最新刊期
卷 49 ， 期 21 ， 2025
- 摘要：The space-air-ground integration (SAGI) technology is a cross-era information and communication technology in the fourth industrial revolution, which has the characteristics of wide coverage, low latency, and high reliability. In view of the paralysis of information and communication systems in modern power systems under extreme events, this paper proposes highly resilient distribution network (SAGI-DN) based on SAGI technology. The structure and technical characteristics of the SAGI-DN are described in detail. The morphological structure and technical characteristics of the SAGI-DN are elaborated in detail. The strategy of power supply restoration for the SAGI-DN is designed. The challenges and key technologies of SAGI-DN are discussed and proposed from the aspects of system planning, information and communications, edge computing, and operation control.关键词：new power system;space-air-ground integration;distribution network;resilience;extreme event;information communication;edge computing0|0|0更新时间：2026-02-28
- 摘要：The connected and automated highway technology has become key technology for improving traffic efficiency and ensuring traffic safety. The connected and automated highway system enables real-time information exchange between vehicles and roadside infrastructure, enhancing the intelligence level of traffic management. However, the reliable operation of the connected and automated highway system depends on continuous and stable power supply. The frequent occurrence of extreme events poses a serious threat to the power supply system of connected and automated highway. In the context of transportation-energy integration, the necessity of resilience enhancement and the vulnerability of the connected and automated highway power supply system in extreme events are firstly analyzed. Secondly, the bidirectional positive feedback between power supply system resilience and the reliability of connected and automated highway system applications is clarified and the cascading failure/recovery effects of the connected and automated highway power supply system in extreme events are elaborated. Then, based on the characteristics of the connected and automated highway system under transportation-energy integration, existing methods for enhancing power system resilience are analyzed and summarized, and pre-disaster prevention, in-disaster mitigation, and post-disaster recovery measures are further proposed for coordinated resilience enhancement of both the power supply system and applications of connected and automated highway system. Finally, from the perspectives of the transportation-power co-simulation of the connected and automated highway, cross-system coordination of diverse and flexible resources as well as the utilization of high-entropy energy in road areas, future resilience enhancement strategies for the power supply system of connected and automated highway are explored.关键词：connected and automated highway;power supply system;extreme event;resilience;transportation-energy integration0|0|0更新时间：2026-02-28
Review·Perspective
- 摘要：Due to the lack of frequency regulation resources caused by the gradual replacement of synchronous units with renewable energy sources such as wind power, providing fast frequency support from wind farms has become an inevitable requirement for ensuring power system frequency security. Timely and accurate assessment of frequency regulation parameters such as equivalent inertia and equivalent droop coefficient of wind farms is the key foundation and prerequisite for dispatch departments to coordinate various frequency regulation sources. However, the frequency regulation capability of wind farms is highly coupled with the real-time operating status of each wind turbine within the farm, having strong time variability and uncertainty. Establishing an evaluation method for equivalent frequency regulation parameters of wind farms that considers the differences in operating status of wind turbines has become a key challenge. The paper considers the uncertainty of micro-wind-speed distribution within the wind farm and constructs an interval assessment method for equivalent frequency regulation parameters of wind farms based on the consistency of response characteristics and micro-wind-speed simulation. Firstly, based on the principle of consistency in key frequency response indicators, a calculation method for equivalent inertia and equivalent droop coefficient of wind farms based on complete wind speed information is established. Secondly, considering the micro-wind-speed uncertainty within the farm in the prediction assessment scenario, a joint distribution model of wind speed for each wind turbine is constructed based on conditional t-Copula. Then, based on wind farm power prediction information, numerous micro-distribution scenarios of wind speed are sampled and generated, the equivalent frequency regulation parameters of the wind farm for each scenario are calculated, and their confidence intervals are statistically derived. Finally, taking a real wind farm as an example, the simulation demonstrates the effectiveness of the proposed method, and the impact of the theoretical power and load reduction reserve power of the wind farm on its equivalent frequency regulation parameters is analyzed.关键词：wind farm;inertia;frequency regulation;frequency response;wind speed;uncertainty;Copula model0|0|0更新时间：2026-02-28
