Numéro |
Sci. Tech. Energ. Transition
Volume 79, 2024
Decarbonizing Energy Systems: Smart Grid and Renewable Technologies
|
|
---|---|---|
Numéro d'article | 4 | |
Nombre de pages | 12 | |
DOI | https://doi.org/10.2516/stet/2023045 | |
Publié en ligne | 11 janvier 2024 |
- Chen G.P., Li M.J., Xu T., et al. (2017) Research on technical bottleneck of new energy development, Chin. J. Electric. Eng. 37, 1, 20–27. [Google Scholar]
- Sun H.D., Wang B.C., Li W.F., et al. (2020) Study on Inertia System of Frequency Response of High Proportion Power Electronic Power System[J], Chin. J. Electric. Eng. 40, 16, 5179–5192. [Google Scholar]
- Yang M., Qu W.Y., Chen Y.Y., et al. (2018) Online inertia identification of servo system based on variable period recursive least square method and Kalman observer, Trans. China Electrotech. Soc. 33, S2, 367–376. [Google Scholar]
- Wang B., Yang D.Y., Cai G.W. (2020) Overview of research on inertia of power system under high proportion of new energy access, Power Grid Technol. 44, 8, 2998–3007. [Google Scholar]
- Inoue T., Taniguchi H., Ikeguchi Y., Yoshida K. (1997) Estimation of power system inertia constant and capacity of spinning-reserve support generators using measured frequency transients, IEEE Trans. Power Syst. 12, 1, 136–143. [CrossRef] [Google Scholar]
- Ashton P., Saunders C., Taylor G., Carter A., Bradley M. (2017) Inertia estimation of the GB power system using synchrophasor measurements, in 2017 IEEE Power & Energy Society General Meeting. [Google Scholar]
- Phurailatpam C., Rather Z.H., Bahrani B., et al. (2020) Measurement based estimation of inertia in AC microgrids, IEEE Trans. Sustain. Energy 11, 3, 1975–1984. [CrossRef] [Google Scholar]
- Sun M., Feng Y., Wall P., et al. (2019) On-Line power system inertia calculation using wide area measurements, Int. J. Electr. Power Energy Syst. 109, 325–331. [CrossRef] [Google Scholar]
- Li D.D., Guo T.Y., Liu Q.F., et al. (2021) Inertia estimation of renewable power system considering photovoltaics, Acta Energizer Solaris Sinica. 42, 5, 174–179. [Google Scholar]
- You S., Liu Y., Kou G., et al. (2018) Non-invasive identification of inertia distribution change in high renewable systems using distribution level PMU, IEEE Trans. Power Syst. 33, 1, 1110–1112. [CrossRef] [MathSciNet] [Google Scholar]
- Zhao B., Zhang D., Hu L.J., et al. (2020) Inertia-distribution estimation method based on characteristics of electromechanical disturbance propagation, Electric Power Construction 41, 8, 25–31. [Google Scholar]
- Cao X., Stephen B., Abdulhadi I.F., et al. (2016) Switching Markov Gaussian models for dynamic power system inertia estimation, IEEE Trans. Power Syst. 31, 5, 3394–3403. [CrossRef] [Google Scholar]
- Schiffer J., Aristidou P., Ortega R. (2019) Online estimation of power system inertia using dynamic regressor extension and Mix-ing, IEEE Trans Power Syst. 34, 6, 4993–5001. [CrossRef] [Google Scholar]
- Allenlla F., Chiodo E., Giannuzzi G.M., et al. (2020) On-Line estimation assessment of power systems inertia with high penetration of renewable generation, IEEE Access 8, 62689–62697. [CrossRef] [Google Scholar]
- Tuttelberg K., Kilter J., Wilson D., et al. (2018) Estimation of power system inertia from ambient wide area measurements, IEEE Trans. Power Syst. 33, 6, 7249–7257. [CrossRef] [Google Scholar]
- Liu F., Wang X.B. (2019) System identification and modeling, China University of Geosciences Press, WuHan. [Google Scholar]
- Xin B., Bai Y.Q., Chen J. (2012) Two-stage ARMAX parameter identification based on bias cancellation least squares estimation and Durbin Method, J. Autom. 38, 3, 491–496. [Google Scholar]
- Salat R., Awtoniuk M., Korpysz K. (2017) Black-box identification of a pilot-scale Dryer model: A support vector regression and an imperialist competitive algorithm approach 50, 1, 1559–1564. [Google Scholar]
- Ljung L. (2002) System identification: theory for the user, Tsinghua University Press. [Google Scholar]
- Yi D.H., Wang Y. (2019) Applied time series analysis, China Renmin University Press, Beijing. [Google Scholar]
- Liu J.K., Shen X.R., Zhao L. (2020) System identification theory and MATLAB simulation, Electronic Industry Press, Beijing. [Google Scholar]
- Tang F., Jia J., Liu D.C., et al. (2016) A fast active splitting strategy for large power grid considering generator coherency clustering, Trans China Electrotech. Soc. 31, 17, 32–40. [MathSciNet] [Google Scholar]
- Mosterller F., John W. (1977) Data analysis and regression, Addison-Wesley, Upper Saddle River, NJ. [Google Scholar]
- Feng S., Junjie S., Xiaoheng Z., et al. (2022) Measurement method of inertia constant of power system based on large-scale wind power grid connection, Energy Rep. 8, 6, 19–21. [Google Scholar]
- Fu S., Sirui L., Guodan O., et al. (2023) Inertia estimation of power system with new energy considering with high renewable penetrations, Energy Rep. 9, 7, 1066–1076. [CrossRef] [Google Scholar]
- Xinyu C., Chenqi W., Chenyang Y., et al. (2023) Load-side inertia estimation method based on comprehensive statistics, J. Phys. Conf. Ser. 2588, 1, 1–6. [Google Scholar]
Les statistiques affichées correspondent au cumul d'une part des vues des résumés de l'article et d'autre part des vues et téléchargements de l'article plein-texte (PDF, Full-HTML, ePub... selon les formats disponibles) sur la platefome Vision4Press.
Les statistiques sont disponibles avec un délai de 48 à 96 heures et sont mises à jour quotidiennement en semaine.
Le chargement des statistiques peut être long.