最新刊期
卷 50 ， 期 21 ， 2026
- 摘要：Against the background of coordinated advancement of the rural revitalization and the carbon emission peaking and carbon neutrality strategies, clarifying the diversified development pathways for rural distributed energy systems and overcoming the bottlenecks in their comprehensive utilization technologies are crucial for promoting the green and low-carbon transition of rural energy systems and supporting the sustainable development of the rural economy. To review the research progress and development pathways of rural distributed energy systems, this paper conducts a comprehensive overview of the current research status in China. First, from a regional perspective, it analyzes the resource endowments and energy demand characteristics of rural distributed energy systems in China, systematically reviews the application status of various types of distributed energy systems and multi-energy complementary systems, and summarizes the common issues in their technological application. Second, it analyzes comprehensive utilization and energy efficiency enhancement technologies from three perspectives such as collaborative optimization of multi-energy complementary systems, digital support and intelligent regulation, and implementation pathways with supporting mechanisms. Finally, based on this analysis, it proposes a phased development pathway and offers targeted recommendations for future development across three dimensions: technology, institution, and market.关键词：rural distributed energy system;development pathways;comprehensive utilization;multi-energy complementary system;energy efficiency enhancement7|21|0更新时间：2026-11-04
Review·Perspective
- 摘要：With the increasing installed capacity of renewable energy and the rising proportion of DC feed-in year by year, the frequency stability issue of the receiving-end power grid has become increasingly severe. The grid-forming voltage source converter based high-voltage direct current (VSC-HVDC) system can provide frequency support for the power grid and enhance system frequency stability. Considering the frequency support characteristics of grid-forming VSC-HVDC, DC system parameters and frequency response characteristics of the AC power grid, a system frequency response model incorporating the support characteristics of the VSC-HVDC system is established. The impacts of major system parameters and control parameters on the frequency regulation characteristics are analyzed. A frequency support strategy based on linear active disturbance rejection control (LADRC) is proposed to improve the adaptability of grid-forming control, and a parameter tuning analysis method is provided. Finally, a grid-forming VSC-HVDC transmission system in Gobi Desert and other arid areas is built on the PSCAD/EMTDC simulation platform. The system frequency model considering the frequency support characteristics can accurately depict the frequency response. The proposed control strategy can significantly reduce frequency deviations and enhance the system frequency support capability and adaptability.关键词：Gobi Desert and other arid areas;renewable energy base;grid-forming control;voltage source converter based high-voltage direct current (VSC-HVDC);frequency response;frequency support;virtual synchronous generator;active disturbance rejection control8|6|0更新时间：2026-11-04
- 摘要：With the increasing penetration of renewable energy in new power systems, the inertia level of power grids has been continuously decreasing, and the problems of system frequency and oscillation have become increasingly serious. To address the above issues, this paper designs a supercapacitor-based inertia emulation control strategy by combining the power equations of the supercapacitor with the grid-forming matching control equations of the photovoltaic system. This strategy enhances system equivalent inertia without modifying the inherent grid-forming control architecture of the photovoltaic inverter. Furthermore, the equivalent torque method is employed to establish a stability analysis model, which clarifies the mechanisms of the influence of the DC-link voltage synchronization loop and the supercapacitor control loop on system stability. It reveals the mechanism of supercapacitor control suppressing low-frequency oscillations by enhancing damping torque in the low-frequency range, providing a theoretical foundation for control design. Finally, the proposed inertia analysis and emulation strategy is validated on the Typhoon hardware-in-the-loop test platform. The results show that the proposed strategy can effectively improve the inertia level and operational stability of the grid-forming photovoltaic inverter.关键词：renewable energy;photovoltaic inverter;grid-forming control;inertia;low-frequency oscillation;supercapacitor;stability;torque22|5|0更新时间：2026-11-04
