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最新刊期
卷 50 ， 期 8 ， 2026
- 摘要：The existing research on cyber security situation awareness for power systems mainly focuses on the cyber security of power monitoring systems, lacking a threat analysis of new dispatch and control entities (NDCEs) on the demand side, such as virtual power plants, user aggregators, and heterogeneous device clouds. With the integration of energy flow and business flow in various links such as source, grid, load, and storage, interactions between cross-subject businesses have become increasingly frequent, and the security threats brought by massive information interactions between NDCEs and power systems increase. In addition, the dominant position of user load control services in open cyberspace is becoming increasingly evident, and there is a new cyber-physical attack path without the need to invade the power monitoring system. This paper focuses on the security risks posed by NDCEs to power systems, and explores the cyber security situation awareness for NDCEs. Firstly, the characteristics of cyberattacks targeting NDCEs are analyzed, and the main security threats caused by such cyberattacks on the power system are deduced. Technical difficulties in cyber security situation awareness of NDCEs are revealed, and the research architecture for the cyber security situation awareness is proposed with a focus on the role of each stage. Finally, key technologies for the cyber security situation awareness are presented, thereby enhancing the ability of power systems to defend against cyber-attacks.关键词：demand side;cyber security;situation awareness;security and defense;dispatch and control entity;cyber-physical system0|0|0更新时间：2026-08-21
- 摘要：As a foundational function supporting the perception and decision-making of new power systems, state estimation is a key target in cyberattacks on critical power infrastructure. Cross-domain attacks using the information side as an entry point undermine the security of physical power systems by interfering with state estimation operations. This paper first employs scientific mapping tools with co-occurrence analysis to identify current research hotspots and development trends related to state estimation and its security threats. Subsequently, it analyzes the cross-domain attack methods, influence mechanisms, attack resources, and consequences associated with various functional modules within state estimation, revealing the security challenges they face. On this basis, a secure state estimation architecture that integrates randomness, heterogeneity and dynamics is proposed to explore the technical path to cope with the evolving external attack threats from the perspective of functional security enhancement of state estimation ontology.关键词：cyber-physical power system;state estimation;cross-domain attack;functional safety0|0|0更新时间：2026-08-21
- 摘要：Power security is crucial for national economic development and energy security. In recent years, the low-probability high-loss extreme events have posed significant challenges to the safe and reliable operation of distribution systems. Resilience assessment can effectively support this by quantitatively characterizing the ability of the distribution system to prevent, resist and recover from extreme events. This paper first introduces the basic theory of distribution system resilience assessment (DSRA), and reviews the research status of DSRA from three aspects: resilience modeling, resilience indices, and assessment algorithms. Then the basic concepts, research status, and application scenarios of model-data-cognition hybrid-augmented intelligent (MDC-HAI) method are presented, and the potential innovations that MDC-HAI may bring to resilience assessment are analyzed. Next, the MDC-HAI approach for DSRA is discussed, covering key technologies including failure modes and resilience modeling of distribution systems under extreme events, assessment indices and element representation of DSRA, and the MDC-HAI algorithm for DSRA. Finally, the future research directions for hybrid-augmented intelligent DSRA are proposed.关键词：distribution system;security;resilience assessment;artificial intelligence;cognition;extreme event0|0|0更新时间：2026-08-21
Review·Perspective
- 摘要：To address the rising export costs and weakened international market competitiveness of Chinese enterprises caused by carbon border regulation mechanism (CBAM), a dispatch strategy is proposed for park-level integrated energy systems (PIES) to participate in the trading of electricity-carbon-green certificate market for CBAM. Firstly, the CBAM policy and its cost calculation principle are clarified. On this basis, the CBAM cost calculation method considering the mutual recognition of green certificate and CBAM is proposed. Secondly, in order to reasonably share the costs of green certificates and effectively adjust the energy consumption demand of each period to cope with the pressure of CBAM, an hourly allocation strategy of user-side green certificates based on carbon intensity response is proposed. The electricity quantities corresponding to green certificates are allocated hourly according to the carbon intensity level in each period. Thirdly, the mechanism of price convergence in the electricity-carbon-green certificate markets is analyzed, and the convergence trading strategy for market entities to participate in electricity-carbon-green certificate markets is proposed. A multi-entity bi-level game optimization dispatch model for PIES is established to fully leverage the complementary advantages of resources among different markets and entities, so as to facilitate cost reduction and emission reduction. Finally, the improved alternating direction method of multipliers is employed for distributed solution. Through a typical case, it is verified that the proposed strategy has the function to promote the overall accommodation and emission reduction and alleviate the pressure of CBAM.