Data-driven methods using synchrophasor measurements have a broad application prospect in Transient Stability Assessment (TSA). Most previous studies only focused on predicting whether the power system is stable or not after disturbance, which lacked a quantitative analysis of the risk of transient stability. Therefore, this paper proposes a two-stage power system TSA method based on snapshot ensemble long short-term memory (LSTM) network. This method can efficiently build an ensemble model through a single training process, and employ the disturbed trajectory measurements as the inputs, which can realize rapid end-to-end TSA. In the first stage, dynamic hierarchical assessment is carried out through the classifier, so as to screen out credible samples step by step. In the second stage, the regressor is used to predict the transient stability margin of the credible stable samples and the undetermined samples, and combined with the built risk function to realize the risk quantification of transient angle stability. Furthermore, by modifying the loss function of the model, it effectively overcomes sample imbalance and overlapping. The simulation results show that the proposed method can not only accurately predict binary information representing transient stability status of samples, but also reasonably reflect the transient safety risk level of power systems, providing reliable reference for the subsequent control.

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For the high-frequency resonant accident of modular multilevel converter (MMC) in real engineering, in this paper, the 10th order state-space model of MMC is established based on the dynamic phasor method. The state-space model of MMC controller for power control is established according to the practical engineering. Then the time delay of input and output is considered in the controller, and the Pade fitting in state-space model applicable to the eigenvalue method is introduced to the complete state space model of MMC. Based on the proposed model, the MMC high-frequency resonance phenomenon is analyzed by the eigenvalue method, and the accuracy of the model is verified by simulation results. Besides, it is demonstrated that high time delay causes high-frequency resonance in the MMC system based on the participation factor and the system eigenvalue trajectory. Then, the coupling relationship between the input and output time delay inside the controller and the d-q axis time delay is investigated, and a new time delay compensation method to suppress high-frequency resonance is proposed based on Pade fitting, which can be used jointly with the traditional method with good effect.

Interconnectivity is an important development trend of future energy revolution. A more precise planning model is needed to enhance the interaction of multiple energy sources. In this paper, a joint planning model of active distribution network and transportation network including electricity, gas, heat, and traffic loads is proposed. The main highlights of this model are summarized below. Firstly, this issue puts forward a novel mixed user equilibrium mathematical model nesting fast charging station user equilibrium considering the charging fee, charging time, and queuing time of various charging facilities. Secondly, this work constructs a new generation of suburban integrated energy system (SIES) model considering electricity, biogas, gas, and heat energy, and fully explores the significant role of biogas digestors in a SIES. Thirdly, because the proposed model is a mixed integer nonlinear problem, the piecewise linear method, big-M method, and second-order cone relaxation are used to deal with the nonlinear constraints. Finally, a SIES based on the IEEE 33-node distribution network and a 12-node traffic network is designed for case studies. The results revealed that the new equilibrium will decrease vehicle charging cost strongly up to 19.58%. Moreover, biogas digesters are conducive to new energy consumption, resulting in the proportion of power supply from the upper-level grid falling to 30.87%.