- 摘要：With the continuous increase in the installed capacity of renewable energy integrated through grid-following converters, the inertia and voltage strength of local power grids have significantly declined, necessitating the deployment of grid-forming energy storage systems to provide grid support. Therefore, local power grids are transitioning to hybrid renewable energy systems that combine grid-following and grid-forming converters. Unlike conventional synchronous generators, the synchronous torque and damping coefficients of these grid-following and grid-forming converters are nonlinear, which complicates the synchronization process and hinders the transient stability analysis in multi-converter systems. To this end, based on the motion equations of power-angle coupling, a third-order transient synchronization equation characterizing frequency and power-angle difference of a two-machine system is established to describe the dynamic process of grid-following/grid-forming hybrid systems under islanded operation. When the hybrid system operates in off-grid mode, load changes can cause steady-state frequency deviations of the system. However, when the positive and negative signs of the frequency deviation are different, the damping effect of the converters is opposite, resulting in differences in transient stability characteristics. To illustrate the influence mechanism of damping coefficients on transient stability, a customized phase-plane diagram is developed to visualize the transient damping energy, providing an intuitive and physical interpretation of the damping effect. On this basis, an adaptive damping enhancement strategy is proposed to adjust the damping coefficient adaptively, thereby further enhancing the system transient stability. Finally, simulation results validate the correctness of the transient stability analysis and effectiveness of the proposed control strategy.关键词：grid-forming converter;grid-following converter;damping;frequency deviation;renewable energy system;transient stability7|2|0更新时间：2026-11-04
- 摘要：With the expansion of grid-forming (GFM) converter grid-connected scale, the interactions among multiple GFM converters tend to induce low-frequency oscillations. If additional control loops are introduced to or parameters are optimized for all GFM converters to suppress low-frequency oscillations, the complexity of control parameter design will increase significantly. To address this issue, this paper proposes a participation-factor-based identification method for critical GFM converters and a corresponding low-frequency oscillation suppression strategy. Only a small number of critical converters need to be controled to improve system stability. Specifically, starting from the Rayleigh quotient, this paper proves that the participation factors of the GFM converter multi-machine system exhibit a concentrated distribution characteristic. That is, large participation factor values appear only at a few GFM converter nodes, while the values at other nodes are nearly zero. Accordingly, the few converters with high participation factors are defined as critical converters, and targeted oscillation suppression is implemented on them. Studies show that selectively introducing additional control loops or optimizing control parameters for only a small set of critical converters can markedly improve the small-signal stability margin of the system. Finally, simulation cases are adopted to verify the effectiveness of the proposed strategy.关键词：grid-forming converter;multi-machine system;participation factor;small-signal stability;low-frequency oscillation11|1|0更新时间：2026-11-04
- 摘要：Due to the high degree of power electronicization and the complexity of power grid characteristics in new power systems, wide-band oscillation issues exist when renewable energy is connected to the power grid. This paper focuses on the dominant subsynchronous oscillation mode of the grid-forming converter in a hybrid grid-connected system with grid-following and grid-forming converters. First, a small-signal model of the heterogeneous hybrid grid-connected system is established. The eigenvalue method and the participation factor method are used to analyze the impact of the grid-following phase-locked loop (PLL) on the subsynchronous oscillation mode of the grid-forming converter. Then, based on the classic Phillips-Heffron framework, an equivalent single-machine linearization model of the grid-forming converter is established. The coupling influence of the reactive power loop is fully considered during the modeling process. The complex torque coefficient method is used to reveal the negative damping effect introduced by the PLL in the subsynchronous frequency band and its causes, providing a mechanistic explanation for the subsynchronous oscillation characteristics. Furthermore, the influence law of the PLL control parameter on the subsynchronous oscillation is obtained by combining modal analysis. To address the negative damping effect of the PLL, a phase-lead compensation link is proposed to counteract the phase lag introduced by the input torque of the PLL, thereby suppressing its adverse effect on subsynchronous oscillation in the grid-forming converter. Finally, the correctness of the theoretical analysis and the effectiveness of the improvement strategy are verified through simulation and experiments.关键词：grid-following converter;grid-forming converter;phase-locked loop (PLL);hybrid grid-connected system;small-signal model;subsynchronous oscillation;negative damping;phase-lead compensation20|2|0更新时间：2026-11-04
