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最新刊期
卷 49 ， 期 16 ， 2025
- 摘要：Current energy system tends to be open and flat, and the energy management mode has gradually shifted from source varing with load to source-load interaction, which challenges the centralized management mode of traditional distribution networks based on the reductionism cognitive approach of assumption simplification and empirical regulations. In this context, this paper proposes an architecture of Energy Internet metaverse that integrates electric power expertise, cutting-edge machine learning, and smart emergence technology to reconstruct the system cognition and optimization decision-making system. First, the connotation and implementation path of the metaverse are elaborated with the trend of electric power digital and intelligent transformation. Then, based on the data-intensive scientific discovery paradigm, this paper designs a functional modular architecture oriented to multi-agent collaboration and intelligent emergence. It also constructs a simulation-analyzable Energy Internet ecosystem. Finally, facing the needs of the whole process cognition and decision-making of complex systems, the realization scheme of data empowerment is discussed from the perspective of three virtual spaces, namely, data space, feature space, and decision space. The results of engineering demonstrations such as Lingang new area in Shanghai, China, show that the architecture provides a new path for the modeling and simulation of multi-agent complex energy systems, and realizes the efficient utilization and flexible regulation of distributed energy resources.关键词：Energy Internet;digital twin;metaverse;situational awareness;intelligent emergence9|0|0更新时间：2025-09-25
- 摘要：Power system is one of the most critical infrastructures in a country, thus ensuring its secure and stable operation is of great significance. However, power system may also face threats of unconventional extreme events such as malicious strikes under complex international situations. Compared with extreme weather events such as typhoons, unconventional extreme events are characterized by intentionality, acute suddenness, and high destructiveness, posing severe threats to the secure and stable operation of the power system. Therefore, from the unconventional perspective, this paper explores the extreme survival issue of power systems under unconventional extreme events. First, based on the characteristics of unconventional extreme events, the concept of power system survivability is defined and compared in detail with concepts of reliability, self-healing and resilience. Then, the major problems and challenges faced in the enhancement of power system survivability under unconventional extreme events are analyzed. Finally, the research plan for enhancing the power system survivability is preliminarily sorted out and five urgent research directions are proposed, i.e., unconventional extreme events simulation and modeling of system damage mechanisms, assessment of power system survivability to unconventional extreme events, improvement of power system survivability capabilities from the perspective of cyber-physics coupling, supporting systems and equipment for power system damage detection and repair, and a survivability sand table deduction system for unconventional extreme events. The main purpose of this paper is to point out the importance and urgency of studying the improvement of power system survivability under unconventional extreme events, and propose forward-looking research ideas, which can help provide reference for enhancing the extreme survival capabilities of power system in China.关键词：extreme event;resilience;power system;cyber-physics coupling;survivability;extreme survival7|1|0更新时间：2025-09-25
Review·Perspective
- 摘要：The power industry is facing increasing pressure to ensure supply and promote renewable energy consumption due to challenges such as the primary energy security crisis, the continuous increase in the penetration rate of renewable energy under the goal of “carbon emission peak and carbon neutrality”, and the frequent occurrence of extreme weather events. Value of lost load (VOLL) can effectively guide the formulation of time-of-use and peak-shaving power consumption and external power transmission planning schemes in various industries. Therefore, starting from the estimation methods of VOLL in various scenarios, first, an estimation method of provincial time-of-use VOLL suitable for China national conditions is proposed based on the production function method. Then, taking the electricity consumption data and economic data of Jiangsu Province, Ningxia Hui Autonomous Region and Xinjiang Uygur Autonomous Region as examples, the applicability of the proposed method is verified, and the differences of provincial VOLL under various industrial structures are discussed. Finally, the proposed provincial time-of-use VOLL curves are combined with the application scenarios of ensuring supply and promoting renewable energy consumption to assess the contributions of renewable energy output to the industrial economy of various provinces and regions. For provinces rich in renewable energy, the planning for external power transmission is carried out in combination with the development of regional industrial economy.关键词：energy security;value of lost load (VOLL);time-of-use;extreme weather event;production function;external power transmission;planning6|0|0更新时间：2025-09-25
