2006 International Conference on Power System Technology 2006
DOI: 10.1109/icpst.2006.321574
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Research on Illed-Conditioned Equations in Tracking Thevenin Equivalent Parameters with Local Measurements

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Cited by 8 publications
(6 citation statements)
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“…In particular, the error of PSO increases beyond the acceptable margins when both loads are time varying and the "Ratio of change margins of the loads" grows up to unity or higher. The SFLA has the lowest error when both loads are constant, while the estimation methods in the previous references are unable to deal with such a condition [15][16][17][18][19][20]. Figure 7 shows the convergence profiles of the SFLA and PSO during estimation processes under the three mentioned conditions.…”
Section: Sample Estimation Resultsmentioning
confidence: 99%
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“…In particular, the error of PSO increases beyond the acceptable margins when both loads are time varying and the "Ratio of change margins of the loads" grows up to unity or higher. The SFLA has the lowest error when both loads are constant, while the estimation methods in the previous references are unable to deal with such a condition [15][16][17][18][19][20]. Figure 7 shows the convergence profiles of the SFLA and PSO during estimation processes under the three mentioned conditions.…”
Section: Sample Estimation Resultsmentioning
confidence: 99%
“…However, under constant load, the two equations will be the same and the TE parameters cannot be determined uniquely. Reference [16] tries to give a solution for this problem; however, this is a rigid mathematical problem and cannot be resolved as long as the load is constant.…”
Section: Online Estimation Of Thevenin Equivalent Parametersmentioning
confidence: 99%
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“…The high level procedure is summarised in Fig. 3, where the adaptive technique is based on [60], the recursive least squares (RLS) solver is derived from [61]- [64], and the algebraic technique is derived from [24], [65].…”
Section: ) Local Pmu Derived Observersmentioning
confidence: 99%
“…However, their performances cannot solve the problem of algorithm divergence caused by the ill-conditioned matrix inverse and lack the robustness and adaptive tracking ability when the system changes. According to the analysis of the ill-conditioned Thevenin equivalent parameters equations, a method based on Schmidt's orthogonalization transformation is presented in [30] to obtain precise solutions. A dynamic state estimation methodology was proposed in [31], which combined a new regularization-based method with a Markov model representation to improve estimation accuracy over classic methodologies based on static load pseudo measurements.…”
Section: Introductionmentioning
confidence: 99%