More than half of the defects caused by metal particle discharge in the oil chamber of high-voltage on-load tap-changer seriously affect long-term operational reliability. The movement law of metal particles in insulating oil during the disconnection process of on-load tap-changers and its impact on the dielectric properties of insulating oil are investigated, which can provide a theoretical basis for the diagnosis of insulation status of on-load tap-changers and the design of oil gap insulation margin. Firstly, theoretical analyses of fluid field, metal particle dynamics, and electric field are presented, and the coupling relationship among the three is explained. At the same time, a two-dimensional simplified simulation model of the on-load tap-changer contact is established, and the distribution of eddy currents in the fluid field, the movement law of metal particles, and the movement trajectory of charged metal particles are obtained. The simulation results show that during the on-load tap-changer movement, the particle concentration at the center of the on-load tap-changer gap is the highest, and a "small bridge" is formed. The influence of changes in metal particle concentration distribution on the dielectric properties of insulating oil is calculated using the dielectric constant and conductivity models of the mixture. A method of calculating according to concentration zones and then paralleling is proposed to improve the accuracy of dielectric parameter calculation.

The research and development of eco-friendly electrical insulation materials is a fundamental issue and development trend in the power industry, among which the research on eco-friendly insulation oil for power transformers is one of the important directions. The research history, latest progress, and future development trends of environmentally friendly insulation oils for power transformers are reviewed. Firstly, the research and development history of three main types of transformer oils are reviewed which are: mineral oil, natural esters and synthetic esters are reviewed. The conventional performance indicators and theoretical evaluation methods of insulation oils are analyzed. Next, the research status of key characteristics such as insulation, aging and heat dissipation of transformer oil are analyzed, as well as common modification technologies for insulation oil at present. Finally, the current status of quantum chemical calculations applied to the design of insulating oil molecules is analyzed, and it is proposed to establish the structure-activity relationship between the macroscopic properties and microscopic parameters of insulating oil through quantum chemical calculations, thereby the research and development efficiency of environmentally friendly insulating oil is improved.

The widespread utilization of power cables leads to an increased demand for capacitive reactive power balance in the power system. Additionally, the integration of a high proportion of renewable energy sources has introduced challenges related to reactive power fluctuations. Existing solutions for reactive power compensation and generation occupy substantial space and come with significant costs. An innovative approach is introduced, which combines magnetically controlled reactors with transformers to create a compact multifunctional single-stage magnetic valve type stereoscopic magnetically controlled transformer（SSS-MCT）. This novel solution not only retains the fundamental voltage regulation capabilities of traditional power transformers but also offers flexible reactive power adjustment. This design is particularly advantageous for urban substations with limited space availability. Finite element simulations are conducted to validate the performance of the SSS-MCT. The results show that this SSS-MCT can provide a reactive power regulation capacity of up to 94.5 kvar, with a maximum turns ratio offset of only 0.439%. Furthermore, it exhibits a harmonics content of merely 3.8%. This innovative solution offers 20% reduction in footprint, shows outstanding overall performance and the capability effectively meets the reactive power compensation requirements of the urban distribution grid.

Electric field information is the foundation of intelligent perception and deep integration of information in the new power system. Electric field measurement needs to take into account many performance requirements such as no distortion, micro-broad eband, strong stability and easy integration. In response to the demand for digital development of the new power system, the sources of electric field measurement errors caused by ground wire intrusion are analyzed. A micro-broadband AC electric field sensor design scheme and an electric field distortion-free measurement method are proposed. The design of a distortion-free electric field sensor is carried out, and the distortion-free measurement effect is compared with microelectro mechanical systems （MEMS）and optical electric field sensors. The results show that when the MEMS electric field sensor is offset 2 cm upwards from the center of the gap, the electric field measurement error is 13.2%, and the electric field measurement error of the optical electric field sensor is about 3%. The measurement error of the undistorted electric field sensor is around 2%, and it does not increase or decrease with the offset distance of the sensor, achieving the isolation effect of ground wire interference, and the degree of undistorted electric field is better than that of optical electric field sensors.

False data injection attack seriously endanger the safety and stability of the power grid operations. Due to the high dimension and complex characteristics of the electricity measurement data, the attack locational detection accuracies of the existing methods are insufficient. For this reason, a false data injection attack locational detection method based on relevant features multi-label cascade boosting forest is proposed to locate the attacked position of the power grid. The proposed method enhances the fitting ability of the multi-label cascade forest processing the complex electricity measurement data by incorporating the extreme gradient boosting algorithm, so as to identify the abnormal state variables of each bus. Furthermore, the "relevant features" algorithm is integrated to extract the highly informative features from the original electricity measurement data to improve the generalization ability of the multi-label cascade forest, so as to obtain more accurate location detection. The simulation results on IEEE 14-bus and IEEE 57-bus test systems verify the effectiveness of the proposed method, and compared with many other methods, the proposed method has better accuracy, precision, sensitivity and F1-score.