- 摘要：Black-start technology is the critical one for ensuring the rapid restoration of power systems following large-scale outages. However, due to the decisive impact of the geographical location and technical parameters of the black-start unit (BSU) on the black-start restoration strategies, the traditional operational mode of black-start ancillary service markets suffers from insufficient competition. This limitation not only reduces the efficiency of utilizing system restoration resources but also significantly increases the operation costs for dispatching agencies. To address this issue, a bidding mechanism of black-start ancillary service market is proposed to enhance the cost-effectiveness by introducing competitive mechanisms. Firstly, the impact of various BSU site selection combinations on service quality is analyzed. Based on this, the market value of candidate units under various bidding scales of black-start ancillary service market is quantified, and the corresponding procurement costs are predicted. Secondly, based on these analysis results, the total BSU bidding quantity is optimized to improve the economy of BSU procurement plans, thereby providing more favorable conditions for system restoration. Finally, it is proven through simulation that the proposed bidding mechanism of black-start ancillary service market can optimize procurement costs while ensuring black-start efficiency.关键词：power system restoration;large-scale outage;black-start;electricity market;ancillary service market;bidding;competition;cost-effectiveness8|0|0更新时间：2025-09-25
- 摘要：To enhance the power generation capacity of solar-thermal power generation systems and promote the development of renewable energy sources such as biomass energy and hydrogen energy, the operation framework of the solar-thermal and biomass integrated hydrogen production plant (STBIHPP) is proposed. On this basis, a dual-layer optimal operation model for STBIHPP in market environment is proposed. Firstly, based on the energy complementarity characteristics between the parabolic trough solar-thermal power generation system and biomass gasification power generation for hydrogen production, an integrated hydrogen production plant model driven by solar-thermal and biomass is established. Secondly, in order to optimize the operation strategy of STBIHPP, a dual-layer optimal operation model for STBIHPP in the electricity-hydrogen integrated market environment is proposed. Finally, the Karush-Kuhn-Tucker (KKT) condition is used to transform the dual-layer model into a single-layer model, and then methods such as piecewise McCormick approximation are adopted to transform the single-layer model into the mixed-integer second-order cone programming (MISOCP) model. The simulation results show that the proposed framework can effectively enhance the energy coupling between various systems and improve the energy utilization rate. At the same time, the revenues of renewable energy hydrogen production plants in both markets are significantly increased.关键词：biomass energy;hydrogen energy;solar-thermal power generation;electricity-hydrogen integrated market;energy coupling;energy complementarity;energy cascade utilization5|1|0更新时间：2025-09-25
- 摘要：With the large-scale integration of distributed energy resources (DERs) into the power system, their excellent regulation capability is not only applied under normal operation conditions but also effectively prevents risks brought by extreme weather such as typhoons. This paper proposes a coordinated pre-disaster scheduling strategy of transmission and distribution networks under the aggregation feasibility and frequency stability constraints of DERs. Firstly, the state of the supporting nodes in the distribution network is characterized by the linear power flow method, and the aggregation feasibility boundary of DERs for pre-disaster scheduling is constructed by combining the adaptive robust optimization method to ensure the feasibility and flexibility of the power regulation interval of the supporting nodes. Secondly, in the pre-disaster prevention stage, relying on the dynamic regulation capability of the supporting nodes, the power distribution strategy is optimized to reduce load shedding during disasters and improve the power supply stability of the transmission network. At the same time, by combining the pre-disaster fault scenario prediction and the dynamic frequency stability constraints during the island formation process, an optimization model is constructed to adjust the power distribution of DERs before the disaster and reserve the frequency regulation reserve capacity, thereby reducing the risk of frequency fluctuations during the island establishment process. Finally, the effectiveness of the proposed strategy is verified by the improved IEEE 30-bus transmission-distribution network simulation.关键词：pre-disaster scheduling;distributed energy resource (DER);aggregation;feasibility;transmission network;distribution network;frequency stability6|0|0更新时间：2025-09-25
