%0 Journal Article
%T Mismatch Loss Reduction in Photovoltaic Arrays as a Result of Sorting Photovoltaic Modules by Max-Power Parameters
%A J. Webber
%A E. Riley
%J ISRN Renewable Energy
%D 2013
%R 10.1155/2013/327835
%X Variations in photovoltaic (PV) module current-voltage curves result in a power loss in PV arrays often referred to as mismatch loss (MML). As a means of reducing MML, newly fabricated PV modules are sorted to meet a set tolerance for variation in overall maximum power output with respect to a given module¡¯s rated power. Starting with flash test data sets for two different polycrystalline PV modules and a simulated sorting procedure, Monte Carlo techniques were used to generate a large number of artificial PV arrays. The MMLs for each of these arrays were then calculated to assess the sorting procedure¡¯s ability to reduce MML. Overall MMLs were quite small (0.001¨C0.01%). Sorting by resulted in the most consistent MML reductions. Sorting by yielded insignificant results. Sorting by yielded significant MML reduction in only one of the two PV module data sets. Analysis was conducted to quantify if additional sorting on top of what both manufacturers had already done would make economic sense. Based on high level economic analysis, it appears that additional sorting yields little economic gain; however, this is highly dependent upon manufacturer sorting cost. 1. Introduction Differences in the current-voltage characteristics of photovoltaic (PV) modules give rise to a type of power loss referred to as ¡°electrical mismatch¡± once modules are connected to networks of series and parallel strings called arrays. The consequence of ¡°mismatch loss¡± (MML) is that the total power output of a PV array will be less than the sum of the power outputs of the modules as if they were acting independently [1]. This phenomenon has been investigated by a number of authors [1¨C5] primarily by using one of two methods: the comparison between a PV array¡¯s ideal max-power and the actual max-power computed by progressively synthesizing the curves of modules, series strings, and finally the complete PV array; and MML estimates of PV arrays composed of modules with known or statistically generated characteristics. This second method was made possible by an equation developed by Bucciarelli [1] that estimates MML in PV arrays composed of modules with relatively small variations in their characteristics. Bucciarelli¡¯s [1] model was found to adequately estimate MMLs in 100£¿kWp arrays by Iannone et al. [2], combining and expanding on the work of Bishop [3] who used random numbers to generate PV modules arranged into arrays, and Chamberlin et al. [4], who estimated small MML values in randomly arranged arrays of four 48£¿Wp PV modules. After a brief outline of some of the causative
%U http://www.hindawi.com/journals/isrn.renewable.energy/2013/327835/