Qing Zhu¹, Denghui Guo¹, Rui Ruan¹, Zhidong Chai¹, Chaoqun Wang², Zhiwen Guan^2,*

Energy Engineering, Vol.122, No.8, pp. 3133-3154, 2025, DOI:10.32604/ee.2025.063165 - 24 July 2025

Abstract This study presents an emergency control method for sub-synchronous oscillations in wind power grid-connected systems based on transfer learning, addressing the issue of insufficient generalization ability of traditional methods in complex real-world scenarios. By combining deep reinforcement learning with a transfer learning framework, cross-scenario knowledge transfer is achieved, significantly enhancing the adaptability of the control strategy. First, a sub-synchronous oscillation emergency control model for the wind power grid integration system is constructed under fixed scenarios based on deep reinforcement learning. A reward evaluation system based on the active power oscillation pattern of the system is… More >

Chongyang Zhao, Wei Chai, Beibei Rui, Lin Chen^*

Energy Engineering, Vol.120, No.11, pp. 2683-2705, 2023, DOI:10.32604/ee.2023.029620 - 31 October 2023

Abstract At present, the direct drive permanent magnet synchronous generator (DD-PMSG) grid connected system based on virtual synchronous generator (VSG) control will experience power oscillation at sub synchronous frequencies. The mechanism and characteristics of this new type of sub-synchronous interaction (SSI) are not yet clear, and the system cannot recover to steady state solely based on the characteristics of VSG itself. Especially when connected to a weak current network, oscillations are more pronounced, affecting the stability of the system. In severe cases, the system may trigger shutdown protection and be disconnected from the network. Existing research More >

Lei Wang¹, Tiecheng Li¹, Hui Fan², Xuekai Hu¹, Lin Yang³, Xiaomei Yang^3,*

Energy Engineering, Vol.120, No.4, pp. 851-867, 2023, DOI:10.32604/ee.2023.025383 - 13 February 2023

Abstract In recent years, subsynchronous resonance (SSR) has frequently occurred in DFIG-connected series-compensated systems. For the analysis and prevention, it is of great importance to achieve wide area monitoring of the incident. This paper presents a Hankel dynamic mode decomposition (DMD) method to identify SSR parameters using synchrophasor data. The basic idea is to employ the DMD technique to explore the subspace of Hankel matrices constructed by synchrophasors. It is analytically demonstrated that the subspace of these Hankel matrices is a combination of fundamental and SSR modes. Therefore, the SSR parameters can be calculated once the More >