Predicting the behavior of a grid-connected photovoltaic system from measurements of solar radiation and ambient temperature

J. Hernandez, G. Gordillo and W. Vallejo

Applied Energy, 2013, vol. 104, issue C, 527-537

Abstract: This paper presents a methodology to predict in a statistically reliable way the behavior of a grid-connected photovoltaic system. The methodology developed can be implemented either in common programming software or through an off-the-shelf simulation of electrical systems. Initially, the atmospheric parameters that influence the behavior of PV generators (radiation and temperature) are characterized in a probabilistic manner. In parallel, a model compound by various PV generator components is defined: the modules (and their electrical and physical characteristics), their connection to form the generator, and the inverter type. This model was verified for comparing their behavior with output measured on a real installed system of 3.6kWp. The solar resource characterized and the photovoltaic system model are integrated in a non-deterministic approach using the stochastic Monte Carlo method, developed in the programming language DPL of the electrical-systems simulation software DIGSILENT®. It is done to estimate the steady-state electrical parameters describing the influence of the grid-connected photovoltaic system. Specifically, we estimated the nominal peak power of the PV generator to minimize network losses, subject to constraints on nodes voltages and conductor currents.

Keywords: Grid-connected PV systems; Monte Carlo method; Radiation and ambient temperature analysis (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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DOI: 10.1016/j.apenergy.2012.10.022

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