- 摘要：The source-grid-storage coordinated planning needs to take into account multiple entities simultaneously. Due to its high dimensionality and strong nonlinearity, the solution process is time-consuming, which limits its practical application. Therefore, an efficient solution method integrating evolutionary algorithms and empirical rules is proposed to fully utilize the strong optimization capability of evolutionary algorithms and the convergence acceleration characteristics of empirical rules, significantly improving the solution efficiency. First, a source-grid-storage coordinated planning model with embedded time-series production simulation is constructed to address the variable operation modes of the new power system. Then, expert experience is summarized and refined, and formalized through a fuzzy reasoning tool. Finally, the empirical rules are integrated into the non-dominated sorting genetic algorithm with elite retention to optimize the initial search space and evolutionary direction, thereby forming an efficient solution algorithm. A case of the 90-bus system of a provincial power grid in China for the siting and sizing of wind and solar power sources and energy storage is used to verify the significant advantages of the proposed method in terms of solution efficiency and optimization effect.关键词：new power system;source-grid-storage;coordinated planning;evolutionary algorithm;empirical rule;non-dominated sorting genetic algorithm9|1|0更新时间：2025-09-25
- 摘要：As the proportion of residential electricity load in the total electricity load of the society gradually increases, accurate residential load forecasting results are of great significance for enhancing the safety and economy of the power system operation, especially for promoting demand-side response. However, due to many objective and human factors, such as incomplete measurement configuration, measurement equipment failures and data transmission problems, load data may be incomplete, lost or distorted. Moreover, residential load is highly uncertain, making it difficult to achieve high-precision load forecasting. Under this background, first, a personalized federated learning framework is proposed, which customizes high-precision personalized load forecasting models for each residential end without infringing on the privacy of residential data. Then, the graph feature propagation (GFP) method is used to reconstruct the missing load feature parameters, which can largely avoid the problem of forecasting accuracy decline caused by data missing. Finally, the proposed method is tested through cases. Simulation results show that, compared with the existing representative methods, the proposed method has higher forecasting accuracy and significantly better performance in handling data missing compared to common interpolation methods.关键词：short-term load forecasting;personalized federated learning;graph feature propagation;missing feature;feature reconstruction5|1|0更新时间：2025-09-25
- 摘要：Aiming at the problem of insufficient accuracy of wind power forecasting under extreme weather events such as cold waves, typhoons and icing, an extreme weather event discrimination method based on meteorological factors is proposed, and an adaptive short-term wind power forecasting method for extreme weather events based on transfer learning and autoencoder is proposed. Firstly, by analyzing the coupling characteristics between meteorological factors and wind turbine output, the extreme weather discrimination standards are defined to identify the types of weather events that will occur in the future. Secondly, based on the autocorrelation mechanism of autoencoder forecasting model, the utilization of long-time-series information is increased. The pre-training-fine-tuning strategy of transfer learning is adopted, whereby sufficient samples under normal weather are used for pre-training the forecasting model, and then fine-tuning is carried out for the limited samples of extreme weather data. The forecasting model is adaptively applied to the short-term wind power forecasting according to the discrimination of extreme weather events. The datasets from 12 wind farms are selected for analysis, and the effectiveness of the proposed method is verified by analyzing the forecasting performance of the model under extreme weather and all kinds of weather conditions. The experimental results show that the proposed method can accurately forecast whether an extreme weather event will occur in the future and substantially improve the accuracy of short-term wind power forecasting under extreme weather events.关键词：extreme weather event;wind power forecasting;autoencoder;pre-training;fine-tuning;transfer learning9|3|0更新时间：2025-09-25
- 摘要：Existing data-driven wind power forecasting models inevitably suffer from the learning offset problem in the modeling process, which leads to these models being biased to learn partial data samples with concentrated distribution, resulting in poor generalization ability in the practical applications. A short-term wind power forecasting method based on the model learning offset correction is proposed to address the aforementioned issue. Firstly, by exploring the principle of differential samples causing model prediction performance offset, temporal samples are classified and characterized. Subsequently, for extreme weather samples, abnormal samples, and similar imbalanced samples that are difficult to predict in historical data, the strategies of multi-scenario generation, progressive mask detection, and sample feature enhancement are used to jointly correct the offset in the model learning. Finally, the Shapley value method is used to evaluate the importance of various samples, in order to verify the necessity and rationality of the offset correction strategy. Actual cases show that the proposed method can significantly improve the short-term wind power forecasting accuracy of various models, and has good generalization in multi-scenario modes.关键词：wind power forecasting;model learning offset;data enhancement;sample feature;sample extraction;multi-scenario mode6|0|0更新时间：2025-09-25
