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最新刊期
卷 46 ， 期 3 ， 2022
- 摘要：Knowledge graph has good knowledge expression ability and interpretability. It is an important branch in the field of artificial intelligence. Its application in power equipment health management can effectively integrate the data of the whole life cycle of equipment and form a new knowledge-oriented operation and maintenance management mode. Firstly, this paper systematically combs the construction methods of open domain knowledge graph, expounds the key technologies and difficult problems in detail, and discusses the construction process of knowledge graph combined with the characteristics of power equipment health management knowledge graph. Then, combined with the existing work, the application scenarios of knowledge graph in power equipment health management are clarified, and the demand for knowledge map technology in the field of health management is analyzed. Finally, the applications of knowledge graph in energy and power equipment health management in the future are prospected.关键词：electric equipment;health management;knowledge graph;deep learning;natural language processing;knowledge reasoning4|1|0更新时间：2025-06-16
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- 摘要：With the increasing penetration of photovoltaic units in microgrids, the uncertainty and time-variability of its power generation have brought challenges to the economic operation of microgrids. When constructing an economic dispatch model, it is necessary to properly simulate the uncertain variables and develop the efficient solving algorithms accordingly. In this context, this paper proposes a deep reinforcement learning algorithm that can effectively account for uncertain factors to solve the problem of optimal operation of microgrids in real time. Firstly, the Markov decision process (MDP) is used to model the optimization operation of microgrids, and the real-time reward function is used to replace the objective functions and constraint conditions, and the interaction with the environment is used to find the optimal strategy. Secondly, the uncertain learning environment is modeled with the help of Bayesian neural networks, and then the stochastic process of state transfer is effectively considered in the MDP. Therefore, a double depth expected Q network algorithm is proposed. By considering the randomness of the state transfer, the Q iteration rules of the general deep Q network algorithm are optimized to significantly improve the convergence speed of the algorithm. Finally, a case is used to verify the effectiveness of the proposed model and algorithm.关键词：photovoltaic generation;uncertainty modeling;deep reinforcement learning;Bayesian neural network;double deep expected Q network3|1|0更新时间：2025-06-16
- 摘要：A prediction method for the operation status of charging stations based on spatio-temporal characteristics and the deep learning model is proposed. Firstly, based on the historical operation data of charging stations and the traffic speed data set in the area, the k-means clustering method is used to classify the charging stations into different types and the temporal characteristics of the operation status of charging stations are analyzed. The “offset-traffic-time” three-dimensional matrix model of individual charging stations is established to deeply explore the coupling correlation between the operation status of charging stations and the surrounding traffic conditions in time and space. Secondly, the spatial reconstruction of the time-lagged correlation between charging station status and traffic conditions is carried out, the feature extraction is carried out by convolutional neural network, and the time series prediction is carried out by long short-term memory network, so as to build a multi-step prediction model of charging station operation status based on Keras deep learning framework. Finally, the proposed method is validated with the data of 20 charging stations and compared with various prediction algorithms, and the results show that the proposed method has high prediction accuracy.关键词：charging station;operation status;traffic condition;multi-step prediction;Keras deep learning framework3|1|0更新时间：2025-06-16
- 摘要：The diversity and dispersion of resources at demand side make it difficult to extend the response model of small-scale demonstration projects to large-scale customer groups. This paper intends to complete the generalized modeling of demand response characteristics and its large-scale potential deduction based on small samples of demand response data. Firstly, the distributionally robust fuzzy set of response random parameters is constructed. Secondly, based on the principal component analysis method, the relationship between the power consumption of small sample users and inflection point of dead zone and saturation zone of their response is mined. The combination of commonness and individuality is used to obtain the key parameters of general user response in the process of large-scale generalization, and finally the deduction of large-scale demand response potential based on the small sample data is realized. Numerical examples show that the proposed quantification method of the demand response potential fully considers the randomness of user response, and better describes the common characteristics of the industry and the individual characteristics of users. On one hand, the research results can support the accurate modeling of demand response characteristics of small sample users within the scope of the demonstration project. On the other hand, it can support the deduction and evaluation of response ability of large-scale customer groups in future scenarios.关键词：distributionally robust optimization;principal component analysis method;demand response;potential deduction3|0|0更新时间：2025-06-16
