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Photovoltaic tilt optimization using physics-informed machine learning methods
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DOI：10.1016/j.epsr.2026.114281.png)
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摘要
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• 刘-乔丹物理基准在安塔利亚（土耳其）给出了34.75°的年度最佳倾角。
• 倾角增强数据集（0–60°，步长0.25°）能够学习倾角-产量响应面。
• 年度滚动前向验证比较了七种机器学习模型以实现鲁棒泛化。
• CatBoost预测34.50°并达到约1,850 kWh m⁻² year⁻¹（1.57 MWh kWp⁻¹ year⁻¹）。
• SHAP可解释性量化了倾角、辐照度和季节特征对产量的影响。
Keyword:
Photovoltaic arrays
PV tilt optimization
Physics-informed machine learning
Liu-Jordan isotropic model
期刊
IF:
4.2
论文数:
1.2W
被引数:
2.2W
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