Motion Equation Modeling of LCC-HVDC Stations for Analyzing DC and AC Network Interactions

• Published in: IEEE transactions on power delivery Vol. 35; no. 3; pp. 1563 - 1574
• Main Authors: Lu, Jun, Yuan, Xiaoming, Hu, Jiabing, Zhang, Meiqing, Yuan, Hao
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: AC and DC; Alternating current; Computer simulation; Direct current; dynamic interaction; Dynamic stability; Dynamics; Electric converters; Electric power grids; Equations of motion; Firing; LCC-HVDC station; Mathematical model; modeling; motion equation; Phase locked loops; Power grids; Power system dynamics; Power system stability; State variable; Stations
• ISSN: 0885-8977; 1937-4208
• DOI: 10.1109/TPWRD.2019.2947572

Line-commutated converter based high voltage direct current (LCC-HVDC) transmissions are widely applied in delivering large-capacity electricity in China. Multiple large-capacity LCC-HVDC transmissions strengthen dynamic coupling between AC and DC networks. Existing literature has reported some stability problems caused by dynamic interactions between AC and DC power grids, however, the mechanism behind these problems has not been totally understood and revealed. To analyze dynamic interactions between AC and DC power grids, this article presents a small-signal model to understand the external characteristics of LCC-HVDC stations based on the motion equation concept. Comparison of time-domain simulation response with the detailed switching model shows that the proposed model can hold main behaviors of concern. Dynamic interactions between AC and DC power grids are studied based on the proposed model in multi-infeed LCC-HVDC systems. Analytical results demonstrate that there exists power dynamics in receiving AC grid when sending AC grid subjects to a disturbance, and effects of converter stations' controller parameters on power dynamics are explained by the physical relationship among state variables of the proposed model.