- 摘要：With the large-scale penetration of distributed generators and the significant extension of transmission distance, the grid strength of the new power system exhibits wide-range fluctuations from the extremely weak grid (the short-circuit ratio is 1) to the extremely strong grid (the short-circuit ratio is 40). This poses severe challenges to the stability of grid-connected converters. The grid-following converter is prone to the negative impedance effect in the weak grid, resulting in distorted output waveforms. The grid-forming converter has tight power coupling with the strong power grid, which is prone to power oscillation. To address these issues, this paper proposes a grid-following and grid-forming dual-natured grid-connected converter, which can simulate the external characteristics of the parallel system of grid-following and grid-forming converters with a single grid-connected converter. The internal mechanism of the wide-range power grid strength adaptability of the grid-following and grid-forming dual-natured grid-connected converter is analyzed based on the impedance characteristic curves. Furthermore, an adaptive selection method for the proportion coefficient is proposed based on the stability region. Finally, the effectiveness and the stability of the proposed control strategy are verified through the RT-LAB hardware-in-the-loop platform. Analysis demonstrates that the grid-following and grid-forming dual-natured grid-connected converter has excellent active support characteristics and wide-range power grid strength adaptability, providing a simple, flexible, cost-effective, and grid-friendly solution for improving the stability of the grid-connected system with large fluctuations in power grid strength.关键词：renewable energy grid-connection;power grid strength;stability region;small-signal stability;grid-forming converter;grid-following converter;hybrid control15|1|0更新时间：2026-11-04
- 摘要：With the rapid development of renewable energy, the pace of new power system construction is gradually accelerating, and the installed capacity of traditional grid-following renewable energy is constantly increasing. Due to the lack of active grid-supporting power sources such as traditional synchronous generators, the stability of the power grid is becoming increasingly prominent. In order to solve a series of problems caused by weak grids, developing grid-forming renewable energy with active grid-supporting capability has become an important solution. In response to the short-circuit test of the grid-forming photovoltaic under large disturbances, a detailed test plan evaluation is conducted, and the data of grid-connected short-circuit and islanded short-circuit tests are compared. Based on the advanced digital power system simulator (ADPSS), the errors between electromechanical-electromagnetic hybrid simulated and field-measured values are analyzed. The test achieves the expected goals and effects, verifying that the grid-forming photovoltaic system has the grid-forming characteristics, system construction and stable support capability during faults. At the same time, a quantitative comparison of the support capability of the grid-forming photovoltaic system and the grid-following photovoltaic system is made. Finally, the next step of work expectations for the grid-forming equipment is given.关键词：renewable energy;large disturbance;grid-forming photovoltaic;grid-connected short-circuit test;islanded short-circuit test;stability;support capability6|1|0更新时间：2026-11-04
Grid-forming Technology
- 摘要：As the construction of new power systems accelerates, the scale of power grids continues to expand, and the uncertainty and complexity of system operation modes become increasingly prominent. When applied to large-scale power grids, traditional numerical iterative power flow solution methods face the dual challenges of convergence difficulty and insufficient computational efficiency. Artificial intelligence for science (AI4S) technology provides a new technical route for data-driven power flow algorithms. However, the existing graph neural network (GNN) methods rely on local neighborhood aggregation, making it difficult to effectively capture the impact of electrical coupling between distant nodes on power allocation and voltage distribution, which limits their application benefit in large-scale power grid analysis and computation. To address these issues, this paper proposes a power flow calculation method that integrates a GNN with Transformer. A random walk positional encoding is introduced to enhance the perception capability of nodal topological positions, and a self-attention mechanism is employed to achieve efficient interaction of global node information. The model performance is further optimized by incorporating physical constraints of power flow equations, a power-mean loss function, and a data augmentation strategy. Experimental results in multiple scenarios demonstrate that the proposed method has advantages in computational accuracy, speed, and transfer generalization, and its engineering effectiveness is verified in a certain provincial grid.关键词：new power system;power flow calculation;graph neural network (GNN);artificial intelligence for science (AI4S);Transformer;self-attention mechanism;random walk positional encoding16|1|0更新时间：2026-11-04
