The increase of wind power permeability in modern power grid has turned rapid and accurate transient stability (TS) prediction into a more challenging issue. To accurately and promptly perform online TS prediction for power system with doubly fed induction generator (DFIG)-based wind farms, an integrated model-driven and data-driven method is proposed in this paper. The influence of DFIGs is considered in the transformation to guarantee the accuracy of the equivalent one machine infinite bus (OMIB) model transformed from the target system. The P-δ trajectory of the OMIB is fitted with the generator-terminal information to predict TS. To improve the prediction speed, an extreme learning machine (ELM)-based method is utilized to process the other DFIG and system information and evaluate the system status immediately after failure. The simulation results verify that the proposed method can reduce the dependence of the data-driven method on the data sample size and improve the speed and accuracy of online prediction.

With the rapid development of ICT technology and automation control technology, the distribution network has gradually transformed into a distribution network cyber-physical system (distribution network CPS) with highly coupled information and physical systems. The information system supports the stable operation of the physical system but also brings about certain security risks to the distribution network CPS. Therefore, information impact should be considered in the original anticipated physical fault assessment. This paper proposes a security analysis and evaluation method for distribution network CPS considering anticipated combined information-physical fault screening. First, based on the CPS structure of the distribution network, a CPS correlation matrix model of the distribution network that can reflect the power-information coupling characteristics is established. Then, we analyze the correlation between information failure and physical failure, and we construct an initial anticipated combined information-physical-fault set according to topology and service correlations. Next, based on the fault recovery rate ordering, the key anticipated combined information-physical fault is selected. Finally, for the selected combination of anticipated failures, an assessment of the distribution network CPS security assessment indicators is carried out and verified via example.

Wind power plants (WPPs) are required to provide primary frequency regulation services when a high proportion of wind power is connected to the grid. The reserve power of wind turbine generators (WTGs), including rotor kinetic energy and deloading power, is determined by its current rotor speed and active power, thus, different frequency regulation levels of WTGs will be formed because of the variable wind speed and the wake effect in a WPP. This article proposes an adaptive frequency control strategy considering releasable reserve power that can enhance the frequency regulation capacity in the permanent magnet synchronous generator (PMSG)-based WPP. The inertial control gains of frequency controller for PMSGs are adjusted adaptively, resting with the releasable kinetic energy, which is a function of current rotor speed. Moreover, primary frequency control gains are adjusted adaptively, resting with the releasable deloading power, which is a function of the current active power, thus, a PMSG operating at a higher rotor speed and active power can release more rotor kinetic energy and deloading power to provide greater frequency regulation capability. The proposed adaptive frequency control strategy is tested using a PSCAD/EMTDC simulator. The simulation analysis indicates that the reserve power of PMSGs in WPP can be utilized effectively while ensuring their stable operation. Meanwhile, the frequency regulation capability would be further enhanced.

With the continuous increase of renewable energy, the power system will face the problem of insufficient frequency response capability. Electric vehicles (EVs) combine the characteristics of mobile energy storage and controllable loads and can provide capacity support in frequency control. However, as a distributed frequency regulation resource, there is inevitably a communication delay in the process of electric vehicles participating in frequency regulation, which will affect the stability of the system frequency. Therefore, this paper proposes a frequency regulation delay compensation control strategy based on model predictive control (MPC). Firstly, the model predictive control is utilized to design an electric vehicle frequency response model controller and establish a frequency regulation model of the power system containing electric vehicles; then, by establishing the selection rules of the control signal, the multi-step control signal is dynamically adjusted during the rolling optimization of the predictive model to form a delay compensation mechanism considering delay and packet loss; finally, multi-scenario simulation is conducted, and the results show that the proposed strategy can roll-optimize the auxiliary frequency regulation function of electric vehicles, significantly reduce the influence of communication time delay, and improve the system frequency stability.

The traditional black-box Thevenin equivalent method cannot analyze the influence mechanism of wind power integration on Thevenin equivalent parameters. With the increase in wind power penetration, it will be difficult to accurately assess the voltage stability of power systems with wind power. Therefore, a Thevenin equivalent analytical method is proposed to analyze the voltage stability of a power system with wind power. This method adopts the equivalent model of wind power integration based on the current source model. It establishes the Thevenin equivalent analytical model for power systems with wind power by dividing the node types. Then, the analytical expressions of the Thevenin equivalent parameters are derived based on two equivalent modes to characterize the mechanism of wind power integration on the Thevenin equivalent parameters. In addition, the calculation flow chart of the voltage stability criterion is formulated based on the analytical value of the Thevenin equivalent impedance under different load growth ratios and wind power penetrations. Finally, a case study is conducted on the improved IEEE 39 node system with wind power. The results demonstrate the feasibility and effectiveness of the proposed Thevenin equivalent analytical method, which can more accurately judge the voltage stability of the power system with wind power.