Under the "Dual Carbon" target, the hybrid pumped storage power station combining conventional hydropower with pumped storage functions is a new trend in hydropower generation. Developing rational scheduling strategies is a key challenge for hybrid pumped storage adaptation to the electricity market. Therefore, a multi-transaction operation mode suitable for hybrid pumped storage power station is proposed, and an internal collaborative control method for the station is proposed based on the characteristics of conventional hydropower and pumped-storage. The conventional hydropower part implements the peak-valley price mechanism, while the pumped storage part implements the two-part tariff mechanism, allowing the station to retain capacity price and participate in the spot market clearing. Based on this operating mode and regulation method, a bi-level optimization scheduling model is proposed to maximize power station profits and social welfare. Finally, the effectiveness of the proposed model is verified through case studies, and the results show that the proposed model is conducive to achieving the rational utilization of hydropower resources. Compared with different single transaction operation modes, the profit of power station increases by at least 1.2%.

The risks of frequency instability and power imbalance in new power systems have been raised due to the features of high-penetration power electronics and renewable energy sources (RES). To reduce these risks, it is necessary to consider the constraints of frequency security and adequacy in system operation dispatch. However, the two type constraints will significantly increase the computational complexity of the model, making it difficult to solve high accuracy during operation scale. A frequency and adequacy constrained unit commitment (FACUC) is proposed. Firstly, a system frequency response model and an adequacy evaluation model considering operational constraints are established. And the constraints of frequency security and adequacy are constructed in FACUC. Then a decomposition optimization algorithm is proposed to solve the proposed optimization model, which decomposes the original problem into a main problem of mixed integer linear programming (MILP), a simulation-based subproblem for frequency evaluation and an optimization-based subproblem for adequacy evaluation. Finally, the FACUC is solved by iterating among the main problem and subproblems. The example cases based on the modified IEEE 39-bus system are analyzed. The results show that the proposed FACUC model can effectively improve the frequency stability and adequacy of the system while ensuring economic efficiency.

Considering the impact of time-of-use electricity pricing and charging utilization characteristics on the load of electric vehicle charging stations, a short-term load forecasting method is proposed for large scale electric vehicle charging stations that integrates long short-term memory and support vector regression (LSTM-SVR). Firstly, a feature matrix is constructed that includes factors influencing the charging load such as time-of-use electricity pricing, charging utilization rates, meteorological information, and historical data on charging load power. Secondly, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method is applied to decompose sequences of the feature matrix containing time-of-use electricity pricing and charging utilization rates, which enhances data diversity. This process also employs a combined correlation coefficient method for data reduction and feature selection. Subsequently, the northern goshawk optimization (NGO) algorithm is used to optimize the hyperparameters of both LSTM and SVR, solving for weight coefficients and constructing the integrated LSTM-SVR model. Finally, the model is validated using data from a large scale charging station in a specific city. Comparative experiments demonstrate that considering time-of-use electricity pricing and charging utilization features can effectively improve the accuracy of electric vehicle charging station load forecasting by over 8%. Moreover, the proposed LSTM-SVR forecasting method further enhances prediction accuracy.

As the penetration rate of electric vehicles(EV) in the urban power system gradually increases, the system's ability to support electric vehicles needs to be further improved. Combined with the urban power distribution system to configure a new type of centralized charging and swapping facilities is an effective way to solve the problem, and reasonable and effective optimization of the planning is a major difficulty. In response to the question, a comprehensive planning model considering the sizing and locating of the electric vehicles’ charging-swapping- storage integrated station (CSSIS) is proposed, as well as path optimization of the cable power supply. Based on the analysis of the functional characteristics of charging and swapping facilities, the operation models and sizing models of charging station, swapping station and energy storage station are established respectively. Based on this, the integrated operation model and sizing and locating model of CSSIS is established. Meanwhile, combined with the probability distribution characteristics of EVs in the planning area, the EV load of the CSSIS is analyzed. Considering the requirements of different types of loads on power supply reliability and the types of cable power supply corridors, an optimization method of cable power supply path combined with the layout of CSSIS is proposed. Based on the free cash flow theory analysis for the firm, the cumulative net present value of the planning of the EV’s CSSIS is optimized. Meanwhile, the cable power supply path and its supporting cable corridor are optimized. The model is solved by YALMIP/CPLEX optimization toolbox. Taking a certain area as the planning area, the feasibility and effectiveness of the method proposed are verified, which provides new ideas and references for the optimization planning of electric vehicle integrated stations and their supporting urban cable distribution systems.

