Conference Papers
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Item Probabilistic Load Flow Considering Load and Wind Power Uncertainties using Modified Point Estimation Method(Institute of Electrical and Electronics Engineers Inc., 2022) Singh, V.; Moger, T.; Jena, D.Nowadays, renewable energy sources (REs) are increasingly integrated into electrical power networks. Among many REs, wind energy has emerged as a prominent source of electricity. However, rising wind power penetration has increased the system's net generation variability. Consequently, the ability to monitor and simulate the behavior of wind power generation (WPG) in detail is critical. Furthermore, the wind speed or wind power output of different wind farms can be highly interdependent and may not follow Normal distribution. This study proposes a probabilistic load flow (PLF) technique for modeling normally distributed loads and non-normally distributed WPG based on the modified point estimation method (PEM). This modification allows modeling dependent input random variables as a function of many independent ones using the Nataf transformation. By utilizing the findings of the Monte-Carlo method as a reference, the usefulness of the suggested technique is tested by conducting case studies on a 24-bus equivalent system of the Indian Southern region power grid. Simulation results indicate that the modified PEM can easily handle the correlation and have high processing efficiency. © 2022 IEEE.Item Modified Cumulant based Probabilistic Load Flow Considering Correlation between Loads and Wind Power Generations(Institute of Electrical and Electronics Engineers Inc., 2022) Singh, V.; Moger, T.; Jena, D.With the growing use of wind sources, power system analysis should consider the variation of wind power and the correlation among wind farms. In this paper, the Cumulant method (CM) for performing probabilistic load flow (PLF) analysis is modified to account for the correlation between random input variables. Considering the dependence between loads and wind power generations (WPGs), the modified CM models the dependent variables as a function of many independent ones using the Nataf transformation. The effectiveness of the suggested method is verified by performing case studies on a 24-bus equivalent system of the Indian southern region power grid. Furthermore, relative error values in reference with the Monte-Carlo simulation (MCS) method are analyzed. © 2022 IEEE.