- 摘要：From the perspective of nonlinear dynamics, the effects of the probabilistic characteristics of wind power output and load on the probabilistic practical stability region (PPSR) of a multi-machine power system with doubly-fed induction generators (DFIGs) is analyzed using the bifurcation theory. Firstly, a nonlinear differential-algebraic equation model of the system is established, and the influence of introducing probability parameters on the bifurcation characteristics of the system and the topological properties of the stability region is theoretically demonstrated. In particular, it’s shown that the degenerate Hopf bifurcation (DHB) will occur under specific probability parameters. Secondly, the active power output of the wind farm and the reactive power load are selected as bifurcation parameters to conduct bifurcation analysis of the system and obtain various bifurcation points, thereby partitioning the PPSR of the system. Based on this, considering the probabilistic characteristics, the PPSR under different probabilistic conditions is partitioned. It is found that the DHB caused by probability change will induce the hole effect in the system’s stability region, and the change of probability may also improve the system’s stability margin. Finally, the time-domain simulation method is employed to verify the accuracy of the PPSR partition results. The PPSR can more intuitively evaluate the stability of the wind power grid-connected system and provide reference for the parameter adjustment of the system in practical engineering.关键词：wind power;grid-connected system;doubly-fed induction generator (DFIG);bifurcation theory;probability characteristic;stability region;hole effect0|0|0更新时间：2026-02-28
- 摘要：In order to achieve the problem of service restoration after large-scale power outage in distribution networks under extreme weather of ice and snow, and solve the problem that the existing islanding partition methods have not effectively considered the combination between neighboring islands, this paper proposes a service restoration method for distribution networks under extreme weather of ice and snow considering the islanding partition and combination. First, the factor of conductor current-carrying temperature change is considered in the conductor ice-cover growth rate model for distribution network. The component failure rate model considering the current thermal effect is proposed. Secondly, on the basis of the traditional virtual current model based on the idea of single-commodity flow, the quantitative relationship between the virtual power and the bus state variables and branch state variables among the islanded areas is comprehensively considered, and the constraint relationship between the virtual power flow and the node state variables and branch state variables is determined by combining with the actual operation status of the distribution network. The service restoration model of distribution network considering islanding partition and combination is constructed. Finally, the effectiveness of the proposed method is verified on PG&E69 test system and an actual 185-bus distribution system.关键词：distribution network;extreme weather;thermal effect;islanding partition;service restoration;single-commodity flow0|0|0更新时间：2026-02-28
- 摘要：The direct control of massive dispersed flexible resources by distribution network operators (DGOs) is facing multiple difficulties in communication, computation, and market organization. Oriented to the scenarios of extensive Internet of Things (IOT) connectivity and intelligent control of flexible resources, an optimization model for maximizing the benefits of flexible resources under the guidance of time-of-use price (TOUP) is constructed to give full play to the ability of flexible resources to respond to power grid dispatching. Based on Stackelberg game theory, the Stackelberg game model containing power tracking objective of virtual power plant (VPP) and maximization objective of users benefit is established with TOUP as a link, and the Kriging model is introduced to accelerate the game solving. Simulation results show that the TOUP obtained from the Stackelberg game can not only guide the VPP to reach higher precision in power tracking, but also improve its power quality. This model is suitable for application scenarios with various flexible resource types, weather types, comfort requirements, power tracking objectives, electricity price parameters, etc. Compared with the genetic algorithm and particle swarm optimization, the solution method of the proposed model achieves a speedup of over 10 times.关键词：virtual power plant;flexible resource;power tracking;time-of-use price;Stackelberg game;Kriging model0|0|0更新时间：2026-02-28
