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Fast and accurate self-healing after faults is an important way to improve the reliability of distribution networks. To improve the self-healing speed and accuracy of distribution networks, this paper proposes a fast and accurate self-healing scheme for distribution networks using mixed integer linear programming. Firstly, this method constructs a centralized 5G communication network architecture, which can effectively reduce the communication delay during the self-healing process. Secondly, the principle of logical algebraic transformation is utilized to linearize the switch function in the fault location model, thereby achieving equivalent transformation of the fault location model. Thirdly, using the polyhedral approximation method, the mixed integer second-order cone programming of the power supply recovery model is transformed into a mixed integer linear programming. The proposed method was validated by distribution network systems with different nodes in MATLAB/Simulink, and the results showed that the proposed method significantly improved self-healing speed and accuracy.

Non-intrusive load monitoring is a novel and cost-effective technology for monitoring details of electricity consumption and identifying the operating status of appliances. It supports the construction of the energy internet and big data on electricity consumption in smart cities. However, one of the most challenging problems in this area is that machine learning algorithms often require large amounts of labeled data. In this paper, a non-intrusive load monitoring model based on the Self-supervised Regularization is proposed. The model reduces the pre-processing stage compared to the traditional methods. We make full use of the unlabeled data by using them to generate proxy labels to participate in the model training together with the true labels. We performed experiments on the common data set PLAID to compare performance with the existing method Mean Teacher and CoMatch. The experimental results show that: 1) when using all labeled data, the model with self-supervised regularization significantly improves the traditional supervised classifier with a recognition accuracy of 0.965; 2) when coupled with unlabeled data, our model produces good semi-supervised performance. It is highly competitive with current state-of-the-art Mean Teacher and Contrastive Learning.

In this paper, a W-band single-layer reflectarray antenna is proposed with the advantages of broadband and high aperture efficiency. A novel dual rotation-symmetry windmill element is designed in the W-band, which consists two layers of copper patches printed on a Rogers RT5880 substrate. Based on the analysis of the proposed metasurface element, a square reflectarray with $13.85\lambda _{0}$ (44.2 mm) aperture diameter at 94 GHz center frequency was designed, fabricated and measured. The designed reflectarray antenna shows a 1-dB gain bandwidth of 25.5% (89-113 GHz) in the W-band. Moreover, the measured gain is 31.1 dBi at 94 GHz and the maximum aperture efficiency is 53.4%. The result shows that the proposed design has prospects in wireless communication applications.

The existing continuation power flow (CPF) methods, which mainly focus on regional independent systems, are not suitable for multi-area interconnected bulk systems in the electricity market environment. These existing CPF models cannot simulate the control behaviors of active/reactive power exchange among subsystems, and the corresponding CPF algorithms cannot satisfy the requirements of data sharing. This study presents a novel CPF model and its corresponding distributed algorithm for interconnected systems in which the influence of the electricity market is considered. This CPF method has the following unique features: 1) Regarding the bilateral power trading contracts (BPTCs) among regional subsystems, the nonlinear constraint equations of the directional trading active power via the interface are derived, and a multi-balancing machine strategy is introduced for realizing the active power balance of each subsystem. 2) Based on the simulation of the constant-voltage control behavior of the pilot buses in the regional automatic voltage control (AVC) system, the constant-voltage control behavior of the boundary buses of the tie-lines is further simulated to realize the reactive power balance among the regional subsystems. 3) According to the characteristics of the proposed CPF model, a novel distributed CPF algorithm based on block matrix computations is presented for realizing the decomposition and coordination calculation of multiple regional subsystems. This distributed algorithm preserves the precision and convergence of integrated CPF algorithms and has an advantage in terms of the calculation speed. The performance of the proposed CPF model and distributed algorithm is demonstrated via case studies and comparative analyses.