Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Jena, D.Subject: search.filters.subject.Probabilistic load flow

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    Sequence operation theory based probabilistic load flow assessment with photovoltaic generation
    (Institution of Engineering and Technology, 2015) Prusty, B.R.; Jena, D.
    This paper proposes a probabilistic load flow approach considering source and load uncertainties. Usually influence of these uncertainties is not considered in deterministic load flow. These uncertainties are a challenge to identify a competent and accurate method for load flow studies. Source uncertainty such as photovoltaic (PV) generation and load uncertainty are modelled as probabilistic discrete sequences and sequence operation theory is applied for load flow analysis. The disturbance in load flow pattern is studied in the presence of PV generation. Correctness of assuming a specific parametric distribution for real PV generation data is verified. DC load flow model is used to implement the proposed method to save memory and reduce computational time. Probabilistic distribution of output random variables (RVs) using proposed method and cumulant method are compared with the distributions obtained using Monte-Carlo simulation. The analysis is carried out on Wood and Woollenberg 6 bus system. The results have clearly established the fact that, application of the proposed method has accurately evaluated the distribution of output RVs.
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    Modeling of power demands of electric vehicles in correlated probabilistic load flow studies
    (Institute of Electrical and Electronics Engineers Inc., 2017) Bhat, N.G.; Prusty, B.R.; Jena, D.
    In this paper, extended cumulant method (ECM) is applied to probabilistic load flow analysis. Input uncertainties pertaining to plug-in hybrid electric vehicle and battery electric vehicle charging demands in residential community as well as charging stations are probabilistically modeled. Probability distributions of the result variables such as bus voltages and branch power flows pertaining to these inputs are accurately approximated; and at the same time, multiple input correlation cases are incorporated. The performance of ECM is demonstrated on the modified IEEE 69-bus radial distribution system. The results of ECM are compared with Monte-Carlo simulation. © 2016 IEEE.
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    A detailed formulation of sensitivity matrices for probabilistic load flow assessment considering electro-thermal coupling effect
    (IEEE Computer Society, 2017) Prusty, B.R.; Jena, D.
    In recent times, use of an analytical method (AM) is prevalent in solving probabilistic load flow (PLF) problem for better computational efficiency. AMs are employed to power system models that endure linear relations between the result variables and input random variables via sensitivity matrices. The accuracy of a sensitivity matrix-based PLF model can be improved by considering the effects of environmental conditions on line parameters. Looking out for an opportunity to upgrade existing PLF model to foresee the strength of thermal resistance model, a temperature-augmented model is presented. A detailed mathematical formulation of the aforesaid model is deliberated. The influence of temperature-augmentation on distributions of resistances, temperatures, power flows, and power losses of the temperature dependent branches is studied in detail. Finally, a note on applicability of the proposed model in the assessment of various power system studies is discussed. © 2017 IEEE.
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    Probabilistic Load Flow in a Transmission System Integrated with Photovoltaic Generations
    (Springer Verlag service@springer.de, 2019) Prusty, B.; Jena, D.
    This paper compares the performance (solution accuracy and computational efficiency) of two hybrid methods (HMs) for probabilistic load flow (PLF) considering a mixture of discrete as well as correlated Gaussian and non-Gaussian input random variables. The PLF is accomplished on IEEE 118-bus test system with photovoltaic arrays installed at specific buses. The results of the HMs are compared with that of the existing methods such as combined cumulant and Gram-Charlier method, combined cumulant and Cornish-Fisher method, dependent discrete convolution method, and Monte Carlo simulation. © 2019, Springer Nature Singapore Pte Ltd.
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    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.
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    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.