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dc.contributor.authorJirasak Laowanitwattanaen_US
dc.contributor.authorSermsak Uatrongjiten_US
dc.description.abstractThis paper presents a new algorithm based on the partial least square (PLS) techniques and the arbitrary polynomial chaos expansion (aPCE) for the probabilistic power flow (PPF) analysis of a power system having many uncertain variables. The proposed method uses the nonlinear PLS to transform a set of random input variables to a smaller number of de-correlated random variables. Then, the aPCE technique is applied to generate the basis polynomial functions and build a surrogate model of the power system response. The algorithm has been implemented and tested with the modified IEEE 118-bus and European 1354-bus systems. The numerical results indicate that, similar to the sparse PCE method and the low-rank approximation technique, the proposed method can be applied to high-dimensional PPF problems. Nonetheless, the proposed approach uses smaller computation time, and estimates statistical characteristics of the response with higher accuracy.en_US
dc.titleProbabilistic Power Flow Analysis Based on Partial Least Square and Arbitrary Polynomial Chaos Expansionen_US
article.title.sourcetitleIEEE Transactions on Power Systemsen_US
article.volume37en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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