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Table of Content

    28 November 2025, Volume 59 Issue 11 Previous Issue   
    New Type Power System and the Integrated Energy
    Modeling Methods for Power Secondary System Simulation in New Power Systems
    HE Ruiwen, XIE Haijun, LU Jialiang, YANG Changxin, MOHAMMAD Shahidehpour
    2025, 59 (11):  1581-1591.  doi: 10.16183/j.cnki.jsjtu.2023.556
    Abstract ( 1472 )   HTML ( 3 )   PDF (2421KB) ( 634 )   Save

    New power system achitecture will greatly increase the difficulty and vulnerability of the operation and control of power systems. The high integration of information and communication technology (ICT) promotes comprehensive information sharing, but it also highlights the urgency of establishing modeling and analysis methods for ICT-based power secondary systems. In this paper, simulation modeling methods for power secondary systems are proposed for the first time to achieve information sharing under interconnectivity and interoperability criteria. A smart substation secondary system with complex functional descriptions is taken as the research object. First, a structural model of intelligent electronic devices (IEDs) is proposed which meets the interconnectivity requirements. Then, a functional model of IEDs with built-in algorithms for secondary business in power systems is proposed, as well as power communication protocol models which meet the interoperability requirements under IEC 61850 standard. Furthermore, the IED function in the node domain and data exchange between IEDs in the network domain are achieved, through the state design in the process domain. Finally, taking a typical 220 kV substation line current protection as an example, the entire process of protection setting modification and protection actions after a fault occurs are simulated by correlating the operating status of the power primary system, verifying the correctness of the proposed simulation models.

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    Neural Branching Power-Computation Network Fast Optimization Method Considering Computing Demand Response
    ZHANG Lei, LI Ran, TANG Lun, CHEN Sijie, ZHAO Shizhen, SU Fu
    2025, 59 (11):  1592-1602.  doi: 10.16183/j.cnki.jsjtu.2023.616
    Abstract ( 1366 )   HTML ( 2 )   PDF (2004KB) ( 396 )   Save

    The rapid development of data centers makes it possible for them to participate in power system dispatching as demand response. By dispatching the computing resources in data centers between regions, it is possible to achieve energy saving, emission reduction, and cost saving. However, considering the demand response of data center computing resources in power system dispatching faces the problem of insufficient computing speed. To address this issue, a neural branching power-computation network fast optimization method considering computing demand response is proposed. First, a unit commitment double-layer model considering computing power resource demand response is established. Then, the graph convolutional neural network and the branch and bound method are combined and applied to the double-layer model. Through historical data training, the neural branching power-computation network fast optimization method considering computing demand response has the ability to quickly determine the order of branch and bound variables and minimize the number of iterations, which significantly improves the solution speed and realizes the fast solution of unit combination demand response considering data center computing resources. The performance of the proposed method is verified in the simulation scenario of “east data, west computing” project. The proposed method achieves an average solution time reduction of 39.1% compared to the pseudo-cost branching algorithm, 38.1% compared to the commercial solver CPLEX, and 13.5% compared to the machine learning-based optimization acceleration algorithm Extratrees, the average solution time is reduced by 13.5%. In addition, the system coordinated dispatching frequency is increased from 1 time/h to 4 times/h, and the maximum potential reduction in wind curtailment of the total wind power generation during 24 h accounts for 17.42%.

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    Collaborative Optimization Scheduling Method for Active Distribution Networks Considering Dispatchable Backup Batteries of 5G Base Station and Soft Open Point
    GAO Chong, DUAN Yao, CHENG Ran, CHEN Peidong, ZHOU Shucan, ZHANG Shenxi, CHEN Weilin, LIU Zhiwen
    2025, 59 (11):  1603-1617.  doi: 10.16183/j.cnki.jsjtu.2024.020
    Abstract ( 1151 )   HTML ( 1 )   PDF (4061KB) ( 361 )   Save

