Study on the improvement of measurement accuracy of grid short-circuit parameters based on semi-physical simulation

[1] Noori, M., Effatnejad, R., & Hajihosseini, P. (2017). Using dissolved gas analysis results to detect and isolate the internal faults of power transformers by applying a fuzzy logic method. Iet Generation Transmission & Distribution, 11(10), 2721-2729. Search in Google Scholar

[2] Zaker, B., Gharehpetian, G. B., & Karrari, M. (2018). Equivalent model parameter estimation of grid- connected fuel cell-based microgrid. International Transactions on Electrical Energy Systems, e2540. Search in Google Scholar

[3] Behrooz, Zaker, Gevork, B., Gharehpetian, & Mehdi, et al. (2018). Equivalent model parameter estimation of grid-connected fuel cell-based microgrid. International Transactions on Electrical Energy Systems. Search in Google Scholar

[4] Hao, L., Liang, D., Li, C., & Xiaodong, P. (2017). The correction method for ultra high voltage transmission line parameters based on smart grid dispatching and control system. Electrical Engineering. Search in Google Scholar

[5] Ye, J., Zhou, J., Mao, D., Ge, X., Zhang, J., & Fang, L. (2020). A Lyapunov function theory-based nonlinear control strategy for NPC-type three-level unified power quality conditioner. International Transactions on Electrical Energy Systems. Search in Google Scholar

[6] Liu, Y., & Ding, B. (2022). Short-term prediction method of solar photovoltaic power generation based on machine learning in smart grid. Mathematical Problems in Engineering, 2022. Search in Google Scholar

[7] Zhang, J., Sun, Y., Liu, M., Dong, W., & Han, P. (2018). Research on modeling of microgrid based on data testing and parameter identification. Energies, 11(10), 2525. Search in Google Scholar

[8] Chen, Y., Li, P., Ren, W., Shen, X., & Cao, M. (2020). Field data–driven online prediction model for icing load on power transmission lines:. Measurement and Control, 53(1-2), 126-140. Search in Google Scholar

[9] Aminzadeh, S., Hagh, M. T., & Seyedi, H. (2020). Reactive power management for microgrid frequency control. International journal of electrical power and energy systems. Search in Google Scholar

[10] Bai, X., Tan, J., Ma, S., & Liu, D. (2020). Online estimation of voltage stability margin via deep neural network with consideration of the local structures in power grid. International Transactions on Electrical Energy Systems. Search in Google Scholar

[11] Yang, M., Liu, L., Cui, Y., & Su, X. (2018). Ultra-short-term multistep prediction of wind power based on representative unit method. Mathematical Problems in Engineering, 2018. Search in Google Scholar

[12] Rao, S., & Yuan, Y. (2022). Online monitoring of power grid intelligent voltage stability considering potential factors. Mobile information systems(Pt.19), 2022. Search in Google Scholar

[13] Alvarez-Bustos, A., Kazemtabrizi, B., Shahbazi, M., & Acha-Daza, E. (2021). Universal branch model for the solution of optimal power flows in hybrid ac/dc grids. International Journal of Electrical Power & Energy Systems, 126, 106543. Search in Google Scholar

[14] Wang, R., Sun, Q., Ma, D., & Zhang, X. (2019). The equivalent impedance characteristic analysis of the ac microgrid and its decoupled power flow calculation. International Transactions on Electrical Energy Systems, 29(7). Search in Google Scholar

[15] Swirydowicz, K., Darve, E., Jones, W., Maack, J., Regev, S., & Saunders, M. A., et al. (2022). Linear solvers for power grid optimization problems: a review of gpu-accelerated linear solvers. Parallel computing(Jul.), 111. Search in Google Scholar

[16] Zhang, Z., Jiang, W., Zhang, Y., Wang, X., & Yang, J. (2024). Rate-accuracy optimized quantization algorithm based on roi image coding in power line inspection. Multimedia tools and applications(6), 83. Search in Google Scholar

[17] Pablo Rodríguez-Pajarón, Araceli Hernández, & Milanovi, J. V. (2022). Estimation of harmonics in partly monitored residential distribution networks with unknown parameters and topology. IEEE transactions on smart grid(4), 13. Search in Google Scholar

[18] Chen, L., Chen, S., Xu, J., & Zhou, C. (2024). Power quality disturbances identification based on deep neural network model of time-frequency feature fusion. Electric Power Systems Research, 231. Search in Google Scholar

[19] Wang, Z., Weng, L., Lu, M., Liu, J., & Pan, L. (2021). Application of multiattention mechanism in power system branch parameter identification. Complexity, 2021(4), 1-12. Search in Google Scholar

[20] Wang, Y., Zhang, W., Sun, H., Xiang, Y., & Wang, Z. (2020). Research on fast response criterion of power grid distributed loads after hvdc block fault. IET Generation Transmission & Distribution, 14(6). Search in Google Scholar

[21] Zakariya, M. Z., & Teh, J. (2023). A systematic review on cascading failures models in renewable power systems with dynamics perspective and protections modeling. Electric Power Systems Research. Search in Google Scholar

[22] Lakshminarayana, S., Sthapit, S., & Maple, C. (2022). Application of physics-informed machine learning techniques for power grid parameter estimation. Sustainability, 14. Search in Google Scholar

[23] Zhao Jingbo,Tao Yan & Sun Zhiming.(2023).Analysis of the influence factors of VSC–HVDC on AC three-phase short-circuit current level.Circuit World(4),413-423. Search in Google Scholar

[24] Weiyan Qian,Ruixuan Zhang,Yao Zou,Niancheng Zhou,Qianggang Wang & Ting Yang.(2024). Quantifying the Inverter-Interfaced Renewable Energy Critical Integration Capacity of a Power Grid Based on Short-Circuit Current Over-Limits Probability.Electronics(8). Search in Google Scholar

[25] Gao Senqi,Sun Rui,Fu Ying & Xu Jianguo.(2022).Simulation and application of the electric power steering system simulation platform based on Simulink.Journal of Physics: Conference Series(1). Search in Google Scholar