Improved parametric empirical determination of module short circuit current for modelling and optimization of solar photovoltaic systems

被引:18
作者
Andrews, Rob W. [1 ]
Pollard, Andrew [1 ]
Pearce, Joshua M. [2 ,3 ]
机构
[1] Queens Univ, Dept Mech & Mat Engn, Kingston, ON K7L 3N6, Canada
[2] Michigan Technol Univ, Dept Mat Sci & Engn, Houghton, MI 49931 USA
[3] Michigan Technol Univ, Dept Elect & Comp Engn, Houghton, MI 49931 USA
基金
加拿大自然科学与工程研究理事会;
关键词
Photovoltaic; PV; System modelling; Short-circuit current; Translation models; PERFORMANCE; SPECTRUM; STATES;
D O I
10.1016/j.solener.2012.04.016
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Correct modelling of solar photovoltaic (PV) system yields is necessary to optimize system design, improve reliability of projected outputs to ensure favourable project financing and to facilitate proper operations and maintenance. An improved methodology for fine resolution modelling of PV systems is presented using module short-circuit current (I-sc) at 5-mM time-scales, and clearly identifies pertinent error mechanisms that arise when working at this high resolution. This work used a modified version of the Sandia array performance model, and introduces new factors to the calculation of I-sc. to account for identified error mechanisms, including instrumentation alignment, spectral, and module power tolerance errors. A simple methodology was introduced and verified where specific module parameters can be derived solely from properly filtered performance time series data. In particular, this paper focused on methodologies for determining the predicted I-sc for a variety of solar PV module types. These methods of regressive analysis significantly reduced the error of the predicted model, and demonstrate the need for this form of modelling when evaluating long term PV array performance. This methodology has applications for current systems operators, which will enable the extraction of useful module parameters from existing data in addition to more precise continuous monitoring of existing systems, and can also be used to more accurately model and optimize new systems. (c) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2240 / 2254
页数:15
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