- 摘要：To improve the benefit and user satisfaction of virtual power plants in the frequency regulation auxiliary service market, a design method for the frequency regulation package based on graph neural network and Stackelberg game is proposed. Firstly, by comprehensively considering the frequency regulation capacity, participation frequency, and settlement methods, diversified packages that meet the frequency regulation participation characteristics of various users are designed to provide personalized choices for users. Secondly, a graph structure model of users, packages, and frequency regulation attributes is constructed by using the graph neural network to capture the complex relationships between users and packages. The model dynamically updates the features of nodes and edges to predict the package selection results of users. In response to the predicted user package selection results, a bi-level optimization model with multi-parameter Stackelberg game is further introduced. Taking the virtual power plant as the leader and the users as the followers, the optimization of package parameters is conducted with the objective of maximizing their respective benefits of the virtual power plant and users, ultimately achieving a balance and maximization of benefits for both parties. Experimental results show that packages with personalized customization and optimal design, not only enhances the flexibility of user choices, meets personalized needs, and enhances market adaptability, but also improves benefits of users and virtual power plant, achieving a win-win goal.关键词：new power system;virtual power plant;frequency regulation;package;graph neural network;prediction;Stackelberg game0|0|0更新时间：2026-02-28
- 摘要：Steel enterprises have significant potential for energy conservation and emission reduction. However, the steel enterprises often lack enthusiasm in participating in the interaction between power supply and demand in power grid. To address this issue, this paper proposes a collaborative transaction method for the integrated energy system (IES) of steel industrial park in multiple markets, aiming to guide the steel industrial park towards energy conservation and emission reduction and to achieve the economic operation. Firstly, considering the coupling relationships among material flow, energy flow, and carbon flow, an IES architecture for steel industrial park based on the material flow-energy flow-carbon flow coupling is proposed. Secondly, based on the characteristics of operational production processes, energy consumption, and carbon emission, a regulation model for the IES of steel industrial park considering the material flow-energy flow-carbon flow coupling is constructed. Thirdly, in response to time-of-use (TOU) prices and a tiered carbon-green certificate joint trading mechanism, a collaborative transaction model is developed. This model enables the IES of steel industrial park to participate in electricity, carbon, and green certificate markets considering the material flow-energy flow-carbon flow coupling. Finally, a collaborative transaction method for the IES of steel industrial park participating in multiple markets is proposed. Through simulation analysis, the feasibility of the proposed method in achieving energy conservation, emission reduction, and economic operation in steel industrial parks is demonstrated.关键词：steel industrial park;integrated energy system (IES);material flow;energy flow;carbon flow;time-of-use price;carbon trading;green certificate0|0|0更新时间：2026-02-28
- 摘要：Electricity demand can reflect the economic development trends, and the development of upstream and downstream industries leads to the causal relationships between the electricity demands of various industries. Existing industrial electricity consumption prediction lacks the analysis of causal transmission pathways among industries, and the prediction algorithms ignore the coupling relationship between time series and features. This results in issues such as unclear input causal transmission pathways, limited policy relevance, and low prediction accuracy in industrial electricity consumption prediction model. Therefore, this paper proposes a industrial electricity consumption prediction method considering causal transmission pathways in industry development. First, to explore the production relationships among upstream and downstream industries, the greedy equivalence search algorithm is employed to construct a causal essential graph among 47 industries, clarifying the causal transmission pathways among various industries. Then, these causal transmission pathways are used as constraints for the convergent cross-mapping algorithm to adaptively calculate the optimal time lag for causal transmission pathways. Finally, a temporal-feature mixing prediction algorithm is proposed, which sequentially incorporates causal transmission pathways among various industries as inputs to the prediction model to predict the electricity demand across various industries. The applicability and effectiveness of the proposed method are validated using actual electricity consumption data from 47 industries in China.关键词：causal transmission;prediction;industrial electricity consumption;greedy equivalence search;convergent cross-mapping0|0|0更新时间：2026-02-28
