With the power industry moving toward a green and low-carbon direction, renewable energy is occupying an increasingly larger share in the power system. However, compared with traditional thermal power generation, the instability of new energy generation is very prominent, which also leads to a decrease in the inertia of the power system after the grid integration of a high proportion of renewable energy. If no measures are taken, this may lead to frequency collapse accidents. Therefore, this paper first introduces two international major power outage accidents that have occurred in recent years, analyzing the causes, and then summarizes the inspiration obtained from the accidents. Subsequently, some research results on low inertia-related issues in the power system caused by the high proportion of new energy grid integration in recent years were summarized and analyzed from three aspects: inertia evaluation methods, optimal operation measures for the power system, and under frequency load-shedding (the abbreviation “ULFS” in the following text stands for it) schemes. Finally, suggestions were made for future research directions.
With the development of power-electronics technology, PWM rectifiers are widely used in many fields. They are especially suitable for high-precision- and high-efficiency-application scenarios, such as communication and industrial control. Although it has many advantages, overshoot control during startup is a challenge. Therefore, this paper first derives the input–output mathematical model through equation establishment and dq-coordinate transformation. Next, a voltage and current double closed-loop simulation model is established in MATLAB/Simulink, and its control effect is analyzed. On this basis, a new voltage-setting strategy is designed to reduce the output-voltage overshoot of the PWM rectifier when starting. The simulation results demonstrate that the strategy has a good application effect and can contain starting-voltage overshooting from 12.88% to 0.925%. Moreover, the principle of this strategy is simpler and easier to understand and implement compared with traditional strategies.
To enhance the operational dependability of renewable energy power systems with high proportions, this study proposes a multi-timescale optimization strategy based on the inertia evaluation model. Firstly, the inertia evaluation model is established based on the factors influencing the inertia demand of the power system, and the concept of the inertia margin coefficient is introduced. Secondly, to address the uncertainties associated with sustainable energy output and the cost of carbon emissions, a multi-timescale optimization operation model is formulated for day-ahead, intraday, and real-time operations, aimed at economic optimization. The output status of each unit is obtained and adjusted in a timely manner in the next stage, while meeting the system’s inertia demand, to derive the final scheduling strategy. Lastly, a sensitivity analysis of the inertia margin coefficient is conducted through simulations to validate the effectiveness and cost-efficiency of the proposed scheduling strategy.
High penetration of renewable energy sources complicates static voltage stability assessment, as conventional line-based indices are typically derived under restrictive assumptions, such as neglecting voltage-angle differences or decoupling active and reactive power effects, which may lead to inaccurate proximity signals under RES-rich operating conditions. The proposed research study develops an enhanced voltage stability index (EVSI) from a two-port π line model that explicitly retains line impedance, active and reactive power terms, and voltage-angle difference between the sending and receiving ends; secure system operation satisfies EVSI < 1. Unlike classical indices, EVSI preserves the coupled physical interactions most relevant to voltage collapse while maintaining a closed-form structure suitable for online monitoring. EVSI is evaluated in a coupled transmission–distribution setting with solar photovoltaic-based distributed generation under varying penetration levels and loadings, using PV-curve nose points as collapse references, and benchmarked against classical indices. Across scenarios, EVSI remains closest to unity at the nose point, accurately tracing the collapse boundary and consistently identifying weak buses, whereas the traditional indices exhibit dispersed values and sensitivity to operating assumptions. The proposed results indicate that EVSI offers a reliable and computationally convenient indicator for online assessment and early warning of voltage instability in renewable-integrated, coupled transmission–distribution networks.