Flexible interconnection transformation of a distribution network using all-control power electronics technology will help to overcome the technical bottleneck of distributed generation (DG) penetration and high-quality power supply in the traditional distribution network. However, the flexible interconnection form that uses back-to-back power electronic converters to replace tie switches has disadvantages such as high cost and large footprint, so its mass promotion and application are bound to be limited. Therefore, a new topology of flexible interconnected distribution network with embedded DC system (FDN+EDC) with a better economy is proposed. Firstly, the topology of FDN+EDC is introduced to improve the controllability level of the distribution network under high percentage DG penetration, and is compared with the conventional flexible interconnection method. Secondly, in order to realize the coordinated optimal economic operation of source, network and load in the FDN+EDC, a dynamic reconfiguration model of switches status and continuous adjustment of flexible interconnection device (FID) are proposed. Then, to achieve a fast and globally optimal solution of the model, a hierarchical coordinated optimization strategy is designed based on an improved particle swarm algorithm for the optimization of discrete and continuous variables. Finally, the validity of the algorithm is verified, and an 88-node FDN+EDC is constructed to verify the advantages of the proposed embedded DC flexible interconnection topology and realize the joint optimal dispatch of network-source-load.

The coal facies and their effects on the coal pore characteristics of the Late Permian Longtan Formation, western Guizhou, were studied, using diverse experiments of macerals and minerals compositions, vitrinite reflectance, and pore characteristics. The results show that five coal facies exist in studied samples, and they are shallow-water covered forest peat swamp facies, moist forest peat swamp facies, dry forest peat swamp facies, low peat swamp facies, and wet land herbaceous peat swamp facies. Among them, the moist forest peat swamp facies accounts for the largest proportion, followed by the shallow-water covered forest peat swamp and dry forest peat swamp facies. The order of pore development degree is identical with the order of moist forest peat swamp facies coal shallow-water covered forest peat swamp facies coal dry forest peat swamp facies coal. In contrast to shallow-water covered forest peat swamp facies and dry forest peat swamp facies samples, moist forest peat swamp facies samples have higher porosity and larger pore size. Coal facies play an important role in controlling the pore structure of coal reservoir, which have more effect on pore size distribution than coal rank for the samples in this study.

Health status assessment is the key link of transformer-condition-based maintenance. The health status assessment method of power transformers mostly adopts the method based on the health index, which has the problems of multiple parameters of each component and strong subjectivity in the selection of weight value, which is easily causes misjudgment. However, the existing online monitoring system for dissolved gas in transformer oil (DGA) can judge the normal or abnormal state of the transformer according to the gas concentration in a monitoring cycle. Still, there are problems, such as fuzzy evaluation results and inaccurate judgment. This paper proposes a dynamic state evaluation method for power transformers based on the Mahalanobis–Taguchi system. First, the oil chromatography online monitoring time series is used to screen key features using the Mahalanobis–Taguchi system to reduce the problem of excessive parameters of each component. Then, a Mahalanobis distance (MD) calculation is introduced to avoid subjectivity in weight selection. The health index (HI) model of a single transformer is built using the MD calculated from all DGA data of a single transformer. Box–Cox transformation and 3 σ criteria determine the alert value and threshold value of all transformer His. Finally, taking two transformers as examples, we verify that the proposed method can reflect the dynamic changes of transformer operation status and give early warning on time, avoiding the subjectivity of parameter and weight selection in the health index, which easily causes misjudgment and other problems and can provide a decision-making basis for transformer condition-based maintenance strategies.

Modular Multilevel Converter (MMC) is widely used in high power motor drive, energy storage and flexible DC power transmission & distribution system, and the parameter identification for sub-module is essentially important for reliable operation of MMC. This paper proposes a digital twins (DT) based method for model construction and parameter identification of the MMC half-bridge sub-module (HBSM). Firstly, the DT model of the HBSM is built, which consists of a simplified MMC sub-module (SM) equivalent model and an arm current simulator based mission profile emulator (MPE). Secondly, a modified particle swarm optimization (MPSO) algorithm is proposed to achieve the online identification of internal parameters in the HBSM, further achieving the real-virtual interaction feedback for real-time sensing of the operation state of the HBSM. Finally, a non-intrusive DT MPE for the HBSM is constructed in MATLAB. The simulation and experimental result shows that the average errors of the actual and model-calculated capacitor voltage values are within 0.1%, and the parameter identification results combined error is less than 1%. The digital twin model established by the proposed method can effectively identify the parameters of MMC sub-modules under different operating conditions.

In this paper, a series hybrid circuit breaker based on a flying capacitor multilevel injector (FCM-SHCB) is proposed for MVDC and LVDC, which utilizes the multilevel characteristic of FCM to realize the fault-current-limitation modulation and extend operation windows for mechanical switch (MS). Meanwhile, by fully exploring the redundant states of the FCM structure, the proposed FCM-SHCB can avoid the high-frequency operation of one single device in conventional S-HCBs, realizing balanced switching operation of the power semiconductor devices and reducing switching frequency without sacrificing the injection performance. The operation principle and parameters design consideration are detailed. A proof-of-concept FCM-SHCB prototype experimentally demonstrates the proposed solution can maintain the high-speed fault-current breaking ability (150V/15A/6μs) while obtaining balanced switching operation (half-reduced switching frequency) and current limiting capability.

In the process of power transformer risk assessment, the loss degree index is difficult to accurately quantify due to the influence of uncertain factors, leading to the deviation of risk judgment. A power transformer risk assessment method based on the three-parameter interval grey number decision-making is proposed. Firstly, the fault probability of the transformer is quantified based on the condition evaluation results. Secondly, considering the uncertainty of DG output and load, the Nataf transform and Cholesky decomposition were used to eliminate the correlation of random variables, and a three-point estimation method combined with a DC cut load model was introduced to calculate the probability distribution of the loss degree caused by the transformer fault. Finally, the origin moment of each order was obtained based on the calculation formula of risk value, and the risk probability distribution was obtained through the Cornish–Fisher series expanding. The decision method of the three-parameter interval grey number distance measure was used to judge the risk grade of the equipment. The results show that the proposed method fully considers the influence of uncertainty on equipment risk judgment, can realize the full use of the equipment risk value interval number to judge the risk, and avoids the decision-making defects of the traditional certain risk quantification method. Meanwhile, the influence of different factors on the risk evaluation results is in line with the actual operation condition of the transformer. The results also verify the effectiveness and accuracy of the proposed method, which provides a new judgment idea for power grid equipment risk quantitative assessment.