- 摘要：With the rapid development of new power system, energy storage technologies such as lithium-ion battery play a crucial role in integrating renewable energy sources with high penetration rates. Rapid and accurate state of health (SOH) estimation of lithium-ion battery helps enhance the safety and reliability of energy storage systems. However, traditional data-driven methods based on correlation analysis suffer from insufficient interpretability and struggle to ensure the accuracy and generalization of battery SOH estimation beyond the training samples. To address this issue, a SOH estimation method for lithium-ion batteries considering causality enhancement and based on bidirectional gated recurrent unit (BiGRU) network is proposed. First, a causality enhancement model for lithium-ion batteries based on causal-observation fusion inference is established. This model constructs multi-temporal nonlinear causality-enhanced features from batteries measurement data to improve the interpretability and in-distribution generalization of SOH estimation. Then, considering the multi-temporal nonlinear causality-enhanced features of the battery, the SOH estimation method for lithium-ion battery based on BiGRU network and invariant risk minimization theory is proposed to enhance the accuracy and out-distribution generalization of SOH estimation. Finally, the proposed method is validated using various actual operational condition data of lithium-ion batteries. Case study results demonstrate that the proposed SOH estimation method for lithium-ion batteries has good interpretability, accuracy, and generalization.关键词：new power system;lithium-ion battery;state of health (SOH);causality;invariant risk minimization;energy storage0|0|0更新时间：2026-02-28
- 摘要：Accurately estimating the state of health (SOH) of lithium-ion batteries is crucial for promoting the development of electric vehicles. However, the complex battery aging mechanism remains a major challenge. Therefore, an SOH estimation model based on hybrid feature extraction and machine learning is proposed. Firstly, based on incremental capacity analysis (ICA) and Spearman correlation analysis, features are extracted from the incremental capacity (IC) curve after sliding average filtering. Secondly, features are extracted from two visual representations of electrochemical impedance spectroscopy, namely Nyquist plot and Bode plot. Then, the k-means clustering method is used to streamline the above features, and an SOH estimation model is established for the CNN-BiGRU-Attention network based on Bayesian optimization. Furthermore, one-dimensional convolution in the network is used to excavate the deep-level information in the original features. And the bi-directional gated recurrent unit (BiGRU) network with multi-head attention mechanism can capture the key information containing battery aging in the input sequence more effectively to estimate SOH of batteries. Finally, experiments are conducted using battery datasets with three different electrode materials to validate the effectiveness of the proposed method.关键词：lithium-ion battery;state of health (SOH);feature extraction;machine learning;incremental capacity analysis;convolutional neural network (CNN);bi-directional gated recurrent unit (BiGRU);multi-head attention mechanism0|0|0更新时间：2026-02-28
- 摘要：The hybrid modular multilevel converter (MMC), which combines the advantages of half-bridge and full-bridge submodules, has significant application values in flexible DC transmission projects. However, the surplus power generated during faults still requires energy dissipation devices for fault ride-through. The energy self-balancing submodule, characterized by low construction costs, compact footprint and multi-modal compatibility, not only achieves energy dissipation but also suppresses capacitor voltage ripple. However, the existing equivalent models in PSCAD and other simulation platforms cannot simulate the newly proposed energy self-balancing half-bridge and full-bridge submodules. Hence, according to the Thevenin equivalent theorem, the equivalent modeling is carried out on energy self-balancing half-bridge and full-bridge submodules starting from their ports. These submodule models are then aggregated to form arm equivalent model, ultimately constructing a hybrid MMC equivalent model. Comparative simulations on PSCAD/EMTDC simulation platforms demonstrate that the equivalent model maintains steady-state and transient errors below 4.2%, with the energy self-balancing branch functioning as designed. Notably, when an 81-level MMC is simulated, the speedup ratio of the proposed model exceeds 1 000 times.关键词：modular multilevel converter;energy dissipation device;flexible DC transmission;overvoltage suppression;equivalent modelling;voltage ripple;energy self-balancing;Thévenin equivalent theorem0|0|0更新时间：2026-02-28
