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Improvement of large scale solar installation model for ground current analysis

Application of a simplified PV model to large-scale PV installations neglects the current distortion, potential rise and losses in the system as consequence of the capacitive coupling inside the dc electric circuit. These capacitive couplings represent a leakage impedance loop for the capacitive currents imposed by the high frequency switching performance of power converters. This paper proposes a suitable method to reproduce these harmonic currents injected not only into the grid, but also into the dc circuit of the PV installation. The capacitive coupling proposed of PV modules with ground is modeled as a parallel resistance and capacitor arrangement which leads to an accurate approximation to the real operation response of the PV installation. Results obtained are compared with those of simplified models of PV installations used in literature. An experimental validation of the proposed model was performed with field measurements obtained from an existing 1 MW PV installation. Simulation results are presented together with solutions based on the proposed model to minimize the capacitive ground current in this PV installation for meeting typical power quality regulations concerning to the harmonic distortion and safety conditions and to optimize the efficiency of the installation.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).13 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