    As the proportion of distributed generation, mainly wind turbine generation and photovoltaic, in terminal energy consumption increases, it is of great significance to fully utilize the flexibility resources within power grids and enhance the regulation capability of active distribution networks (ADN). To this end, an ADN collaborative optimization scheduling method is proposed considering dispatchable backup battery of 5G base station (BS) and soft open point. First, an analysis of the power consumption model of 5G BS is conducted, leading to the establishment of a backup battery capacity evaluation model which considers the communication load of 5G BS and the reliability of ADN nodes. Based on this and taking the minimization of the comprehensive operating cost of ADN as the objective function, considering the uncertainty of wind power, photovoltaic output, and load demand, an ADN collaborative optimal scheduling model based on chance constraints is developed. A second-order cone relaxation and a chance-constrained determinization approach based on Latin hypercube sampling are employed to enhance the solution efficiency of the model, which transforms the model into a mixed-integer second-order cone programming problem. Finally, the feasibility and effectiveness of the proposed method are verified by the IEEE 33-bus ADN case.

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    Low-Carbon Economic Dispatch of Energy Distribution Network in Synthetic Ammonia Park Considering Hydrogen Production by Water Electrolysis
    LI Haoran, SUN Hongbin, XUE Yixun, CHANG Xinyue, SU Jia
    2025, 59 (11):  1618-1624.  doi: 10.16183/j.cnki.jsjtu.2024.010
    Abstract ( 813 )   HTML ( 1 )   PDF (965KB) ( 157 )   Save

    As a typical chemical industrial park, the coal to hydrogen ammonia synthesis park relies on fossil fuels such as coal, resulting in huge carbon emissions and difficulties in green and low-carbon transformation. As a clean and nonpolluting hydrogen production method, hydrogen production by water electrolysis has been developing quickly in recent years,which provides a probability for low-carbon operation of hydrogen to ammonia chemical industry parks. In this paper, a low-carbon operation framework of the energy distribution network in the synthetic ammonia park is proposed. Taking the traditional coal to hydrogen ammonia synthesis park as an example, the roof photovoltaic, electric energy storage, and hydrogen system are introduced to construct the coal-electricity-hydrogen-heat coupling energy distribution network in the chemical industry park based on coal to hydrogen and hydrogen to ammonia equipment, the original power system, and heating system, so as to realize the multi-energy complementary operation and reduce the carbon emission. Then, a model including hydrogen source, hydrogen load, energy storage system, and heat source is established. The economic dispatch model of the energy distribution network in the chemical industrial park is developed and solved to minimize the operation cost and carbon emission of the park and meet the operational constraints of the park. Finally, the case study shows that the proposed method can effectively reduce the operation cost and carbon emission of the park.

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    Information Gap Decision Theory-Spectrum Clustering Typical Scenario Generation Considering Source Load Uncertainty
    ZHANG Jiamin, CAI Ye, TANG Xiafei, TAN Yudong, CAO Yijia, LI Junxiong
    2025, 59 (11):  1625-1636.  doi: 10.16183/j.cnki.jsjtu.2023.580
    Abstract ( 1212 )   HTML ( 3 )   PDF (2201KB) ( 580 )   Save

    The high proportion of new energy and dynamic load brings significant bidirectional uncertainty of source and load to power system. The strong uncertainty makes scheduling planning face high dimensional decision space and increases planning risk. Therefore, an information gap decision theory (IGDT)-spectral clustering typical scenario generation method considering the uncertainty of source load is proposed to provide a more accurate planning scenario for the determination of the operation mode of multi-source joint systems. First, the source load uncertainty can be quantified effectively by the IGDT theory without considering the uncertain quantitative probability distribution. The source load fluctuation range is described using the IGDT robust model and the IGDT chance model, and the original scenario representing each uncertainty situation is generated using the Latin hypercube sampling method to ensure the adequacy and accuracy of sample space. Then, to address the huge scale of the original scenario caused by the uncertainty of the source load, a spectral clustering method considering the adjustment ability of the system is introduced to mine the feature vectors of different source load fluctuations which have an important impact on the scheduling decision to reduce the complex original scenario set to a representative typical scenario of the source load. Finally, the simulation analysis of the actual system and operation data of a provincial power grid shows that compared with the traditional spectral clustering method, the proposed method generates four more typical scenarios after considering the bidirectional uncertainty of source load, the comprehensive average Pearson correlation coefficient is increased by 8.76%, the comprehensive average Euclidian distance is reduced by 43.48%, and the clustering scenario is more similar to the actual scenario.

