Gaussian Copula Methodology to Model Photovoltaic Generation Uncertainty Correlation in Power Distribution Networks

Deterministic load flow analyses of power grids do not include the uncertain factors that affect network elements; hence, their predictions can be very unreliable for distribution system operators and decision makers who deal with expansion planning network. Adding probability parameters in deterministic is vital to capture wide variability currents voltages. This achieved by probabilistic studies. Photovoltaic systems represent a remarkable source uncertainty In this study, we used Gaussian copula model correlated photovoltaic generators. Correlations among generators were also included exploiting technique. The large sets samples generated statistical method (Gaussian copula) as inputs Monte Carlo simulations. proposed methodologies tested on two different networks, i.e., 13 node IEEE test feeder non-synthetic European low voltage Node health, measured percentage unbalance factor, investigated. importance including correlations discussed.