关键词：integrated energy system;carbon border adjustment mechanism;electricity market;carbon market;green certificate market;bi-level game;distributed algorithm0|0|0更新时间：2026-08-21
- 摘要：Under the dual drive of electricity marketization reform and the EU carbon border adjustment mechanism (CBAM), export-oriented electric arc furnace (EAF) steelmaking enterprises are facing the dual pressure of reducing both energy consumption and emissions. How to achieve the electricity-carbon synergy through optimized production scheduling and trading strategies has become a critical research priority. The continuous cross-day production characteristic of steelmaking makes its production scheduling cycles inconsistent with the trading cycles of the spot market, resulting in poor economic efficiency of the formulated strategy. Therefore, this paper proposes a joint trading and scheduling optimization method with electricity-carbon synergy in EAF steelmaking enterprises considering the coordination of long- and short-term decision cycles. Firstly, the EAF steelmaking production scheduling model based on the resource-task network is established. Secondly, a two-stage coordination framework is proposed. In the first stage, the long-term production scheduling plan is optimized using multi-day electricity price and carbon emission factor forecasts, followed by daily slicing with fixed cross-day tasks. In the second stage, based on the production scheduling plan after daily slicing, the day-ahead electricity price and real-time electricity price forecasts are used for rolling optimization and adjusting daily trading and scheduling strategies. Finally, simulations validate the effectiveness of the proposed method in reducing electricity costs and carbon emissions.关键词：electric arc furnace steelmaking;electricity-carbon synergy;spot market;market trading;production scheduling;joint optimization0|1|0更新时间：2026-08-21
- 摘要：In the context of the carbon trading market, microgrids, as prosumers, can participate in the market transactions of electricity and China Certified Emission Reduction (CCER). To this end, this paper proposes a low-carbon dispatch strategy for the microgrid cluster alliance considering electricity-CCER coupling transactions. By constructing a Stackelberg game between the distribution system operator (DSO) and the microgrid cluster alliance, as well as a profit distribution model among the microgrid entities within the alliance, the coupling relationship between electricity and CCER is explored. A compensation mechanism between CCER and carbon emission is designed, and a bi-level optimization method is established. The upper-level DSO optimizes the transaction price to maximize its own profits, while simultaneously balancing the demand of the lower-level microgrids. After meeting its own load, the lower-level microgrid alliance, integrates and sells its surplus electricity and CCER to the DSO. Concurrently, considering the uncertainty of operation scenarios, the bi-level model is transformed into a distributionally robust optimization (DRO) model. To fairly distribute the benefits among various microgrid entities within the alliance, the Shapley value method is employed to address the allocation issues arising from electricity-CCER coupling. Finally, the DRO model is decomposed into a master problem and subproblems, which are solved iteratively by using the column-and-constraint generation algorithm. Case study analysis indicates that this mechanism can not only effectively optimize the transaction of electricity and CCER, increasing the benefits for entities at both upper and lower levels, but also promotes the development and maturity of the carbon market, providing a new approach for future low-carbon dispatch strategies of microgrid alliances.关键词：carbon trading;electricity-China Certified Emission Reduction coupling;carbon emission;Shapley value method;microgrid;optimal dispatch;uncertainty0|0|0更新时间：2026-08-21