- 摘要：Accurately constructing equivalent models that can characterize the dynamic response characteristics of photovoltaic power stations is the basis for analyzing the grid performance of photovoltaic power stations and the safety and stability of large-scale photovoltaic power integrated to the power grid. Therefore, this paper proposes a dynamic equivalent method for photovoltaic power stations considering the differences in active power ride-through response characteristics. First, the low voltage ride-through dynamic response curve of photovoltaic power generation unit is analyzed, and three types of typical active power response are clustered. Then, three types of active power response characteristics are studied, and their general clustering boundary function is derived. Identifying that the initial active power and fault sustained voltage before the fault of photovoltaic power generation unit are the dominant factors affecting its active power response category. Based on this, clustering indices are constructed, and the photovoltaic module engineering models and network graph theory are used to approximate the clustering indices to overcome the difficulty of obtaining actual unit level operating parameters in power stations, effectively dividing three photovoltaic clusters with different active power dynamics. Furthermore, the clustered photovoltaic power generation units and collection networks adopt a two-stage slope recovery function to characterize the active current command of the equivalent model of the active power slope recovery cluster, in order to fit the actual slope reduction recovery characteristics of the active power for the power station. Finally, taking an actual photovoltaic power station as an example, the proposed method is analyzed and validated, and the results prove that the proposed dynamic equivalent method has high accuracy and strong adaptability.关键词：photovoltaic power station;low voltage ride-through;clustering;active power response;dynamic equivalent method;power recovery6|0|0更新时间：2025-09-25
- 摘要：To address the issues that synergistically coordinating and enhancing the suppression capability of ultra-low-frequency oscillations and primary frequency regulation performance in hydropower clusters is difficult, as well as the optimization efficiency of multi-machine parameters is not high and dependent on expert experiences, a parameter optimization method for hydropower clusters is proposed. First, a multi-machine damping analytical model is used to analyze the composition of ultra-low-frequency oscillation damping in hydropower clusters, thereby obtaining the key influencing factors and influencing laws regarding the ultra-low-frequency oscillation damping and primary frequency regulation performance. Then, a dual-knowledge-assisted deep reinforcement learning (DRL) framework is constructed, integrating the parameter optimization method and oscillation safety damping knowledge. In this framework, the parameter optimization method and the oscillation safety damping knowledge are learned through model-driven approaches and rule-guided assistance, respectively, enabling the agent to efficiently search for optimal parameters that achieve the best primary frequency regulation performance within safety damping intervals. Finally, taking a specific hydropower cluster as a case, the effectiveness of the proposed method is validated through hardware-in-the-loop experiments.关键词：ultra-low-frequency oscillation;damping;primary frequency regulation;deep reinforcement learning;hydropower cluster;parameter optimization6|1|0更新时间：2025-09-25
- 摘要：Aiming at the problem of winding temperature rising in power transformers caused by renewable energy output fluctuations and harmonic currents, a hotspot temperature correction method for renewable energy transmission transformers is proposed. Based on this, a 3D Copula-based probability density model for hotspot temperature of renewable energy transmission transformers is established. Considering the impact of renewable energy penetration rate and its correlation variation with wind-photovoltaic-load, the corresponding relationship between renewable energy output fluctuations and hotspot temperature is obtained. Harmonic loss factors are introduced to calculate transformer losses under harmonic currents, and the coupling effects of total harmonic distortion (THD) and load rate on hotspot temperature are analyzed. Taking a wind-photovoltaic-thermal bundling transmission system as an example, using historical wind and photovoltaic output data, the hotspot temperature of the transmission transformer is calculated and its thermal aging risk is evaluated. Results show that the proposed modified model can handle hotspot temperature calculations for transformers in various renewable energy output scenarios. With the increase in the renewable energy penetration rate, load correlation, THD and load rate, the risk probability of hotspot temperature exceeding extreme conditions significantly rises. Therefore, greater attention to the problems of transformer temperature rise is required in high-penetration renewable energy integration systems.关键词：renewable energy;load correlation;transformer;harmonic current;hotspot temperature;total harmonic distortion (THD);thermal aging risk3|1|0更新时间：2025-09-25