- 摘要：The power flow calculation is the basis for optimal regulation and control of interconnected power grids with multi-terminal DC partition. However, currently, the AC/DC power flow algorithms do not fully consider the coupling characteristics of interconnected power grids with multi-terminal DC partition. They have requirement for large memories and low solution efficiency, and cannot satisfy the requirement for rapid optimal control of interconnected power grids with multi-terminal DC partition. Therefore, this paper proposes an improved power flow algorithm of interconnected power grids with multi-terminal DC partition based on the linear power flow of DC grid. Firstly, the steady-state model and control characteristics of the voltage source converter (VSC) are analyzed. On this basis, the power flow calculation for the AC partition of the power station is performed to obtain the power injected into DC grid by the power station. Secondly, the fast linear power flow calculation of DC grid is carried out to obtain the state information of the point of common coupling (PCC) of the voltage station. Then, the power flow calculation of the AC partition of the voltage station is carried out. The improved power flow algorithm is not needed for AC-DC loop iterations and achieves the AC/DC power flow decoupling calculation. Finally, the theoretical and case analyses demonstrate that the improved algorithm improves computational efficiency while maintaining good convergence and general flexibility. The efficiency of power flow calculation of a small-scale system can be increased by more than 30%. As the scale of the power grid increases, the computational efficiency can be increased by more than 60%.关键词：interconnected power grid;multi-terminal DC partition;voltage source converter;power flow;point of common coupling (PCC);decoupling0|0|0更新时间：2026-02-28
Basic Research
- 摘要：To enhance the capability of the integrated energy system (IES) to support the safe and stable operation of power systems with high proportion of renewable energy and improve their operational efficiency, an uncertainty-aware scheduling method for IES considering the refined modeling of the solid oxide fuel cell (SOFC) is proposed. Firstly, by establishing a two-level day-ahead and intraday scheduling framework to coordinately tackle multiple uncertainties, such as forecasting uncertainties on the source-load sides and cumulative errors of device models. Secondly, at the day-ahead stage, based on the refined model of SOFC, an hourly scheduling plan is formulated to minimize total costs. At the intraday stage, by integrating the model predictive control (MPC) method with the objective of minimizing the total operation costs and adjustment penalty fees, the unbalanced power in the IES is allocated to fast-response devices through feedback correction, thereby promoting renewable energy accommodation. Finally, case studies verify the feasibility and effectiveness of the proposed scheduling method. Compared with other methods, it has advantages in terms of operational costs and model errors.关键词：solid oxide fuel cell (SOFC);integrated energy system (IES);high proportion of renewable energy;uncertainty;model predictive control (MPC);multi-timescale scheduling0|0|0更新时间：2026-02-28
- 摘要：The quay crane load, influenced by container weight and lifting acceleration, exhibits the characteristics of short-duration high-power impacts. Increasing hoisting force to improve the efficiency of quay crane exacerbates power impacts. To address the trade-off between operation efficiency enhancement and power impact mitigation of the quay crane, first, a DC microgrid interconnecting quay cranes and electric container trucks is constructed. On this basis, a model predictive control method for vehicle-crane coordinated efficiency and voltage optimization is developed. By coordinating container lifting acceleration and the energy storage droop coefficient of container trucks, the proposed method improves quay crane operation efficiency and optimizes the DC voltage. Then, a state-space equation integrating bus voltage, quay crane efficiency, and container truck energy storage output in vehicle-crane interconnected system is developed. A weight adaptive calculation method based on the transient recovery process of DC voltage is designed, and a cost function aiming to minimize DC voltage deviation and optimize quay crane operation efficiency is formulated to rapidly suppress the power impacts caused by efficiency enhancement. Finally, RT-LAB hardware-in-the-loop simulation demonstrates that the proposed method effectively improves DC voltage stability and improves the quay crane operation efficiency by 1.7%∼3.0% under different container weights and container truck quantities.关键词：vehicle;quay crane;DC microgrid;model predictive control;power fluctuation;operation efficiency;voltage stability0|0|0更新时间：2026-02-28
