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access icon openaccess Evaluation of extended Kalman filter and particle filter approaches for quasi-dynamic distribution system state estimation

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References

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      • 1. Abur, A., Exposito, A.G.: ‘Power system state estimation: theory and implementation’ (Marcel Dekker Inc., Hoboken, USA, 2004), pp. 126.
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      • 8. Blood, E.A., Ilic, M.D., Ilic, J., et al: 2006, ‘A Kalman filter approach to quasi-static state estimation in electric power systems’. 38th North American Power Symp. (NAPS), pp. 417422.
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      • 9. Hernández, C., Maya-Ortiz, P.: 2015, ‘Comparison between WLS and Kalman Filter method for power system static state estimation’. Int. Symp. Smart Electric Distribution Systems and Technologies (EDST), pp. 4752.
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      • 11. Emami, K., Fernando, T., Nener, B.: 2014, ‘Power system dynamic state estimation using particle filter’, IEEE 40th Annual Conf. the Industrial Electronics Society (IECON), pp. 248253.
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      • 12. Cigré Task Force C6.04: ‘Benchmark systems for network integration of renewable and distributed energy resources’, Technical Brochure 575, France, 2014.
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      • 14. Kays, J.: ‘Agent-based simulation environment for improving the planning of distribution grids’, Reihe ie3, Institut für Energiesysteme, Energieeffizienz und Energiewirtschaft, 2014, 14, pp. 6467.
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