Abstract
Photovoltaic (PV) systems are usually developed by configuring the PV arrays with regular connection schemes, such as series-parallel, total cross-tied, bridge-linked, among others. Such a strategy is aimed at increasing the power that is generated by the PV system under partial shading conditions, since the power production changes depending on the connection scheme. Moreover, irregular and non-common connection schemes could provide higher power production for irregular (but realistic) shading conditions that aere caused by threes or other objects. However, there are few mathematical models that are able to predict the power production of different configurations and reproduce the behavior of both regular and irregular PV arrays. Those general array models are slow due to the large amount of computations that are needed to find the PV current for a given PV voltage. Therefore, this paper proposes a general mathematical model to predict the power production of regular and irregular PV arrays, which provides a faster calculation in comparison with the general models that were reported in the literature, but without reducing the prediction accuracy. The proposed modeling approach is based on detecting the inflection points that are caused by the bypass diodes activation, which enables to narrow the range in which the modules voltages are searched, thus reducing the calculation time. Therefore, this fast model is useful in designing the fixed connections of PV arrays that are subjected to shading conditions, in order to reconfigure the PV array in real-time, depending on the shading pattern, among other applications. The proposed solution is validated by comparing the results with another general model and with a circuital implementation of the PV system.
Highlights
The recent world challenges that are related to environmental and energy subjects have lead photovoltaic (PV) systems to become a competitive option for electricity generation
Mathematical modeling is a useful tool for analyzing the electrical relationships between voltages and currents in a PV array; it makes obtaining the current vs. voltage (I-V) and power vs. voltage (P-V) curves possible, which are needed for performing different kinds of studies on a PV array, such as energy estimation, degradation, and failure analysis, among others
The main contribution of this model is the reduction of the processing time by using the inflection point concept to limit the search range of the node voltages in the solution of each sub-array, which enables analyzing larger arrays in the same time interval when compared with a previously published model
Summary
The recent world challenges that are related to environmental and energy subjects have lead photovoltaic (PV) systems to become a competitive option for electricity generation. The authors use a machine learning-based technique to calculate the power of PV arrays using single and double-diode module models This solution does not apply to any configuration and it does not consider partial shading or mismatching operating conditions. This paper is based on the following hypothesis: it is possible to improve the computation times for analyzing PV arrays with any size and configuration by combining the inflection points modeling technique of [10] with the circuital nodes principle that is presented in [14] In this way, the new solution provides the same analytical versatility to model any PV array (any size and configuration), but with much shorter processing times.
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