2017 19th International Conference on Intelligent System Application to Power Systems (ISAP) 2017
DOI: 10.1109/isap.2017.8071423
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Merging conventional and phasor measurements in state estimation: A multi-criteria perspective

Abstract: This paper presents a new proposal for sensor fusion in power system state estimation, analyzing the case of data sets composed of conventional measurements and phasor measurements from PMUs. The approach is based on multiple criteria decision-making concepts. The equivalence of an L1 metric in the attribute space to the results from a Bar-Shalom-Campo fusion model is established. The paper shows that the new fusion proposal allows understanding the consequences of attributing different levels of confidence or… Show more

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Cited by 4 publications
(2 citation statements)
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“…The studies of SE with PMU measurements have already been extensively carried out, the approaches are either based on the combination of SCADA and PMU measurements [12][13][14][15][16][17][18] or purely PMU measurements [8,[19][20][21]. The former ones can be further divided into two categories: namely hybrid state estimator method and multistage method.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…The studies of SE with PMU measurements have already been extensively carried out, the approaches are either based on the combination of SCADA and PMU measurements [12][13][14][15][16][17][18] or purely PMU measurements [8,[19][20][21]. The former ones can be further divided into two categories: namely hybrid state estimator method and multistage method.…”
Section: Introductionmentioning
confidence: 99%
“…To address the issues of time scale inconsistency, the multi‐stage approach is adopted by processing PMU measurements or SCADA measurements in independent stages. A Bar‐Shalom‐Campo data fusion technique is applied to combine the results of different PMU and SCADA stages in [17, 18]. All those methods based on the combination of SCADA and PMU measurements adopt various principles to enhance the robustness against gross errors.…”
Section: Introductionmentioning
confidence: 99%