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In order to cope with the failure of existing fault analysis schemes for AC/DC distribution networks with a high proportion of distributed generations, this paper proposes a fault characteristic analysis method for AC/DC distribution networks that considers the influence of distributed generation control strategies. Firstly, a transient model for the AC/DC distribution network connected to distributed generations is built. Then, the fault characteristics of the AC/DC distribution network in different stages, such as the capacitor discharge stage, inductive renewal stage, and steady state stage, is analyzed. Finally, detailed simulation analysis is conducted using PSCAD/EMTDC to validate the effectiveness of the developed scheme by the superior approximation performance between simulated curves and calculated curves.

Short video hot spot classification is a fundamental method to grasp the focus of consumers and improve the effectiveness of video marketing. The limitations of traditional short text classification are sparse content as well as inconspicuous feature extraction. To solve the problems above, this paper proposes a short video hot spot classification model combining latent dirichlet allocation (LDA) feature fusion and improved bi-directional long short-term memory (BiLSTM), namely the LDA-BiLSTM-self-attention (LBSA) model, to carry out the study of hot spot classification that targets Carya cathayensis walnut short video review data under the TikTok platform. Firstly, the LDA topic model was used to expand the topic features of the Word2Vec word vector, which was then fused and input into the BiLSTM model to learn the text features. Afterwards, the self-attention mechanism was employed to endow different weights to the output information of BiLSTM in accordance with the importance, to enhance the precision of feature extraction and complete the hot spot classification of review data. Experimental results show that the precision of the proposed LBSA model reached 91.52%, which is significantly improved compared with the traditional model in terms of precision and F1 value.

The multi-terminal AC/DC system will become one of the important forms of the future power grid. The negative impedance characteristic caused by the constant power load in the DC network will reduce the power transfer capacity between the terminals, especially when a grid fault occurs in AC system at any terminal. Energy storage has played an important role in improving the stability of AC and DC systems. This paper proposes an additional control method based on an energy storage system to improve system power transfer capacity with low cost. The state space model of two-terminal AC/DC system is established, and the feedback laws for additional control are further designed by Lyapunov theory. Furthermore, the additional control strategies based on the energy storage system is built, without changing the existing control system of each control object. Finally, the corresponding system simulation model is established by Matlab/Simulink for analysis and verification. The research results show that the proposed additional control method is effective. The power transfer limitation can be overcome by only adding small damping energy with the stable DC voltages under large disturbances, and the power transfer capacity between the terminals can be significantly improved with low control cost.