Faculty Publications
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Item Impact of Different PQ Models of Wind Turbine Generating Units (WTGUs) on System Voltage Performance(Walter de Gruyter GmbH info@degruyter.com, 2017) Moger, T.; Dhadbanjan, T.This paper presents the voltage performance analysis of the system with various types of wind turbine generating units (WTGUs). A detailed voltage performance analysis is carried out by considering the different PQ models used for computing the reactive power output of the WTGUs (fixed/semi-variable speed and variable speed WTGUs). The different PQ models of fixed/semi-variable speed WTGUs incorporated for the studies are voltage dependent model, voltage independent model, power factor based model, and PX model. In addition, the variable speed WTGUs are also considered in different fixed power factor mode of operation. Based on these models, a comparative analysis is presented. A modified 27-bus equivalent distribution test system with dispersed wind generation is considered for the studies. Further, the case studies have been carried out by considering the various wind power output levels of WTGUs to examine its impact on system voltage performance. From the comparative analysis, the power factor based model can be the best choice over the other models (which are based on voltages) for the system studies with fixed/semi-variable speed WTGUs. © 2017 Walter de Gruyter GmbH, Berlin/Boston 2017.Item Probabilistic Load Flow for Wind Integrated Power System Considering Node Power Uncertainties and Random Branch Outages(Institute of Electrical and Electronics Engineers Inc., 2023) Singh, V.; Moger, T.; Jena, D.This paper proposes an analytical probabilistic load flow (PLF) approach that considers conventional generator outages, load variability, and random branch outages. The branch outages are modeled as 0-1 distributions of fictitious power injections at the appropriate nodes. The distribution of state variables and line power flows is then obtained using a combined Cumulant and Gram-Charlier series expansion approach. The proposed PLF performs contingency sequencing with fuzzy logic to eliminate random line checking and avoid masking mistakes faced by performance index-based algorithms. The Jacobian inverse calculation in the traditional Cumulant method is eliminated to conserve storage space and speed up the computation using the Gauss-Jordan method. The correlations among loads and wind power generations has been modeled using the Nataf transformation process. Results of 24-bus and 259-bus equivalent systems of the Indian southern and western power grids are analyzed and validated with those obtained using the Monte Carlo simulation method. The suggested method's efficacy is justified by its accuracy and low computational burden. © 2010-2012 IEEE.Item Probabilistic Load Flow Approach Combining Cumulant Method and K-Means Clustering to Handle Large Fluctuations of Stochastic Variables(Institute of Electrical and Electronics Engineers Inc., 2023) Singh, V.; Moger, T.; Jena, D.The modern electrical power system faces various uncertainties, including load fluctuations, forced outages of conventional generators, network branches. Furthermore, the rising penetration of wind power generation introduces additional uncertainty, causing difficulties in power system planning, operation. This paper uses an analytical probabilistic load flow approach to account for all such uncertainties. The random branch outages are simulated using the fictional powers injections into the relevant nodes. A fuzzy method is used to perform contingency sequencing to avoid masking mistakes that might occur when utilizing performance index-based sequencing methods. The sparse Jacobian inverse is eliminated to preserve storage space, accelerate the computation. A modified Cumulant method is used in conjunction with the K-means clustering process to deal with the substantial fluctuations of the input variables. In the proposed approach, the correlated samples are generated using inverse Nataf transformation. These correlated samples are clustered using K-means clustering. The Cumulant method is applied within each cluster, total probability law is used to integrate each cluster's findings. The proposed PLF is tested on 24-bus, 259-bus wind integrated equivalent systems. Compared with the Monte-Carlo simulation, the proposed PLF yields computationally efficient, more accurate findings. © 1972-2012 IEEE.