Faculty Publications
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Item 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.Item Modeling of correlated photovoltaic generations and load demands in probabilistic load flow(Institute of Electrical and Electronics Engineers Inc., 2016) Prusty, B.R.; Jena, D.This paper performs probabilistic load flow under the consideration of uncertainty pertaining to conventional generation, photovoltaic (PV) generation and aggregate load demand in power systems. Effect of PV penetration and bus power correlations on distribution of desired random variables (bus voltages and line power flows) is analyzed with the help of an efficient analytical method named modified cumulant method. Generation-generation and load-load correlation cases are considered. Effectiveness of the proposed method has been tested on three test systems such as Ward-Hale 6 bus, IEEE 14 bus and IEEE 30 bus. Results are compared with Monte-Carlo simulation. The effectiveness of the proposed method is justified in terms of accuracy as well as execution time. © 2015 IEEE.Item An efficient hybrid technique for correlated probabilistic load flow study with photovoltaic generations(Institute of Electrical and Electronics Engineers Inc., 2017) Prusty, B.R.; Jena, D.This paper proposes an efficient hybrid technique for probabilistic load flow study. A mixture of correlated Gaussian and non-Gaussian as well as discrete distributions is considered for input random variables. Distributions of desired random variables pertaining to the input random variables are found to be multimodal. Analysis using Gaussian mixture approximation is promising in this context, but computational burden increases significantly with the increase in number of discrete random variables. In contrast, the proposed method precisely obtains distribution of desired random variables in considerably less time without compromising accuracy. Multiple input correlations are effectively incorporated. Accuracy of the proposed method is examined in IEEE 14-bus and 57-bus test systems. Results are compared with combined cumulant-Gaussian mixture approximation method and Monte-Carlo simulation. © 2016 IEEE.