- 摘要：To address the challenges of heterogeneous energy flow coupling and multi-agent coordination in coal mine-agriculture integrated energy systems (CM-AIES), a multi-energy collaborative optimization method for coal mine-agriculture integrated energy systems that considers the coupling of carbon-green certificate trading mechanisms is proposed. Firstly, by comprehensively considering the energy endowments of coal mine and agriculture, the potential for mutual support among electricity, gas, and thermal energy, as well as the utilization of associated energy resources and biogas, a fundamental model of an electricity-gas-thermal collaborative and mutually supportive CM-AIES is constructed. Secondly, agricultural carbon sink resources are accounted for, and the coupling mechanism of the carbon-green certificate trading mechanism is analyzed. Then, with the objective of minimizing the total operational cost of the CM-AIES, a collaborative optimization scheduling model for the system that integrates the carbon-green certificate trading mechanism is established. Finally, different scenarios are set up for simulation analysis. The results demonstrate that the proposed model can achieve multi-energy coupling and complementarity in CM-AIES, effectively promoting low-carbon economic development and enhancing the consumption of wind and solar energy.关键词：integrated energy system;coal mine;agriculture;agent;multi-energy collaboration;carbon trading;green certificate trading1|2|0更新时间：2026-08-21
Power System Analysis and Optimization from Carbon Perspective
- 摘要：The large-scale integration of various emerging elements has led to new characteristics of the power and energy balance of new power systems as multi-directional interaction, probabilistic balance, and temporal coupling. How to achieve quantitative analysis of power and energy balance under the new situation has become an important issue. Based on the theory of the time-series-probabilistic power and energy balance, the quantitative evaluation method oriented to high-dimensional balance region is proposed, including new evaluation indicators such as balance probability, unbalanced value, and unbalanced risk. And a robust evaluation model with its algorithm based on the maximum inner approximation of the balance region is also proposed. Since the approximate region is the largest inner filled subset of the real balance region, the reliability and the calculation accuracy of the evaluation results is guaranteed. Due to the avoidance of numerous repeated simulation and complex integral operation, the computational efficiency is improved, and the requirement of practical engineering can be met. Case study results show the validity of the proposed method based on the 2050 planned power system of a region of China.关键词：power and energy balance;balance region;time-series coupling;uncertainty;robust optimization0|0|0更新时间：2026-08-21
- 摘要：New power systems are facing a contradiction between the rapid growth of renewable energy installation and the increasingly insufficient peak-shaving capacity. The coordinated allocation issue of renewable energy generation and peak-shaving resources needs to be solved at the planning stage, meeting the demands of autonomous peak-shaving. A method for characterizing the grid-connection boundary conditions for autonomous peak-shaving is proposed. Based on the yearly sequential operation simulation, a system peak-shaving demand assessment and a verification model for autonomous peak-shaving principle of newly connected units are constructed. Furthermore, an optimal capacity allocation model for wind-thermal-load-storage under the principle of autonomous peak-shaving is proposed. The bundling allocation scheme is achieved through iteratively solving production optimization problem of flexible loads, the optimization of wind-thermal-storage capacity, and the verification of autonomous peak-shaving principle. Analysis shows that optimal load-production sequencing strategies are superior to equal-interval production methods, thereby maximizing the ability to match fluctuations in wind power. The proposed planning scheme neither increases the system peak-shaving demand nor influences the consumption of original renewable energy generation. Multiple newly connected units planned in parallel can still satisfy the autonomous peak-shaving principle when being connected to the system simultaneously. The proposed method can realize sustainable planning of renewable energy generation.关键词：peak-shaving;capacity allocation;flexible load;renewable energy generation;wind-thermal-load-storage bundling planning0|0|0更新时间：2026-08-21
- 摘要：Aiming at the problems of energy storage capacity demand and economic cost-benefit of multiple integrated energy systems at the present stage, this paper proposes a bi-level optimal capacity allocation method for electricity-hydrogen shared energy storage. First, to verify the applicability of shared energy storage in various scenarios, the region includes residential, industrial and commercial integrated energy systems, as well as the transportation process and economic model of hydrogen between two locations. Then, considering the full life-cycle cost covering energy storage procurement, operation and maintenance, aging, and hydrogen transportation, a bi-layer capacity allocation model for electricity-hydrogen shared energy storage is established with the capacities of batteries and hydrogen storage tanks as optimization variables. The upper layer adopts an improved particle swarm optimization algorithm with dynamic adjustment of inertial weight, while the lower layer uses mixed-integer linear programming to solve the capacity of the hybrid energy storage system. In