面向双馈风电场+串补系统的次同步振荡快速自适应抑制控制

Investment Rating - The report does not explicitly provide an investment rating for the industry. Core Insights - The global energy crisis is intensifying, prompting countries to accelerate energy transitions, with wind power becoming a core component of this shift. Cumulative global wind power installations have surpassed 1136 GW, and the penetration rate of wind power in electricity systems is increasing [11][14]. - The interaction between doubly-fed wind farms (DWF) and series compensation (SC) systems can induce subsynchronous oscillations (SSO), which pose significant challenges to the safe and stable operation of new power systems [14][20]. - Existing SSO suppression strategies face technical challenges, including insufficient adaptability and slow response times, necessitating the development of more effective control methods [20][23]. Summary by Sections Research Background - The demand for renewable energy is growing due to the global energy crisis, with countries implementing policies to promote wind energy [11]. - Wind resources are often distributed inversely to load centers, requiring SC to enhance long-distance transmission capabilities, while the interaction between DWF and SC can lead to SSO [14][17]. SSO Control Strategies - Current SSO suppression strategies are categorized into grid-side and wind turbine-side controls, with many lacking adaptability and having slow response times [20][21]. - The classic SSO control strategies (SSDC) are insufficient for broader SSO suppression due to their fixed frequency bands and reliance on specific scenarios [23][25]. MA-SOSC Design - The report introduces the Modified Adaptive Linear Element SSO Suppression Controller (MA-SOSC), which is designed to effectively identify and eliminate SSO components across multiple operating conditions [37][49]. - MA-SOSC utilizes a control architecture that includes SSO filtering, frequency identification, and frequency locking modules, enabling rapid and accurate identification of dominant SSO frequencies [37][39]. FA-SOSC Enhancement - The Fast Adaptive SSO Suppression Controller (FA-SOSC) builds on the MA-SOSC framework, integrating SFFT identification data with Long Short-Term Memory (LSTM) neural network algorithms to improve SSO suppression timeliness [56][60]. - The FA-SOSC's improved locking module can predict dominant SSO frequencies with a 50% reduction in update time, enhancing the controller's responsiveness [62][65]. Summary and Outlook - The report highlights the innovative aspects of the MA-SOSC and FA-SOSC designs, emphasizing their potential for real-time control applications in power systems [71][73]. - Future research should focus on the economic feasibility and engineering viability of SSO suppression strategies, as well as expanding the applicability of models to address complex oscillation scenarios [75][76].