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Power Flow Analysis under Uncertainty using Symmetric Fuzzy Arithmetic Manuel Marin 6129d321bde77a77d93f828fa5287807 univ-perp.fr 938923 701871-938923 David Defour 67af2e8afbd85766c069226056dec94d univ-perp.fr david-defour 4651 1032-4651 https://orcid.org/0000-0001-9923-2394 https://www.idref.fr/104542454 Federico Milano 905737-0 David Defour 67af2e8afbd85766c069226056dec94d univ-perp.fr 2019-12-20 13:01:34 2025-08-13 03:12:53 2019-12-20 14:36:29 2014-07-27 2019-12-20 contributor David Defour 67af2e8afbd85766c069226056dec94d univ-perp.fr CCSD lirmm-01206373 https://hal-lirmm.ccsd.cnrs.fr/lirmm-01206373 marin:lirmm-01206373 <i>PES General Meeting 2014 | Conference & Exposition</i>, Jul 2014, National Harbor, MD, United States. pp.1-5, <a target="_blank" href="https://dx.doi.org/10.1109/PESGM.2014.6939274">⟨10.1109/PESGM.2014.6939274⟩</a> PES General Meeting 2014 | Conference & Exposition, Jul 2014, National Harbor, MD, United States. pp.1-5, ⟨10.1109/PESGM.2014.6939274⟩ HAL Authorization CNRS - Centre national de la recherche scientifique Université Perpignan Via Domitia Digits, architectures et logiciels informatiques Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier Mathématiques, Informatique, Physique et Systèmes Université de Montpellier Université de Montpellier (2015-2021) International No No Yes Yes Power Flow Analysis under Uncertainty using Symmetric Fuzzy Arithmetic Manuel Marin 6129d321bde77a77d93f828fa5287807 univ-perp.fr 938923 701871-938923 David Defour 67af2e8afbd85766c069226056dec94d univ-perp.fr david-defour 4651 1032-4651 https://orcid.org/0000-0001-9923-2394 https://www.idref.fr/104542454 Federico Milano 905737-0 PES General Meeting 2014 | Conference & Exposition 2014-07-27 2014-07-31 National Harbor, MD United States IEEE 1-5 2014 10.1109/PESGM.2014.6939274 English Jacobian matrices Vectors Uncertainty Symmetric matrices Probabilistic logic Power systems Equations Computer Science [cs]/Hardware Architecture [cs.AR] Conference papers Conference papers Conference papers

This paper present a novel approach using symmetric fuzzy numbers to deal with uncertainty in power system analysis. Special attention is put on reducing overestimation due to conservatism inherent in fuzzy arithmetic. The midpoint-radius interval representation and a linear programming optimization problem are used in order to enhance efficiency and accuracy, respectively. The proposed method is tested over the IEEE 14-bus test system and compared with other techniques available in the literature. The case study that the proposed method yields accurate results at a reduced computational cost.

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