- 摘要：Aiming at the problem of the wrong phase relationship in the topology of low-voltage distribution station areas, by using the similarity between the phase voltage sequence on the low-voltage side of the distribution transformer in the station area and the user voltage sequence, this paper proposes a phase identification method for single-phase users based on the adaptive piecewise cloud model. First, the digital features of the cloud model are used to describe the data distribution of the voltage sequence. Then, the adaptive piecewise cloud model algorithm is used to adaptively determine the total number of segments of the voltage sequence and the start time and end time of each segment. Finally, the similarity of the piecewise cloud model of the voltage sequence is calculated to determine the phase connection relationship between the users and the distribution transformers in the station area. This method is not affected by the topology and load changes of the station area, and is universal. Aiming at the situation that the three-phase voltage of the distribution transformers in the station area is very close, compared with the existing similarity algorithms, the proposed method has better discrimination and higher accuracy in the phase identification results. Numerical simulation and case analysis verify the effectiveness of the proposed method. This work is supported by National Natural Science Foundation of China (No. 51677060) and Hunan Provincial Natural Science Foundation of China (No. 2019JJ60012).关键词：low-voltage distribution network;low-voltage topology identification;phase identification;cloud model;adaptive segmentation;voltage similarity analysis;household-transformer relationship3|4|0更新时间：2025-06-16
- 摘要：In view of the insufficient adjustment of the phase sequence in station area based on historical load modeling and the inability to guarantee the duration of the power supply state after phase sequence adjustment, from the data-driven perspective, an on-line optimization method for the phase sequence in station areas based on improved support vector machine for ultra-short-term load forecasting is proposed. First, the variational mode decomposition is used to decompose the historical load of the forecasting object into multiple sub-sequences, and an improved support vector machine is used to forecast each sub-sequence. An adaptive weight mechanism is introduced in the forecasting model to improve the performance of least squares support vector machines, which can filter the impact of data noise on the results and improve the forecasting accuracy. Then, a multi-objective optimization model for the load branch of the intelligent commutation switch is established with the smallest three-phase unbalance, the smallest number of commutations, and the longest phase sequence duration. A set of satisfactory solutions is selected from the Pareto optimal solution set solved by the non-dominated sorting genetic algorithm-Ⅲ as the automatic phase sequence adjustment scheme for decision-makers. Finally, a certain station area in Guangdong power grid of China is used as an example to analyze and compared with other methods to verify the effectiveness of the proposed method.关键词：data-driven;support vector machine;load forecasting;genetic algorithm;phase sequence3|0|0更新时间：2025-06-16
- 摘要：Typhoon and torrential rain disasters occur frequently in coastal areas, which is highly possible to cause accidents such as tower falling and line disconnection of transmission lines. Therefore, an evaluation method of tower falling and line disconnection accidents considering typhoon and torrential rain disasters is proposed for 110 kV transmission lines. Firstly, load models in typhoon and torrential rain are established respectively to describe the wind and rain loads at any position in the typhoon wind field. The finite element models for the different transmission tower types of 110 kV lines are established respectively. Considering the correlation of wind and rain loads, the dynamic response of lines and towers with wind and rain loads is analyzed. Based on the structural reliability theory, the probability expressions of tower falling and line disconnection are derived, the mechanism effects of different tower types, purposes and wind angles on tower falling are studied, the weak links of power grid are analyzed, and the tower falling and line disconnection accidents of 110 kV lines in typhoon and torrential rain disasters are evaluated. Finally, the simulation uses the actual power system and real typhoon data in a region of China to verify the applicability of the proposed assessment method.关键词：typhoon;torrential rain;tower falling;transmission lines line disconnection;reliability evaluation3|1|0更新时间：2025-06-16