- 摘要：The widespread integration of distributed resources in distribution networks exhibits significant spatiotemporal coupling characteristics, which substantially increases the modeling and computational complexity of the optimal power flow (OPF) problem for distribution networks. This paper proposes a closed-form iterative solution algorithm for the OPF problem, which approaches the optimum by iteratively computing a series of closed-form solutions. Each iteration requires only a single matrix multiplication operation without invoking any optimization solver. A central processing unit (CPU) plus graphics processing unit (GPU) computing paradigm for the OPF problem is presented, in which the CPU transforms diverse practical power grid models into graph computing models, and the GPU is then employed to perform efficient computation. The proposed method is implemented using a general message-passing mechanism provided by an open-source platform, making it compatible with mainstream high-performance computing frameworks and ensuring its easy deployment and scalability. Finally, a distribution network case study with a high proportion of distributed resources is constructed and simulated. Simulation results demonstrate that, compared with solver-based methods, the proposed method significantly improves computational efficiency while maintaining result accuracy.关键词：distribution network;distributed resources;optimal power flow (OPF);closed-form iterative solution;graph computing;graphics processing unit (GPU);general message-passing mechanism;alternating direction method of multipliers17|21|0更新时间：2026-11-04
- 摘要：Green power trading is an important means to promote green and low-carbon energy transition. The current electricity market in China generally adopts the sequential separate-platform clearing mode of green power-conventional power or electric energy-environmental attributes, which makes it difficult to maximize the overall social welfare of conventional power and green power trading, resulting in unsatisfactory market resource allocation. Therefore, a unified-platform market clearing method of green power and conventional power for optimal overall social welfare is proposed. Firstly, the green power trading is decomposed into two types of commodities, i.e., electric energy and environmental attributes. A market clearing mode of green power and conventional power is also constructed, in which the two types of commodities are declared separately and compete on a unified platform. Secondly, a unified-platform market clearing model of green power and conventional power, which takes the optimal overall social welfare of electric energy and environmental attributes as its objective and covers supply-demand balance and mutual coupling constraints of the two types of commodities, is constructed, and the advantages of this model over the sequential separate-platform clearing model are analyzed. Then, the pricing and settlement mechanism for the unified-platform market clearing of green power and conventional power is proposed, which can realize the scientific decomposition of green power price. It is theoretically proven that this mechanism satisfies the cost-recovery property for market participants. Finally, case studies verify that the proposed method can effectively improve the overall social welfare and reasonably decompose the total green power price into electric energy price and environmental price.关键词：green power;conventional power;social welfare;market clearing;pricing mechanism13|1|0更新时间：2026-11-04
- 摘要：In the background of the rapid development of new power systems and electricity markets, resource aggregators are playing an important role as electricity market participants. One of the key challenges for aggregators lies in making coordinated trading decisions across wholesale electricity procurement and retail electricity sales. However, conventional mathematical programming methods depend heavily on accurate models and are prone to the curse of dimensionality, resulting in high computational complexity. Meanwhile, the data-driven machine learning models suffer from poor interpretability and heavy dependence on training data, which renders existing methods unable to balance decision transparency and environmental adaptability effectively. Therefore, this paper proposes a coordinated trading decision-making method for aggregators in the wholesale and retail electricity markets based on large language models (LLMs). The proposed method leverages chain-of-thought (CoT) and theory-of-mind (ToM) modeling based reasoning mechanisms to realize the integrated utilization of structured market data and unstructured external information, thereby improving the applicability of the trading decision-making model in the dynamic market trading environments. Verification results of simulation cases show that the proposed method outperforms both conservative and aggressive trading strategies in terms of electricity market adaptability and aggregator trading revenues in multiple scenarios.关键词：new power system;electricity market;resource aggregator;large language model (LLM);trading decision-making model;chain-of-thought(COT);theory-of-mind(TOM)15|2|0更新时间：2026-11-04
