The Yunnan power grid has a large-scale hydropower station whereby the power generated at the station is transmitted via HVDC lines under an asynchronous operation mode. In the system performance test of the Yunnan asynchronous operation, a 0.05 Hz ultra-low-frequency oscillation occurred in the grid. This ultra-low-frequency oscillation is a frequency stability problem caused by instability of hydraulic turbine governing system, which is quite common in the islanded system and very rare in the normal synchronous system. The relationship between the speed governing system stability of one unit and that of the system with parallel operation units was proposed to explain that the high proportion of units with an unstable governing system will lead to system frequency instability and the reduction in loads in the traditional sense was proved to further worsen the frequency stability of the Yunnan asynchronous system. By using related measures, the ultra-low-frequency oscillation of the Yunnan asynchronous system have been curbed effectively. System performance testing verified the effectiveness of the analysis and the measures.

To address the uncertainty of renewable energy sources, the present work employs the reactive power optimization incorporating interval uncertainties (RPOIU) model for the transmission systems. In the RPOIU model, state variables, including load voltages, reactive power generation, and bus angles, are regarded as variables with interval values. Meanwhile, to account for the fluctuation of the load demand and the renewable energy sources in multiple periods of one day, a multi-time RPOIU is proposed. The model seeks to obtain a day-ahead optimal voltage control strategy for ensuring that interval state variables remain within their operating limit constraints in each period of one day, as well for maintaining a low level of daily real power losses. To solve the multi-time RPOIU model, we propose the interval sequential quadratic programming method (ISQPM), which employs a second-order interval Taylor expansion. In addition, an improved interval power flow calculation method i.e., the optimizing-scenarios method, is employed to obtain the accurate ranges of the interval variables, thus improving the convergence performance of the ISQPM. Three cases are tested by simulation to demonstrate the effectiveness, good applicability, and robustness of the proposed method, particularly in comparison to the previously proposed linear approximation method.

This paper utilizes modern statistical and machine learning methodology to predict the oscillation mode of interest in complex power engineering systems. The damping ratio of the electromechanical oscillation mode is formulated as a function of the power of the generators and loads as well as bus voltage magnitudes in the entire power system. The celebrated Lasso algorithm is implemented to solve this high-dimension modeling problem. By the nature of the L1 design, the Lasso algorithm can automatically render a sparse solution, and by eliminating redundant features, it provides desirable prediction power. The resultant model processes a simple structure, and it is easily interpretable. The precision of our sparse modeling framework is demonstrated in the context of an IEEE 50-Generator 145-Bus power network and an online learning framework for the power system oscillation mode prediction is also provided.

Asynchronous interconnected systems connected by High-Voltage Direct Current (HVDC) transmission lines struggle with frequency support between interconnected areas, increasing the risk of frequency instability and resulting in low efficiency in frequency resource utilization. This study establishes a frequency dynamic analysis model for asynchronous interconnected power grids and develops an HVDC frequency controller for frequency control in these systems. It analyzes the control effects of HVDC frequency under two scenarios: without Automatic Generation Control (AGC) and with AGC. The research conducts an in-depth study on the system stability and frequency control parameter optimization for HVDC-asynchronous interconnected systems, significantly improving the system’s response speed and accuracy under various conditions through parameter optimization. Furthermore, the introduction of AGC demonstrates good adaptability, and a comparative analysis of HVDC frequency control effects under different AGC control modes is conducted. Finally, case studies validate the effectiveness and robustness of the proposed optimization scheme for frequency stability control in asynchronous interconnected systems under various fault scenarios.