Basic Research
- 摘要：With the increasing penetration of distributed energy resources (DERs) in the distribution network, innovative business modes such as the shared battery energy storage system (BESS) are emerging. The shared energy storage systems are typically co-invested by multiple stakeholders, including energy storage users, energy service companies, aggregators or energy storage operators. The conflicting interests of these stakeholders pose significant challenges to the operation and control of the shared energy storage systems. This paper proposes a decentralized distributed management framework based on blockchain smart contracts, utilizing smart contract technology to realize automatic control and optimize the operation strategies of shared energy storage systems. By establishing a multi-layer automated management framework based on data processing, decision support, and decision-making, and adopting smart contract rule sets such as highest combined offer (HCO) and ranked preference selection (RPS), the stakeholder conflicts are harmonized to achieve optimal shared operation for shared energy storage systems. Through the case analysis on shared battery energy storage of households and energy storage operators, the effectiveness of the automated management mode for smart contracts is validated, and its advantages in enhancing energy efficiency and improving stakeholder satisfaction are demonstrated.关键词：smart contract;blockchain;shared energy storage;business mode;distributed energy resource (DER);distribution network8|0|0更新时间：2025-09-25
- 摘要：The offshore wind power transmission system with the current source converter (CSC) has the advantages of high power density and the ability to supply power to a passive network, which has a good application prospect. However, the existing scheme has three major problems: it requires a lot of communication, the black start is uneconomical, and the reactive power of the wind turbine is prone to overload. In this paper, an improved islanded operation and black-start strategy is proposed. Firstly, based on the sensitivity analysis, a cooperative control method of AC voltage amplitude and frequency by CSC and wind turbine without communication is proposed. Secondly, by using the LC filter as the reactive load, a method for establishing offshore AC voltage through cooperation between the sending-end CSC and the receiving-end CSC is proposed. Thirdly, the effect of DC voltage on reactive power overload of wind turbines during system start-up is analyzed, and the reactive power optimization strategy is proposed. The above strategies are verified by simulation based on PSCAD. Finally, the CSC scheme and the diode rectifier unit scheme are discussed from three aspects of complexity, feasibility and cost. The analysis results show that the improved islanded operation and black-start strategy is effective.关键词：offshore wind power;DC transmission;current source converter (CSC);islanded operation;black start;sensitivity;reactive power optimization5|2|0更新时间：2025-09-25
- 摘要：Most of the anti-islanding protections applied in the field are passive anti-islanding protections based on voltage/frequency inspection. The problems of misoperation and refuse-operation are common when grid disturbances and unplanned islands are formed. Impedance-measurement anti-islanding protection utilizes the impedance characteristics of the system to identify grid disturbances and islands, effectively solving the deficiencies in the existing anti-islanding protection. However, the setting of protection criteria is highly dependent on the impedance parameters of the system, and the mutual interference of the inspection signals in a multi-distributed generator (DG) system can lead to the failure of the protection. Therefore, an anti-islanding protection method based on the magnitude ratio of inspection signal to power frequency voltage is proposed. On the basis of analyzing the measured impedance characteristics before and after the formation of an island, a unified identification criterion is established for different islanded systems, and the adaptability of the method is analyzed in terms of branch lines, low voltage ride-through, and so on. Besides, a synchronous injection and inspection method based on a 60 Hz signal is designed by combining the DG control strategy with a voltage zero-crossing point. Simulation experiments based on real-time digital simulation (RTDS) system show that the method can complete the islanding inspection within one second after the islanding occurs, which avoids the misoperation and refuse-operation problems in the existing over-/under-voltage (OUV), over-/under-frequency (OUF) and other anti-islanding protection methods.关键词：distribution network;distributed generator;inspection signal;power frequency voltage;anti-islanding protection;voltage synchronization;magnitude ratio4|0|0更新时间：2025-09-25