- 摘要：To address challenges including load uncertainty and complex geographic information faced in the siting and sizing planning of urban integrated energy stations, this paper proposes a two-layer robust planning method based on multi-agent safe reinforcement learning. Firstly, a two-layer planning framework for the siting and sizing of urban integrated energy stations is constructed. At the upper level, based on the location set-covering model, the spatio-temporal characteristics of multi-energy loads and geographic information system data are integrated to optimize the siting strategy of urban integrated energy stations with the objectives of optimal economy and coverage efficiency. At the lower level, considering the multi-stage construction sequence, the multi-stage sizing and operation strategies of equipment are optimized to minimize the full-life-cycle cost. Secondly, a multi-agent safe proximal policy optimization algorithm is proposed to tackle complex high-dimensional uncertainty problems in the planning process. By introducing a value constraint network, the proposed algorithm guides the optimization policy into the safe feasible region. The augmented Lagrangian method is adopted to transform the constrained optimization problem into an unconstrained one, where agents adaptively learn robust optimization policies in uncertain environments. Finally, numerical cases are carried out based on a real-world city. Simulation results demonstrate that the proposed model and algorithm outperform conventional methods in terms of economic performance, computational efficiency, and robustness against long‑term load-growth uncertainty, and can provide effective decision-making support for urban energy system planning.关键词：integrated energy station;siting and sizing;robust planning;geographic information system;multi-agent;deep reinforcement learning;augmented Lagrangian method;uncertainty12|1|0更新时间：2026-11-04
- 摘要：With the deepening implementation of the “East Data, West Computing” strategy, the rapid growth of data center construction scale requires more refined siting planning. This paper addresses the decision-dependent uncertainty (DDU) in siting and computing power of data center planning, and proposes a two-stage robust optimization method for interconnected data centers. First, a decision-dependent budget uncertainty set is constructed to dynamically quantify the endogenous coupling between data center siting decisions and fluctuations in computing power demand. Then, based on the decision-dependent uncertainty set, a two-stage robust mixed-integer programming model that accounts for DDU is established for interconnected data centers, incorporating multi-dimensional cost components including land, equipment, electricity, and carbon emission. Finally, to overcome the inability of the conventional column-and-constraint generation (CCG) algorithm to handle DDU, an improved Benders&CCG algorithm is custom-designed to rapidly and accurately solve the DDU problem in interconnected data center planning. Case results show that, compared with the conventional decision-independent uncertainty method, the proposed method reduces the total cost by 4.73% while still guaranteeing computing power demand in extreme scenarios. Sensitivity analysis further verifies the strong adaptability of the proposed model to demand fluctuations. This study provides a decision-making tool that balances economic efficiency and robustness for the planning of interconnected data centers, which are characterized by high capital intensity and long planning horizons, and can further support the coordinated development of the goals of carbon emission peaking and carbon neutrality and the digital economy.关键词：data center;computing power;siting;mixed-integer programming model;decision-dependent uncertainty (DDU);robust optimization14|3|0更新时间：2026-11-04
- 摘要：With the integration of electric vehicles (EVs) into the power grid, large-scale EVs exhibit great potential for participating in grid dispatch. To accurately assess the potential of EVs in grid dispatch, a probabilistic assessment method for dispatchable potential of EVs based on user charging behavior profiles is proposed. First, multi-dimensional user profile labels are constructed according to charging behaviors, vehicle attributes and users’ subjective psychological effects. A classification decision model is adopted to categorize users into different clusters to establish individually differentiated behavior profiles. Second, for each individual user, EV energy probability feasible regions and dispatchable power models at different confidence levels are constructed. An improved zonotope approximation method considering time and energy values in different time periods is put forward to conduct inner approximation of the EV energy probability feasible region. Finally, for different EV clusters generated from user profile results, the Minkowski sum method is used to aggregate the approximated EV energy probability feasible regions. The dispatchable power of each EV within the cluster at different confidence levels is aggregated to yield the corresponding cluster dispatchable power, so as to probabilistically assess the dispatchable potential of different clusters.关键词：electric vehicle (EV);charging;user profile;probabilistic assessment;feasible region;cluster;dispatchable power22|1|0更新时间：2026-11-04
- 摘要：The high penetration of renewable energy and the intensifying variability of meteorological conditions have led to severe fluctuations in power load, making it difficult for traditional models to capture the deep-level features within load sequences. Time-series foundation models, leveraging transferable knowledge acquired through pre-training, are capable of effectively capturing the complex patterns in load sequences. However, foundation models still have limitations in utilizing covariate information. To further improve load forecasting accuracy, this paper proposes a paradigm that deeply integrates foundation models with covariate information. First, a time-series foundation model is fine-tuned using load data, transferring its knowledge to the field of power load forecasting. Then, a general exogenous feature embedding module is designed, which can be flexibly integrated with any foundation model to compensate for the insufficiency of foundation models in utilizing external information. Finally, the effectiveness of the proposed method is verified based on actual load data from a power grid and data from the Global Energy Forecasting Competition.关键词：load forecasting;time-series foundation model;large language model;covariate;knowledge transfer;artificial intelligence7|1|0更新时间：2026-11-04
