保在复杂情景下稳定有效地跟踪全球最大功率点 (GMPP).
主要方法:
- 开发一个适应的扰动和观察基于模型预测控制 (APO-MPC) 算法.
- 在 MATLAB/Simulink 中进行模拟,包括六个串联的光伏模块和一个增压转换器.
- 在统一,简单部分和复杂部分阴影条件下 (UIC,SPSC,CPSC) 与其他MPPT算法进行比较分析.
- 使用实时硬件实现和季节性现场数据进行验证.
主要成果:
- 与其他MPPT方法相比,APO-MPC算法显示出更高的性能.
- 在GMPP跟踪期间没有实现任何振荡.
- 平均收时间为0.17秒.
- 在复杂的部分遮阳条件下达到99.46%的高追踪效率.
结论:
- APO-MPC方法提供了快速,准确和稳定的GMPP跟踪.
- 它有效地避免陷入LMPP,即使在复杂的部分遮阳条件下.
- 这种先进的MPPT策略显著提高了光伏能源产量和系统可靠性.
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