Power system simulations that extend over a time period of minutes, hours, or even longer are called extended-term simulations. As power systems evolve into complex systems with increasing interdependencies and richer dynamic behaviors across a wide range of timescales, extended-term simulation is needed for many power system analysis tasks (e.g., resilience analysis, renewable energy integration, cascading failures), and there is an urgent need for efficient and robust extended-term simulation approaches. The conventional approaches are insufficient for dealing with the extended-term simulation of multi-timescale processes. This paper proposes an extended-term simulation approach based on the semi-analytical simulation (SAS) methodology. Its accuracy and computational efficiency are backed by SAS's high accuracy in event-driven simulation, larger and adaptive time steps, and flexible switching between full-dynamic and quasi-steady-state (QSS) models. We used this proposed extended-term simulation approach to evaluate bulk power system restoration plans, and it demonstrates satisfactory accuracy and efficiency in this complex simulation task.
Chen, J. J., Crow, M. L. (2008). A variable partitioning strategy for the multirate method in power systems. IEEE Transactions on Power Systems, 23: 259–266.
Yao, R., Huang, S. W., Sun, K., Liu, F., Zhang, X. M., Mei, S. W. (2016). A multi-timescale quasi-dynamic model for simulation of cascading outages. IEEE Transactions on Power Systems, 31: 3189–3201.
Chen, L. Z., Zhang, H. X., Wu, Q. W., Terzija, V. (2018). A numerical approach for hybrid simulation of power system dynamics considering extreme icing events. IEEE Transactions on Smart Grid, 9: 5038–5046.
Vournas, C. D., Manos, G. A. (1998). Modelling of stalling motors during voltage stability studies. IEEE Transactions on Power Systems, 13: 775–781.
Yao, R., Liu, Y., Sun, K., Qiu, F., Wang, J. H. (2020). Efficient and robust dynamic simulation of power systems with holomorphic embedding. IEEE Transactions on Power Systems, 35: 938–949.
Rao, S., Feng, Y., Tylavsky, D. J., Subramanian, M. K. (2016). The holomorphic embedding method applied to the power-flow problem. IEEE Transactions on Power Systems, 31: 3816–3828.
Liu, C. X., Wang, B., Hu, F. K., Sun, K., Bak, C. L. (2017). Online voltage stability assessment for load areas based on the holomorphic embedding method. IEEE Transactions on Power Systems, 33: 3720–3734.
Wang, C., Hou, Y. H., Qiu, F., Lei, S. B., Liu, K. (2017). Resilience enhancement with sequentially proactive operation strategies. IEEE Transactions on Power Systems, 32: 2847–2857.
Panteli, M., Mancarella, P. (2015). The grid: Stronger, bigger, smarter?: Presenting a conceptual framework of power system resilience. IEEE Power and Energy Magazine, 13: 58–66.
Huang, G., Wang, J. H., Chen, C., Qi, J. J., Guo, C. X. (2017). Integration of preventive and emergency responses for power grid resilience enhancement. IEEE Transactions on Power Systems, 32: 4451–4463.
Song, J. J., Cotilla-Sanchez, E., Ghanavati, G., Hines, P. D. H. (2016). Dynamic modeling of cascading failure in power systems. IEEE Transactions on Power Systems, 31: 2085–2095.
Qiu, F., Li, P. J. (2017). An integrated approach for power system restoration planning. Proceedings of the IEEE, 105: 1234–1252.
Yao, R., Sun, K., Qiu, F. (2019). Vectorized efficient computation of padé approximation for semi-analytical simulation of large-scale power systems. IEEE Transactions on Power Systems, 34: 3957–3959.
Ju, W. Y., Sun, K., Yao, R. (2018). Simulation of cascading outages using a power-flow model considering frequency. IEEE Access, 6: 37784–37795.
Yao, R., Qiu, F. (2020). Novel AC distribution factor for efficient outage analysis. IEEE Transactions on Power Systems, 35: 4960–4963.
Stahl, H. (1985). Extremal domains associated with an analytic function Ⅱ. Complex Variables, Theory and Application: an International Journal, 4: 325–338.
Basiri-Kejani, M., Gholipour, E. (2017). Holomorphic embedding load-flow modeling of thyristor-based FACTS controllers. IEEE Transactions on Power Systems, 32: 4871–4879.
This work was supported by the lab-directed research & development (LDRD) program of Argonne National Laboratory and U.S. DOE Advanced Grid Modeling Program grant DE-OE0000875. We also acknowledge the Laboratory Computing Resource Center of Argonne National Laboratory.
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