- 摘要：Aiming at the problem of poor grid-connected current quality of virtual synchronous generator (VSG) caused by background harmonics of the power grid, this paper proposes a method for suppressing the harmonics of the grid-connected current based on quasi-harmonic voltage drop feedforward. First, by establishing the sequence impedance model of the VSG, the influence mechanism of background harmonics in the power grid on the grid-connected current of the VSG is analyzed. A harmonic suppression method is proposed that requires neither filter design nor complex controllers, whose suppression effect is minimally affected by power grid frequency fluctuations. Then, the actual voltage drop on the grid-side filter inductor is calculated based on the voltage at the point of common coupling and the power grid voltage. Combined with the ideal fundamental voltage drop, the quasi-harmonic voltage drop is obtained. The quasi-harmonic impedance is reshaped by appropriate feedforward with the feedforward factor. Furthermore, based on the small-signal model, the influence of this method on the system stability is analyzed. The correctness and effectiveness of the proposed control method are verified through experiments.关键词：virtual synchronous generator (VSG);sequence impedance modeling;quasi-harmonic voltage drop;feedforward;harmonic suppression;small-signal model;stability0|0|0更新时间：2026-02-28
- 摘要：When a line commutated converter-based high-voltage direct current (LCC-HVDC) system with high proportion of renewable energy feeds into a weak receiving-end power grid, there exists a risk of wide-band oscillation. Thus, it is essential to conduct rapid and effective wide-band impedance measurements on the LCC-HVDC receiving-end system to analyze its operation stability. This paper circumvents the issues such as stability problems associated with intrusive impedance measurement methods. Firstly, based on the non-intrusive impedance measurement model of the LCC-HVDC system established by using the harmonic state space theory, a variable-step index is designed by leveraging the variation in DC transmission power to reflect the system operation state. Secondly, the versoria-like function is employed as the adaptive mother function for variable steps. Through multi-dimensional analysis of the mother function, an adaptive variable step factor is derived to achieve real-time updates of the sampling step, thereby optimizing the computing power of the impedance measurement system. Meanwhile, the indicators such as the data compression ratio and the percentage reduction in computation time are introduced to comparatively analyze the capabilities of the adaptive variable step and the traditional fixed step in quickly and effectively capturing system instability. Finally, the effectiveness of the proposed method in wide-band impedance measurement is verified through a case of the CIGRE standard model.关键词：line commutated converter-based high-voltage direct current (LCC‑HVDC);wide-band oscillation;harmonic state space;wideband impedance measurement;adaptive variable step;versoria-like function;data compression ratio;computation time0|0|0更新时间：2026-02-28
Application Research
- 摘要：On the background of the new power system, conventional faults may lead to large-scale renewable energy fault ride-through and trip-off incidents. The traditional security and stability control system (SSCS) relies on the event-driven feedforward control with relatively coarse measures, which are insufficient for quickly identifying the transient operation conditions of renewable energy sources and optimizing the control measures. This may result in the deviation between the effects of security and stability control and expectations. In the context of the new power system, the formulation and implementation of security and stability control strategies need to consider the uncertainties in the transient process of renewable energy sources, as well as the urgent need for quick perception and precise control of large-scale control objects by security and stability control devices. The autonomous identification technologies for the states of renewable energy units and the generation method of lean control strategies are investigated. The design principles, functional architecture, and technical solution schemes for reliable communication of the SSCS for renewable energy farms and stations that support feedforward-feedback hybrid control are proposed. Furthermore, a complete set of SSCS equipment for renewable energy farms and stations is developed, tested, and verified. The system has been used in the Gansu power grid of China since May 2022 and has achieved large-scale application in the Northwest China power grid, achieving remarkable results.关键词：renewable energy;new power system;security;stability;feedforward;feedback;lean control;fault ride-through0|0|0更新时间：2026-02-28
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