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|dc.identifier.citation||IET Conference Publications, 2015, Vol.2015, CP683, pp.164-169||en_US|
|dc.description.abstract||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.||en_US|
|dc.title||Sequence operation theory based probabilistic load flow assessment with photovoltaic generation||en_US|
|Appears in Collections:||2. Conference Papers|
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