Heuristic grey-box modelling for photovoltaic power systems

被引:4
|
作者
Al-Messabi, Naji [1 ,2 ]
Goh, Cindy [1 ]
Li, Yun [1 ,3 ]
机构
[1] Univ Glasgow, Sch Engn, Glasgow, Lanark, Scotland
[2] Abu Dhabi Transmiss & Despatch Co TRANSCO, Abu Dhabi, U Arab Emirates
[3] Dongguan Univ Technol, Coll Comp Sci & technol, Dongguan, Peoples R China
来源
关键词
Photovoltaic; renewable energy; neural networks; particle swarm optimization; heuristics; grey-box modelling;
D O I
10.1080/21642583.2016.1228485
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Amongst non-conventional generators, photovoltaics (PVs) are becoming more popular owing to their relatively low costs and convenience. However, the intermittency of the PV generator outputs require accurate forecasting, planning, and optimal management. Existing forecasting methods, which are based on either clear-box or black-box modelling, have room for improvement, especially in the accuracy of capturing the underlying PV characteristics and forecasting of PV yields. This paper explores the use of a priori knowledge of PV systems to heuristically improve their clear-box and black-box models. The paper then further explores the use of heuristic grey-box modelling to identify uncertain parameters of physical principle. Incorporating black boxes to account for such un-modelled uncertainties inherent in a clear box provides the resultant grey box with improved forecasting performance and offers a new approach to practical system modelling. The experimental results on an installed PV system have confirmed the usefulness of this approach.
引用
收藏
页码:235 / 246
页数:12
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