- 摘要：The large-scale centralized development of renewable energy in regional areas will cause serious renewable energy abandonment problems. The configuration of a certain scale of energy storage devices can significantly reduce the abandonment. Based on time-series production simulation software and probabilistic statistical analysis methods, this paper studies the energy storage capacity allocation problem in partial sections considering the uncertainty of the renewable energy and the abandonment rate constraints. First, the algorithm framework of the mainstream time-series production simulation software is introduced; based on this software, considering the uncertainty of renewable energy output, the abandonment curve of partial area sections can be obtained. Then, considering the limit of the abandonment rate, the initial configuration scale can be determined by constant power method, the cumulative probability statistical analysis on the length of the abandonment duration time is performed to obtain the best duration time for the energy storage; and the optimal energy storage configuration scale that meets the abandonment rate constraint is obtained. Finally, a calculation analysis is carried out on the actual power grid of a province in Northwest China, and a sensitivity analysis is carried out on the scale of energy storage configuration, the proportion of renewable energy installed capacity and the utilization rate of the renewable energy, which verifies the convenience of the proposed method in solving problems.关键词：renewable energy;configuration of energy storage capacity;time-series production simulation;probability statistics;energy storage duration time;abandonment rate3|0|0更新时间：2025-06-16
- 摘要：Accurate wind speed simulation is a fundamental and important step in the study of wind-integrated generation systems. Hence, this paper proposes a wind speed simulation model based on mutual conversion based Ornstein-Uhlenbeck process, which is capable of producing simulated wind speed samples with any given time step. Consolidating such model into the sequential Monte Carlo simulation method, an adequacy assessment method for wind-integrated generation systems with variable simulation time steps is developed. Then, the measured wind speed samples from an observatory are used to verify the proposed model. The results indicate that the simulated wind speed samples with variable simulation time steps in the proposed model share similar probability distribution characteristics and autocorrelation characteristics with those of measured wind speed samples. The adequacy assessment method is applied to assess the adequacy of the wind-integrated IEEE-RTS generation system. The results indicate that the loss of load frequency presents higher sensitivity to the simulation time step than those of loss of load expectation and loss of energy expectation. A wide simulation time step will lead to the considerable underestimation for the loss of load frequency. Richer wind resources can further magnify the adequacy benefit of the wind farm integration.关键词：wind speed simulation;adequacy assessment;probability distribution of wind speed;Ornstein-Uhlenbeck process;simulation time step3|0|0更新时间：2025-06-16
- 摘要：Aiming at the problem that the modular multilevel converter (MMC) using traditional vector control is prone to system operation instability when a single-phase short circuit occurs in the power grid, this paper proposes a simple and stable passivity-consensus based control method from the perspective of system energy. The first goal is to track the desired trajectories of positive sequence currents and suppress negative sequence currents rapidly. The model of port-controlled Hamiltonian with dissipation for MMC is established, and the “reactive force” which does not affect the global energy dissipation is obtained. Thus, the design of the passivity-based controller can be simplified and the global energy is minimized at the desired equilibrium point. The global asymptotic stability of the closed-loop control system is guaranteed. The second goal is to improve the tracking synchronousness of the desired trajectories of positive and negative sequence currents in the dq coordinate system. The desired trajectory tracking errors of grid-connected currents between neighboring phases are introduced into the passivity-based control law as the state errors, and the consensus-based control method is integrated with the passivity-based method properly, to realize the synchronization of desired trajectories tracking of positive and negative sequence currents in the dq coordinate system. The simulation results based on MATLAB/Simulink show that the proposed method has good dynamic and static performance, global stability and strong robustness when the single-phase short-circuit fault of the power grid occurs simultaneously with DC-side voltage step change, active power change and MMC parameter perturbation, respectively.关键词：unbalanced power grid;modular multilevel converter (MMC);port-controlled Hamiltonian model with dissipation;passivity-based control;consensus-based control3|1|0更新时间：2025-06-16