addition, to reasonably allocate the operation cost of multiple systems under the sharing mode, an improved Shapley value method is adopted in the cooperative game to apportion the operation cost of the multi-system alliance. Finally, based on probability theory, typical days in southwest China are selected as cases to analyze the impacts of various alliance cooperation modes on regional allocation results and economic performance, so as to verify the superiority of the proposed method. The results show that shared energy storage in regional integrated energy systems can reduce the total regional cost, improve the utilization rate of energy storage and lower the dependence of the region on the main power grid. The proposed business model of shared energy storage can enhance the enthusiasm for energy sharing, and all systems participating in the construction of shared energy storage can achieve economic benefits.关键词：integrated energy system;shared energy storage;capacity allocation;improved Shapley value method;cooperative game1|1|0更新时间：2026-08-21
- 摘要：The source-load uncertainty, multi-interest games, and cheating behaviors in the trading process of multi-region integrated energy systems (IESs) with hydrogen pose challenges to the collaborative operation. Therefore, this paper proposes a robust optimization method of triple game for multi-region IESs with hydrogen against cheating behaviors. First, an operation architecture of multi-region IESs with hydrogen containing photovoltaic (PV) prosumers is established, and the distributionally robust chance constraints are incorporated into a two-stage distributionally robust optimization model under the Wasserstein distance ambiguity set, which fully considers the uncertainties on both the source and load sides of PV prosumers and each IES. Then, a triple game architecture of “Stackelberg+cheating+cooperation” is constructed to address the problems of multi-interest games among IESs with hydrogen and cheating behaviors in trading process. Finally, the alternating direction method of multipliers (ADMM) nested with the column-and-constraint generation (C&CG) algorithm is adopted for distributed solution, which can defend against cheating behaviors while protecting the privacy of participants. Simulation results verify that the proposed strategy can effectively improve the operation efficiency of IES and enhance its ability to cope with uncertain risks while resisting cheating behaviors.关键词：integrated energy system (IES);photovoltaic (PV) prosumer;cheating;distributionally robust optimization;game;alternating direction method of multipliers (ADMM);column-and-constraint generation (C&CG) algorithm0|0|0更新时间：2026-08-21
- 摘要：The electricity-hydrogen-gas integrated energy system based on hydrogen-blended pipelines can effectively mitigate the operation uncertainties caused by high-penetration renewable energy. Therefore, this paper proposes an optimal scheduling framework that integrates Transformer-based unsupervised learning with physical mapping, aiming to address the problems of insufficient solution efficiency and strong dependence on labels in existing scheduling methods. First, an operation model of the electricity-hydrogen-gas hybrid integrated energy system is constructed. Then, the Transformer network is used to extract the temporal features of the model, and the energy flow equations are embedded through the physical mapping layer. Finally, the loss function is constructed via the Lagrange multiplier method to generate physically feasible strategies without labels. The results of the case analysis show that, in the 10-hour scheduling scenario, the deviation of the total cost from the mathematical programming benchmark solution is only 0.29%, and the online prediction time is stable at about 1 second. Compared with the long short-term memory network and the deep neural network, the training time of the proposed method is reduced by 18.8% and 11.4%, respectively, and the average constraint violation rate is decreased by 29.1% and 16.8%, respectively. Sensitivity analysis reveals the influence of learning rate and multiplier weight on training convergence and constraint violation degree, which provides theoretical support for multi-energy coordinated optimization.关键词：integrated energy system;multi-energy coordination;optimal scheduling;Transformer architecture;physical mapping;unsupervised learning0|0|0更新时间：2026-08-21
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Distributed Consensus Control of Multiple Dynamic Virtual Power Plants for Fast Frequency Regulation
