一个适应的模型预测控制MPPT用于验证在部分遮阳条件下的最佳GMPP跟踪
Muhammad Abu Bakar Siddique1, Dongya Zhao2, Ateeq Ur Rehman3
1College of New Energy, China University of Petroleum (East China), Qingdao, 266580, China.
Scientific reports
|April 24, 2024
概括
本研究引入了一种适应的混合控制算法,以提高光伏 (PV) 系统在部分遮阳条件下 (PSC) 的效率. 该方法有效地跟踪全球最大功率点 (GMPP),改善输出功率并降低成本.
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:
- 部分遮阳条件 (PSCs) 通过导致多个局部最大功率点 (LMPPs) 来显著降低光伏 (PV) 系统效率.
- 准确跟踪全球最大功率点 (GMPP) 对于在不同辐射强度下最大限度地提高光伏系统的能量产量至关重要.
研究的目的:
- 提出一个适应的混合控制算法,用于在部分遮阳下在光伏系统中强大的全球最大功率点跟踪 (GMPPT).
- 通过克服传统跟踪方法的局限性,提高光伏系统的能源生产效率和成本效益.
主要方法:
- 实现一个3x3多串联光伏阵列与修改后的增压转换器.
- 使用适应的扰动和基于观察的模型预测控制 (APO-MPC) 算法用于GMPPT.
- 预测控制策略通过最小化MPC成本函数来稳定输出功率和跟踪GMPP.
主要成果:
- 拟议的APO-MPC算法成功地跟踪GMPP,防止在各种PSC下趋同到局部最大值.
- 该系统以最小的传感器向GMPP展示了准确和稳定的融合,降低了硬件成本.
- 该方法在恒定,变化和线性变化的辐射下,在成本效益和功率提取效率方面优于经典技术.
结论:
- 开发的适应混合控制算法为面临部分遮阳的光伏系统中GMPPT提供了具有成本效益和高效的解决方案.
- 无传感器方法和稳定的跟踪性能突显了拟议方法的实际适用性和优势.
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