- 摘要：Recently, coherency equivalence method has been widely used in the dynamic equivalence of large-scale systems, and the obtained reduced-order model can accurately reflect the dynamic response of the system. Among them, the slow coherency algorithm as a representative has the advantages of being insensitive to the location and severity of the fault. However, due to model limitations and poor accuracy, traditional slow coherency algorithms are difficult to apply to the distributed generation network. To this end, a slow coherency and aggregation method applicable to the droop-controlled grid-connected inverter networks is proposed. Based on the singular perturbation theory, a slow coherency model is established and the influence of damping is analyzed to solve the applicability problem of droop-controlled inverter networks. Meanwhile, the fuzzy C-means spatial clustering algorithm is used in the space vector of the modal matrix to achieve the purpose of accurately identifying the coherent power sources. Finally, a reduced-order model is established by using the aggregation method, and the simulation results of 10 parallel inverters verify the effectiveness of the proposed method.关键词：slow coherency algorithm;aggregation method;reduced-order model;dynamic equivalence;singular perturbation theory4|2|0更新时间：2025-06-16
- 摘要：High-frequency electrical data is one of the data bases to improve the accuracy of situation awareness, monitoring level and auxiliary service quality of power grids . However, the traditional reconstruction algorithm is difficult to achieve the high-precision data reconstruction. Therefore, this paper uses the improved generative adversarial network to reconstruct the low-frequency electrical data into the high-frequency ones. By transforming the time series data into electrical images, the efficient extraction of electrical image features by neural network method is realized. The generator based on deep residual network and improved residual block structure are used to improve the feature learning ability of the generator. In addition, the generator loss function considers the difference in low- or high-dimensional features between real samples and generated samples. The public data set is taken as an example to verify the algorithm. The verification results show that compared with the traditional reconstruction methods, the proposed method has higher peak signal-to-noise ratio, structural similarity, lower mean absolute error and mean absolute percentage error, as well as the higher high-frequency detail reproduction and reconstruction accuracy, and can be generalized for different data sets.关键词：frequency-increased reconstruction;low-frequency electrical data;generative adversarial network;deep residual network;image feature;data-driven3|0|0更新时间：2025-06-16
Basic Research
- 摘要：With the integration of high proportion of power electronic equipment and renewable energy, the future power system needs time-domain protection to deal with the complex fault characteristics of the system. System-level fault transient analysis is of great significance as the research basis of time-domain protection. In view of the controlled characteristics of inverter-interfaced generator (IIG), system-level fault transient analysis needs to deal with two challenges: dynamic phase conversion of output current of generation units and solving of high-order multi-generation system equations. A transient analysis method of system-level fault based on transient current back-substitution of IIG is proposed in this paper. By analyzing the dynamic relationship between the output power of generation unit and the terminal voltage phase, the dynamic phase conversion of IIG transient current to unified reference system is realized. The system equation is modified transiently to avoid high-order operation. On this basis, the transient voltage of the network nodes can be solved linearly by the transient current of each generation unit, and the time-domain accurate solution for the transient currents at the fault point and the whole network can be obtained. Simulation results show that the proposed method can achieve more accurate system-level fault transient analysis.关键词：fault transient analysis;high proportion of renewable energy;inverter-interfaced generator (IIG);transient current back-substitution;dynamic phase conversion3|1|0更新时间：2025-06-16