- 摘要：The grid-connected system of the grid-forming converter exhibits abnormal instability in a strong grid. The mechanism of interaction between the power synchronization control loop and the voltage control loop is unclear. Therefore, from the perspective of oscillation frequency (bandwidth of control loop), this paper analyzes the interaction between control loops under various strong or weak grid conditions (with line reactance variation) of the system, and various stability results caused by the interaction are obtained. Firstly, the linearized model of the system is established, and the subsystem bandwidths of both the virtual synchronous generator and the terminal voltage control loops are calculated based on the automatic control theory. It is revealed that the bandwidths of the two subsystems exhibit opposite trends varied with the line reactance. Subsequently, by using the singular perturbation theory, the analysis of the interaction between the control loops under various grid conditions is carried out with the virtual synchronous generator or terminal voltage control as the main subject. Furthermore, the system stability is evaluated by analyzing the amplitude-phase characteristics of the open-loop transfer function of the system, and the critical line reactance leading to the instability in the strong grid is obtained. Finally, the parameter influences of the virtual synchronous generator and the terminal voltage control, as well as the difference and relationship between the control loop bandwidth separation method and the mainstream methods are studied. The correctness of the above analysis is verified by simulation and hardware-in-the-loop (HIL) experiments.关键词：renewable energy;grid-forming converter;virtual synchronous generator;power synchronization control;terminal voltage control;small-signal stability;control loop bandwidth;singular perturbation6|0|0更新时间：2025-09-25
- 摘要：To enhance the operational efficiency of the bidirectional wireless power transfer (BWPT) system for electric vehicles over a wide power range, this paper focuses on a dual-coupled double-sided inductor-capacitor-capacitor series and parallel connection (LCC-LCC) compensation topology and proposes a multi-variable and multi-mode combined regulation strategy for high-efficiency operation. Firstly, the high-efficiency conditions of the resonant network and the power converter are derived as the theoretical basis for the efficiency optimization method. Secondly, a time-domain model compatible with various excitation voltage schemes is developed. Based on this model, the triple-phase-shift control method is analyzed, which achieves impedance matching, critical soft switching of power devices, and optimal efficiency. Furthermore, three operation modes of the high-frequency converter, namely full-bridge, half-bridge, and mixed-bridge, are studied. Mode-switching coordination is introduced to minimize the deviation of the external phase-shift angle, reduce switching losses, and adapt to different parameters and operating conditions. Finally, the experimental platform of a BWPT system is established. The effectiveness of the proposed model, method, and strategy is verified under various operating conditions. Experimental results show that the system achieves a DC-DC conversion efficiency of 94.0%~96.4% across the power range of 5%~100%.关键词：electric vehicle;charging and discharging;bidirectional wireless power transfer;efficiency optimization;phase-shift control;mode switching9|0|0更新时间：2025-09-25
- 摘要：The converters on the rectifier side and the inverter side of the existing high-voltage direct current (HVDC) and ultra-high-voltage direct current (UHVDC) transmission systems coordinate and cooperate during faults, and control methods such as converter phase shifting, switching in the bypass pair, and blocking are adopted to suppress the fault current. Various control methods and timing coordination are adopted according to various fault locations to form various blocking modes, including pole X blocking, pole Y blocking, pole Z blocking, converter X blocking, converter Y blocking, etc. Further, the fault is isolated by tripping the AC breaker, opening the pole neutral bus switch, and closing the bypass switch. However, the existing control methods for converters during faults only consider the handling of faults and do not consider the impact on the AC system. As a result, severe overvoltage will occur in the weak AC system and the fault current may not be effectively suppressed under some grounding faults. This paper presents a fault control method for HVDC transmission. By controlling the DC currents of the converters on both sides of the fault to be equal during a fault, the fault current can be effectively suppressed. Meanwhile, the converters continue to consume reactive power in coordination with the disconnection of the AC filter to effectively suppress the AC overvoltage. Finally, the fault control methods for faults in the pole area, bipolar area and DC transmission line are introduced, respectively.关键词：high-voltage direct current (HVDC) transmission system;blocking;overvoltage;fault current;converter5|0|0更新时间：2025-09-25
Application Research
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