摘要：With the increasing penetration of renewable energy, power system frequency stability faces severe challenges. As an aggregation of distributed energy resources (DERs) over short timescales, dynamic virtual power plants (DVPPs) have significant frequency regulation potential. However, the heterogeneity of DERs in energy characteristics and response speeds constrains efficient coordination. To address this, this paper proposes a distributed consensus control to coordinate heterogeneous DERs across multiple DVPPs for fast frequency regulation. First, through the design of a power control link and energy dynamics equation modeling, the available energy ratio that characterizes the utilization of DER energy is defined, achieving standardization of DER operating status. Then, by using the available energy ratio as a consensus state indicator, a distributed consensus control suitable for multi-loop communication networks of DERs is proposed, along with delay compensation and interruption detection strategies for non-ideal communication conditions. Subsequently, consensus convergence is proven through Lyapunov analysis. Finally, the simulation on a modified IEEE 39-bus system with three DVPPs verifies that the proposed control outperforms decentralized control in both frequency regulation effectiveness and energy security margin.关键词：distributed energy resource;dynamic virtual power plant;frequency regulation;consensus;energy security margin0|2|0更新时间：2026-08-21 - 摘要：The integration of high proportion of renewable energy poses challenges to the power system static stability. The non-analytical and highly non-linear characteristics of voltage-power angle stability constraints make optimization solutions difficult. However, such constraints can be approximately resolved within local regions. By focusing on these critical parts where stability constraints are active, the easily solvable analytical models can be constructed and embedded into the optimization process. On this basis, a modeling and operation optimization method for the static voltage and power angle stability constraints based on the critical part focusing is proposed. First, the method pre-solves the optimization model without considering stability constraints to identify an initial point, which guides the focus towards the critical parts of stability boundary. Then, the data-driven approach is used to construct a linear analytical expression to characterize the complex non-linear stability constraints within the critical parts. Finally, this expression is embedded into the operation optimization model for solving, coupled with a constraint correction strategy to guarantee system stability. Case studies validate that the proposed method can meet the requirements of static stability while ensuring economy, and has good computational efficiency.关键词：voltage stability;power angle stability;static stability;modeling;operation optimization0|0|0更新时间：2026-08-21
- 摘要：The nonlinear limiter in the governor of hydropower units may yield the ultra-low frequency oscillation in the power system. Existing description functions are difficult in analyzing the nonlinear interaction through power grid coupling among multiple limiters. A matrix description function (MDF) method is proposed to analyze the impact of multiple limiters on the ultra-low frequency oscillation characteristics of power system with hydropower units. Firstly, the transfer function matrix of the power system with multiple hydropower units in the frequency domain is established. The similarity transformation MDF method is used to analyze the coupling mechanism among multiple limiters. Secondly, the 2-norm is used to quantify the MDF curves, enabling prediction of the limit cycle of power system. Finally, based on the generalized Nyquist theory, the system stability discrimination method is proposed to define an indicator for quantifying the impact of limiters on system ultra-low frequency oscillations. Simulation analysis on the test system with four hydropower units in two areas verifies the effectiveness of the proposed algorithm and stability criterion. Simulation results demonstrate that the oscillation frequency remains basically unchanged while the oscillation amplitude changes under different amplitude limits. Excessive amplitude limits will weaken the system ability to suppress ultra-low frequency oscillations and increase the risk of instability.关键词：hydropower unit;limiter;ultra-low frequency oscillation;stability;matrix description function;generalized Nyquist theory0|0|0更新时间：2026-08-21
- 摘要：During the operation of wind farms, due to the influence of factors such as weather and transmission failures, there are a large number of abnormal data in the data set, which will seriously affect the quality of the data set. In view of the low performance and poor universality of the abnormal data recognition algorithm in the existing wind power data processing, a wind power abnormal data processing method based on combined anomaly recognition and graph attention network (GAT)-generative adversarial network (GAN) is proposed. First, based on the analysis of the generation mechanism of wind power abnormal data, the abnormal data is divided into three types: bottom accumulation type, middle accumulation type and discrete type. Then, according to the characteristics of various abnormal situations, a combined recognition method is established to identify and label targeted anomalies for each type of abnormal data. Next, considering the spatio-temporal correlation between each wind turbine, a wind farm graph structure is constructed for each unit based on their spatio-temporal correlations. Based on this graph data structure, a reconstruction model is established by using techniques such as graph attention mechanism, gradient penalty mechanism, and GAN to accurately capture the complex spatio-temporal correlations between units and generate wind power data that conforms to the actual observed distribution. Finally, the universality and progressiveness of the proposed method are demonstrated through experiments and comparative analysis of the measured data of wind turbines in the wind farm.关键词：wind farm;wind power;abnormal data;graph structure;spatio-temporal correlation;graph attention network;generative adversarial network;gradient penalty0|0|0更新时间：2026-08-21