- 摘要：Due to the dynamic interaction between converters, the design of control parameters of medium-voltage DC (MVDC) distribution systems is much more complicated than that of single converter. First, for the current control loop, the voltage control loop and droop control loop of the converters in the system, the open-loop and closed-loop transfer functions considering the dynamic interaction between the converters are established respectively. In addition, the number of poles (or zeros) of the transfer function considering the dynamic interaction between converters is consistent with the single-converter situation. Then, a control parameter design method for the MVDC distribution system considering the dynamic interaction between converters is proposed. In this design method, the control parameters of all converters are designed qualitatively and quantitatively from the perspective of system dynamic stability. Through the mutual cancellation of some zeros and poles, the dynamic characteristics of the system can be designed by this method with a pair of conjugate poles. Moreover, this design method is effective in a wide oscillation frequency range (for example 10~50 Hz). Finally, the proposed transfer function and control parameter design method are simulated and verified in the power electronics simulation software PLECS.关键词：medium-voltage DC distribution system;dynamic interaction;control parameter design;open-loop transfer function;closed-loop transfer function3|0|0更新时间：2025-06-16
- 摘要：Aiming at the problem that the traveling wave protection of the flexible DC grid line can not take into account the operation speed and the ability to withstand the transition resistance under the long-line fault, a two-section traveling wave protection scheme based on the positive and negative difference of voltage refractive wave amplitude is proposed. First, by analyzing the propagation process of the fault traveling wave on the transmission line, the expressions of each refractive wave are derived, and the positive and negative difference characteristics of the refractive wave amplitude of the line port voltage under the condition of internal and external faults are obtained. Then, based on these characteristics, a two-section traveling wave protection scheme is proposed, in which the first section is composed of traditional traveling wave protection criterion, and the second section is based on the port voltage amplitude and recovery time. Finally, based on the PSCAD/EMTDC simulation platform, the effectiveness of the protection scheme is verified.关键词：flexible DC grid;two-section traveling wave protection;refractive wave;operation speed;transition resistance3|1|18更新时间：2025-06-16
- 摘要：Due to the effect of the arc suppression coil and the grounding impedance, the electrical quantity of the high-impedance grounding fault in the resonant grounded system is relatively weak, which makes fault detection and line selection difficult. Through the analysis of the transient and steady state characteristics of high-impedance faults and the instantaneous and permanent changes of the fault line to the ground branch, the rules and characteristics of the instantaneous change of line-to-ground capacitance parameters of the normal line and the fault line are summarized. Furthermore, this paper constructs the virtual energy component that characterizes the change of line-to-ground capacitance parameters of each line before and after the fault, and analyzes the change law of change rate of virtual energy. Finally, the criterion of using the peak ratio of the virtual energy change rate of the line to determine the fault line is proposed and used in the design of the fault line selection method. The method not only ensures the correct line selection, but also improves the detection range and the ability to resist three-phase imbalance interference. Simulation results and field measured data verify the accuracy and reliability of this method.关键词：resonant grounded system;high-impedance grounding fault;line-to-ground capacitance parameter;change rate of virtual energy;fault line selection3|0|0更新时间：2025-06-16
- 摘要：In order to improve the ability of line commutated converter based high voltage direct current(LCC-HVDC) system to resist commutation failures and improve the dynamic characteristics of the LCC-HVDC system during the fault period, this paper proposes a compound line commutation converter (LCC) topology based on thyristor-type full bridge sub-modules (T-FBSMs). The compensation of commutation voltage and the suppression of DC current rise can be realized by switching the control modes of T-FBSM during the fault, which improves the commutation failure immunity. Then, the coordinated control strategy of the T-FBSM and the converter valve is studied, and the electrical parameters of T-FBSM are designed. Finally, different simulation cases are set in the PSCAD simulation environment to verify the voltage and current stress and the commutation failure suppression effect of the proposed topology. The simulation results show that the proposed coordinated control strategy of the compound LCC topology and the designed electrical parameters of T-FBSM are rational and effective, and the proposed topology can effectively reduce the commutation failure probability and improve the recovery characteristics of the system.关键词：line commutation converter (LCC);commutation failure;auxiliary commutation topology;commutation voltage compensation;fault current suppression;thyristor-based full bridge sub-module (T-FBSM)3|1|0更新时间：2025-06-16
