Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Comparative Evaluation of Basic Probabilistic Load Flow Methods with Wind Power Integration(Institute of Electrical and Electronics Engineers Inc., 2021) Singh, V.; Moger, T.; Jena, D.The unprecedented penetration of distributed energy resources (DERs) such as wind power generations (WPGs) poses tremendous challenges for for the planning and maintenance of power systems due to their intermittent and uncertain nature. This paper mainly focuses on comparing basic probabilistic load flow (PLF) techniques when WPGs are integrated into the existing power grid. Considering loads and WPGs as random inputs, the performance of the cumulant method (CM) and point estimation method (PEM) are analyzed with respect to Monte-Carlo method for higher precision and less computational time. Case-studies are carried out on sample 10-bus and SR 72-bus equivalent systems. Simulation results demonstrated that 2n+1 PEM provides the best performance when dealing with high level of uncertainty associated with input variables. © 2021 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.