Basic Research
- 摘要：Intra-provincial power grid enterprises face dual uncertainties in agency power procurement due to fluctuations of renewable energy output and electricity spot market prices. Traditional price-volume prediction models are poorly suited for the highly volatile scenarios of agency power procurement. To address this issue, an inference model for trading trends based on a liquid neural network (LNN) is developed. This model considers the multi-factor coupling characteristics of agency power procurement and quantifies the spot trading trends using a vertical-horizontal filter indicator from financial domains. By incorporating feature data such as day-ahead settlement power volume, settlement power price, cumulative temperature, and supply-demand ratio, the LNN is adopted to dynamically adjust neuron states and liquid time constants, achieving the adaptive learning of complex temporal patterns in the electricity market. Finally, the verification is conducted by using the price-volume data from the electricity spot market in a region of Hebei Province, China. The results demonstrate that the proposed model can effectively identify both the trend and oscillation intervals in agency power procurement data, outperforming conventional price-volume models in terms of trend segmentation and inflection point prediction.关键词：price-volume prediction;vertical-horizontal filter indicator;agency power procurement;electricity spot market;liquid neural network (LNN);uncertainty;trend segmentation;inflection point prediction0|1|0更新时间：2026-08-21
- 摘要：The loss-of-excitation protection is an important component of grid-related protection for generators. Its correct design and reasonable protection setting are crucial for enhancing the coordination between the generator and the grid and ensuring the safe and stable operation of the system. Accidents caused by unreasonable protection settings occur frequently. Firstly, a theoretical analysis of the physical characteristics and impedance variation patterns of generators during loss-of-excitation faults is conducted, revealing the limitations of existing schemes that adopt conservative settings. It is pointed out that the key to solving the problem is to achieve grid-side state perception that adapts to changes in actual operating modes. Furthermore, a mechanism-equivalent model incorporating the system operating parameters required for protection is constructed, and a model parameter synchronization method that integrates unit operating data is designed. Finally, by using the difference between real-time data and model calculation results as an indicator for model updating, adaptive adjustment of protection settings is achieved, forming a complete adaptive setting scheme for loss-of-excitation protection of turbogenerators based on mechanism-data integration. Real machine experiments and simulation verification show that the proposed scheme can reliably identify loss-of-excitation faults in different operating scenarios without requiring additional measurement equipment.关键词：turbogenerator;mechanism-data integration;equivalent model;loss-of-excitation protection;protection setting0|0|0更新时间：2026-08-21
- 摘要：To address the existing issues of main protection for transmission lines connected to energy storage power stations, this paper proposes an adaptive differential protection principle based on current amplitude and phase compensation. First, the amplitude and phase characteristics of the fault current provided by the energy storage power station, as well as the operating performance of traditional current differential protection, are analyzed. Based on this analysis, considering the amplitude ratio of currents on both sides of the transmission line and the charging and discharging states of the energy storage system, the amplitude and phase compensation functions are constructed, respectively. Then, according to the phase difference between the currents on both sides, the fault current is compensated in different ways, thereby forming an adaptive percentage-restrained differential protection. Through simulation and dynamic model tests, it is verified that the proposed protection principle adapts to the charging and discharging states of the energy storage power station, exhibits high reliability and speed under various fault conditions, can withstand 500 Ω transition resistance and 30 dB noise, and solves the problem of mal-operation of traditional differential protection for internal faults.关键词：energy storage power station;transmission line;current differential protection;amplitude and phase compensation;charging and discharging0|0|0更新时间：2026-08-21
Application Research
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