- 摘要：Advanced firing control is an important method to reduce the probability of commutation failure in high voltage direct curren (HVDC) transmission systems. Accurate advanced firing is the key to mitigate commutation failure. According to the theory of commutation voltage-time area, a commutation failure mitigation method based on commutation voltage-time area prediction is proposed. This method not only takes into account the change of DC current after fault, but also indirectly takes into account the change of commutation angle and equivalent commutation reactance after fault through the measurement of commutation area. At the same time, this method has clear physical meaning and does not need to improve the commutation failure mitigation performance through complex parameter tuning. Finally, taking the CIGRE standard model in PSCAD/EMTDC as the test model, the effectiveness of the proposed method is verified under different faults.关键词：high voltage direct current (HVDC) transmission;commutation failure;commutation failure mitigation;commutation angle;advanced firing control3|1|12更新时间：2025-06-16
- 摘要：Currently, the parity-time (PT) symmetric mode of magnetic coupling wireless power transfer (MC-WPT) systems is not fully understood in terms of physical principles, parameter conditions and the difference from common operating modes. Aiming at this problem, the PT-symmetric MC-WPT systems is modeled and analyzed based on the vibrational theory. It is demonstrated that the PT-symmetric mode is essentially a real eigenstate mode, and the general parameter conditions of the real eigenstate mode are derived. From the perspective of real eigenstate, the physical principles of the PT-symmetric systems based on the operational amplifier and the inverter are compared and analyzed. It is proved that the PT-symmetric system based on the operational amplifier is a self-excited oscillation system with the self-selected frequency characteristic. While the PT-symmetric system based on the inverter is essentially a forced response system and the operating frequency is given by the inverter. On this basis, the PT-symmetric system is compared with several common operating modes of the MC-WPT system, including the zero phase angle mode, magnetic resonance mode proposed by Massachusetts Institute of Technology (MIT) of USA and complex eigenstate mode. The characteristics, advantages and disadvantages of each operating mode are obtained.关键词：wireless power transfer;magnetic coupling;real eigenstate;parity-time (PT) symmetry;self-excited oscillation;energy efficiency characteristic3|1|0更新时间：2025-06-16
- 摘要：In order to enhance the ability of the deep residual shrinkage network to learn the features of transformer faults and improve the accuracy of fault identification, the fault feature gas vector with an improved deep residual shrinkage network is constructed to identify transformer faults. First, a variable soft threshold function is constructed to eliminate the effects of constant deviations, and the fast back tracking algorithm is used to speed up the threshold determination and ensure the integrity of the output results. Then, a cross-entropy function with variable weights is proposed to reduce the effects of misrecognition on the network accuracy. The constructed feature gas vector is used as the input to ensure that the network learns and recognizes the features of more fault factors. Finally, taking overheating faults and arcing faults as samples, the experimental results verify the effectiveness of the method. Compared with the traditional method, the recognition accuracy of the proposed method is higher, and it is suitable for the identification of multi-feature faults in the power system.关键词：transformer;deep residual shrinkage network;fault identification;feature gas3|0|0更新时间：2025-06-16
Application Research
- 摘要：In the context of carbon neutrality and emission peak, the power system with high penetration of renewable energy will become one important development trend of future power system. In addition, extreme weather events occur with high variability and frequency. Power systems, in consequence, have more and more uncertainties, that have great impacts on economical, safe and stable system operation. It is necessary to analyze these impacts and the corresponding measures based on the stochastic characteristics. From the perspectives of stochastic variables and system equations, the power system stochastic problems are divided into three categories of stochastic steady state problem, stochastic dynamic problem and stochastic event problem. The description and analysis methods are presented for these three types of problems, respectively. For the power system stochastic steady state problem, the system stochastic steady state analysis method is presented from the perspective of stochastic feature analysis and stochastic decision problem. For the power system stochastic dynamic problem, the impacts of stochastics on dynamics from oscillation, security, and stability are reviewed and discussed. For the power system stochastic event problem, a survey on probabilistic analysis and Markov analysis is performed. Finally, the future trend of probabilistic forecasting for renewables, system stochastic planning and operation, anti-disturbance capability with low inertia, stochastic dynamics, and impacts of extreme weather on renewables are discussed.关键词：power system;stochastic event;steady state;dynamic state5|0|0更新时间：2025-06-16
Review
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