The virtual synchronous generator section of a grid-forming converter is the most important factor affecting its frequency dynamics, but the frequency of the internal voltage within a grid-forming converter does not only include the frequency of the virtual synchronous generator. To address this point of view, a research approach is proposed to characterize the effect of voltage control in influencing the frequency dynamics of grid-forming converter. Firstly, analogous to the frequency analysis method of the synchronous generator, the concept of the internal voltage of the grid-forming converter is proposed, and the frequency of the converter are characterized by the frequency of the internal voltage. Then the effect of the AC voltage control on the frequency dynamics in response to the active power perturbation within the electromechanical time scale is analyzed through the method of the motion equation modeling, and the influence trends of the voltage control parameter on the active power and the frequency response capability of the grid-forming converter are analyzed. It is found that larger voltage control proportional and integration parameters deteriorate the system frequency dynamics, but the response performance of the converter is mainly determined by the virtual synchronous generator. The simulations in MATLAB/Simulink with a 3-machine 9-node system and a real-world regional grid system verify the effectiveness of the method respectively.

Construction of energy storage systems for new power system is an effective means to improve the accommodation of distributed renewable energy and the quality of power supply. The existing research on energy storage planning doesn’t fully utilize the available information from actual distribution automation system, and the configuration results are difficult to apply to actual power grids. Arming at this problem, an optimal allocation method of energy storage based on electric common information model （CIM/e） is proposed. Firstly, the praising approach for CIM/XML data is proposed to realize topology identification and reconstruction of the power flow model for actual distribution network. Secondly, an energy storage optimization configuration model is established, which considers economic and power quality indexes and embedded power flow constraints. This model realizes the integrated design for system operation and planning, providing the optimization of energy storage location and capacity. Finally, two practical power distribution systems with two different voltage levels in southern China are simulated to verify the effectiveness of the proposed method.

To solve the problem that feeder-consumer connectivity is difficult to be efficiently identified and accurately checked due to the monotonous and large-scale measurement data, a method of identifying feeder-consumer connectivity in low-voltage distribution network based on multivariate data feature is proposed. Firstly, the correlation of outage equipment is analyzed, and the abnormal data preprocessing method based on fuzzy C-means algorithm, threshold division and Neville interpolation is proposed for smart meter sampling anomalies. Secondly, a clustering method of smart meters based on outage correlation and Hausdroff distance is proposed. Thirdly, based on Kirchhoff's current law, a quadratic programming model for the identification of feeder-consumer connectivity is established, which is effectively solved by a solver after transformation. Finally, the effectiveness and superiority of the proposed identification method of feeder-consumer connectivity are verified by a practical example.

With the challenges posed by high penetration of distributed photovoltaic integration into low-voltage distribution networks, such as substation reverse overload, voltage violations, and three-phase imbalances, a multi-stage evaluation method for assessing the maximum available capacity of distribution substations considering high proportions of distributed resources is proposed. Firstly, the inverse peak load time-series characteristics of distributed PV and load are analyzed, considering constraints related to reverse overload and voltage violations caused by PV over-generation, as well as the impact of three-phase imbalance on the substation transformer's load capacity. A robust optimization model for substation demand response to enhance distribution transformer load capacity is proposed. Secondly, considering phase selection configuration of distributed photovoltaics, coordinated charging of electric vehicles, as well as the demand response of flexible loads, a multi-stage collaborative evaluation model is proposed for determining the maximum available capacity of distribution substations under high proportions of distributed photovoltaic and electric vehicle integration. This model incorporates phase selection configuration optimization, virtual capacity expansion, and verification and correction stages. Finally, on the basis of nested column and constraint generation algorithm（N-C&CG）, the model is transformed into three sub-problems: photovoltaic phase selection configuration optimization, demand response of flexible resources, and capacity verification at the upstream substation, which are solved interactively. Through comparative analysis based on simulations of typical distribution substations, the proposed method demonstrates a 9.84% improvement in the available capacity of the distribution substations, providing technical support for optimized connection schemes and reliable operation in the expansion of distribution networks.