Electric power load forecasting used to rely on some key information such as weather or socioeconomic development data. However, it is usually difficult to obtain accurate data on all the contributing factors. A rolling load prediction method based on phase space reconstruction of chaos theory and stacking ensemble learning is proposed. First, we adopted phase space reconstruction method to process the historical load series to avoid collecting some key data. The rolling forecasting method is used to predict a forecast length in advance, and the test data of learning model is obtained by shifting a forecast length of training data. And then we build a stacking ensemble learning model for load forecasting giving full play to the advantage of various algorithms such as Random Forest, Adaptive Boosting, Gradient Boosting Regression, Decision Tree, eXtreme Gradient Boosting and Long Short Term Memory, etc. Finally, the PJM power grid data set of the United States is used to verify the effectiveness of the proposed method, and the performance of the ensemble model is evaluated. Results show that comparing with single model forecasting, the proposed stacking ensemble learning method based on multi model fusion has higher forecasting accuracy.

Under the typhoon disaster, the power grid often has serious accidents caused by falling power towers and breaking lines. It is of great significance to analyze and predict the damage probability of a transmission line-tower system for disaster prevention and reduction. However, some problems existing in current models, such as complicated calculation, few factors, and so on, affect the accuracy of the prediction. Therefore, a damage probability assessment method of a transmission line-tower system under a typhoon disaster is proposed. Firstly, considering the actual wind load and the design wind load, physical models for calculating the damage probability of the transmission line and power tower are established, respectively based on model-driven thought. Then, the damage probability of the transmission line-tower system is obtained, combining the transmission line and power tower damage probability. Secondly, in order to improve prediction accuracy, this paper analyzes the historical sample data containing multiple influencing factors, such as geographic information, meteorological information, and power grid information, and then obtains the correction coefficient based on data-driven thought. Thirdly, the comprehensive damage probability of the transmission line-tower system is calculated considering the results of model-driven and data-driven thought. Ultimately, the proposed method is verified to be effective, taking typhoon ‘Mangkhut’ in 2018 as a case study.

The very fast transient overvoltage (VFTO) is characterized by steep wavefronts, high amplitude, and wide spectrum. These characteristics can lead to partial discharges or insulation breakdowns in potted insulators, which can lead to localized overheating or turn-to-turn insulation damage in transformers. The strong electromagnetic radiation generated by VFTO may also interfere with relay protection and communication systems, triggering risks to grid operation. This paper introduces the existing mainstream VFTO suppression methods, such as damping resistance method, disconnecting switch operation method, inductive method, etc., from the aspects of circuit structure, parameter design and suppression effect, and focuses on the influence of the material selection, parameter adjustment, and mounting structure adjustment of ferrite ring on VFTO suppression effect. In addition, the lightning arrester method and the method of utilizing overhead lines for VFTO suppression are also briefly discussed. The article concludes with a comparison of the advantages and disadvantages of each method and an outlook on the future research direction of VFTO suppression technology.

The interleaved parallel topology of the dc–dc converter can increase the load capacity and reduce the ripple. However, the multiphase control system requires many current sensors, which increases the software/hardware cost. To solve this problem, this article proposes a dual time-scale model predictive control (DMPC) algorithm based on a single current sensor. First, the current estimator replaces current sensors to measure the unbalanced branch currents and reduce hardware complexity. Then, a DMPC algorithm is proposed to reduce the parallel computational complexity of the controller. Furthermore, a parameter identification module dynamically updates the current estimator and controller to further increase the system’s accuracy. This method reduces the software/hardware complexity while ensuring control effectiveness. The validity of the proposed algorithm is verified on a three-phase buck converter.

Dynamic wireless power transfer (DWPT) technology provides a reliable and safe approach for charging electric vehicles. However, the mobility of electric vehicles results in fluctuations in the dynamic coupling coefficient, which can reduce the stability and transmission power of the system. To improve the DWPT system’s dynamic performance, this paper proposes the adaptive tube based model predictive control algorithm (ATMPC) to control the DWPT system. The ATMPC algorithm adds a non-linear autoregressive neural network (NAR)-based tube to a two-layer MPC. The algorithm can dynamically plan the expectation trajectory according to the fluctuation of mutual sensing of the DWPT system and adaptively tighten or loosen the tube for constraints, thus improving the dynamic performance. In addition, the algorithm also deals the hardware environment delay problem by the predictive compensation. Finally, the proposed algorithm is verified on an 85kHz, 1.5-kW DWPT experimental platform.

Very fast transient over voltage (VFTO) is a unique electromagnetic transient phenomenon occurring in Gas Insulated Substation (GIS), which determines the insulation level of the GIS (above 330 kV). Unfortunately, up to the present, there is no standard VFTO waveform to test the high voltage equipment to ensure the safety of power grid. For this reason, this paper focuses on obtaining the standard VFTO waveform through finding a method to fit the curve of VFTO. Hence, a UHV disconnector operation experiment of GIS was carried out on the UHV GIS test platform. The representative waveform of VFTO generated by a single SF6 gas discharge was extracted from the measured data. Furthermore, The Fast Fourier Transformer is applied to analyze the frequency features of VFTO. As one of the switchgear operation voltage, VFTO can be concluded to be a superposition of the power‐frequency waveform with the non‐periodic impulse waveform. Thus, it is found that The Squares Method is convenient for fitting the expression of VFTO according to its transient characteristics. Then the standard VFTO waveform can be obtained from the fitting expression, which coincides well with the measured waveform. The simulation results using ATP‐EMTP software are compared with the calculation results and the measured results.