- 摘要：Harmonics cause the distortion of commutation voltage waveforms, thereby reducing the commutation margin of the converter valves, which is an important inducement of commutation failure in high voltage direct current (HVDC) transmission systems. Existing commutation failure suppression methods considering the influence of harmonics mainly rely on the fast Fourier transform (FFT) for harmonic analysis. However, during the transient process caused by AC faults, the FFT suffers from limited calculation accuracy under non-stationary signals and inherent response delays, which affect the effectiveness of the suppression strategy. Based on the commutation voltage-time area theory, this paper quantitatively analyzes the impact of harmonics on the commutation margin area and proposes a firing angle correction strategy independent of real-time FFT calculation. In this strategy, the harmonic content boundary value that causes commutation failure is determined first. After quickly detecting an AC fault, the expected firing angle that meets the commutation margin requirement is calculated based on this boundary value. Further, the firing angle order output by the control system is corrected. Finally, the effectiveness of the proposed method is verified on the electromagnetic transient simulation platform PSCAD/EMTDC using the CIGRE HVDC benchmark test model and the Guizhou-Guangdong Ⅱ HVDC project model.关键词：high voltage direct current (HVDC) transmission;commutation failure;harmonic;fast Fourier transform (FFT);commutation voltage-time area;firing angle correction12|21|0更新时间：2026-11-04
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Online Impedance Identification and Stability Analysis Method for Wind Farm Based on Annulus Theorem
摘要：Due to the rapid time-varying operation status of wind turbines and the usual unknowns of unit structures and parameters, there is an urgent need for an online small-signal stability analysis method for grid connection to assess stability. This paper proposes an online impedance construction method based on piecewise affine and a fast stability judgment method based on annulus theorem. In terms of impedance identification, an off-line affine modeling and online linear calculation method is proposed. The agglomerative hierarchical clustering algorithm is used to optimally partition the parameter space, and within each partition, the impedance is expressed as a first-order explicit function of operation status variables and complex variables. It is only necessary to measure the real-time operation working point online to quickly locate the parameter partition and determine the corresponding impedance. In terms of stability judgment, an eigenvalue search method based on the annulus theorem is proposed, which can quickly search for the dominant oscillation mode online. The proposed method uses the coefficients of the characteristic equation to judge the position of the annulus where eigenvalues are located, avoiding the complex calculations caused by directly solving the characteristic equation. Through case study analysis, it is verified that the proposed method has high computational efficiency and accuracy, and can be applied to the online oscillation stability analysis of wind turbines.关键词：wind turbine;stability;piecewise affine;annulus theorem;impedance identification12|4|0更新时间：2026-11-04
Basic Research
- 摘要：In a flexible DC transmission station, the computing and processing capability of high-frequency time-series data is critical to ensuring the safe and reliable operation of key devices represented by insulated gate bipolar transistors (IGBTs). When handling high-frequency IGBT fault recording data, traditional computing methods often suffer from insufficient real-time performance and large time alignment errors, making it difficult to meet the requirements for rapid fault diagnosis and isolation. To address this issue, this paper proposes a high-frequency time-series data computing system for the scenario of high-frequency monitoring and fault diagnosis of IGBTs in flexible DC transmission stations. The system adopts a double-buffer out-of-order correction method to guarantee the complete alignment of high-throughput data, designs a streaming dynamic delay computation engine to achieve microsecond-scale snapshot processing, and introduces a reentrant computation window verification mechanism to improve result reliability. Experimental results show that the proposed system can significantly enhance the real-time performance and accuracy of data computation in application scenarios such as IGBT fault diagnosis, and provide effective support for condition monitoring and rapid fault isolation of key components in flexible DC transmission stations.关键词：flexible DC transmission station;insulated gate bipolar transistor (IGBT);fault recording;high-frequency time-series data;fault diagnosis;fault isolation11|1|0更新时间：2026-11-04
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