Forecasting-Aided Graphical Learning for Robust State Estimation of Distribution System
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9251-5_11
Reference18 articles.
1. Primadianto, A., Lu, C.N.: A review on distribution system state estimation. IEEE Trans. Power Syst. 32(5), 3875–3883 (2017)
2. Zhao, J., et al.: Power system dynamic state estimation: motivations, definitions, methodologies, and future work. IEEE Trans. Power Syst. 34(4), 3188–3198 (2019)
3. Zhang, Y., Wang, J., Li, Z.: Interval state estimation with uncertainty of distributed generation and line parameters in unbalanced distribution systems. IEEE Trans. Power Syst. 35(1), 762–772 (2020)
4. Ngo, V., Wu, W.: Linear programming contractor for interval distribution state estimation using RDM arithmetic. IEEE Trans. Power Syst. 36(3), 2114–2126 (2021)
5. Baran, M.E., Kelley, A.W.: State estimation for real-time monitoring of distribution systems. IEEE Trans. Power Syst. 9(3), 1601–1609 (1994)
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