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    An Evolutionary Game Approach to Incentive Mechanism of Vehicle-to-Grid
    PAN Yi, WANG Mingshen, MIAO Huiyu, YUAN Xiaodong, HAN Huachun
    2025, 59 (11):  1637-1646.  doi: 10.16183/j.cnki.jsjtu.2023.603
    Abstract ( 1553 )   HTML ( 2 )   PDF (4079KB) ( 2213 )   Save

    Electric vehicles (EVs) can provide significant support for the flexible operation of power systems, in which vehicle-to-grid (V2G) mode is an important way for EVs to participate in the frequency and voltage regulation of power grids. However, the commercialization of V2G has experienced slow progress to date, and the lack of an effective market operation mechanism makes it difficult for large-scale EVs to participate in the ancillary services of the grid. Therefore, a novel evolutionary game model is proposed with the participation of the electricity regulatory commission, power grid company, and EVs and the impact of the strategic choices of the three parties on the operation of the V2G market is explored to identify the subsidy and pricing mechanisms for the government to facilitate the long-term evolution of the V2G. First, replicator dynamic equations for the game are established to investigate the stability of multiple strategy equilibrium points in the three-party evolutionary game. Then, the Lyapunov stability theory is employed to analyze the stability of these equilibrium points and to determine the subsidy amount to promote V2G development. Next, a simulation analysis is conducted on the actual electricity price data from Shanghai in China, which quantitatively identified the government subsidy coefficient range and electricity price range to incentivize EV participation in the V2G model. The simulation results provide theoretical support for the electricity regulatory commission and power grid company in formulating subsidy and pricing strategies.

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    Transaction Mechanism of Medium- and Long-Term Continuous Centralized Auction Considering Available Transmission Capacity
    YANG Kaitao, LUO Xi, XUE Bike, GUO Yanmin, FU Xueqian
    2025, 59 (11):  1647-1659.  doi: 10.16183/j.cnki.jsjtu.2023.628
    Abstract ( 1017 )   HTML ( 3 )   PDF (2682KB) ( 194 )   Save

    With the advancement of the construction of the national unified electricity market system, the intra-provincial medium- and long-term electricity market adopts the trading mode of unrestricted clearance before security assessment, which is unable to meet the needs of the future medium and long-term market continuous market opening and high-frequency trading requirements. Therefore, this paper establishes a continuous centralized bidding trading mechanism and clearing model for the medium- and long-term electricity market. The continuous opening of the medium and long-term market is achieved through daily continuous trading, and the available transmission capacity is considered in the clearing model to improve the enforceability of trading results. Then, based on the marginal clearing price, it establishes a Marginal-Vickrey-Clarke-Groves mechanism to meet the balance of payments, which quantifies the contribution of market entities in the transaction through market efficiency coefficient, and distributes the market value, promoting the market participants to declare the true price information. Finally, based on medium- and long-term as well as spot electricity market trading data from a certain province in central China, a simulation analysis is conducted on the transaction data including three power generation enterprises and five power users. The clearing price is 399.64 yuan/(MW·h), which verifies the effectiveness and feasibility of the mechanism.

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    Dynamic Modeling and Optimal Defense Strategy Against DdoS Attacks on Power Advanced Metering Infrastructure
    LIANG Haolan, LIU Dongqi, ZENG Xiangjun, ZHANG Qiong, ZHANG Tao, WANG Rui
    2025, 59 (11):  1660-1674.  doi: 10.16183/j.cnki.jsjtu.2024.006
    Abstract ( 1060 )   HTML ( 0 )   PDF (3580KB) ( 241 )   Save

    Advanced metering infrastructure (AMI) is a key component of new power systems. However, the wide application of heterogeneous communication networks and intelligent terminals makes it vulnerable to cyber-attacks. Therefore, this paper studies the dynamic modeling and optimal defending strategy of AMI network under distributed denial-of-service (DDoS) attacks. First, the propagation path of DDoS attack in AMI network is analyzed. Combined with the complex network theory and the SEIR epidemic model, a state evolution model is established to describe the state evolution of nodes after DDoS attack and the propagation mechanism and attack tolerance level of DDoS attack in AMI network are analyzed. Then, a defending strategy is proposed with the goal of minimizing defense losses and costs to flexibly optimize the deployment of defense resources. Finally, the effectiveness of the proposed strategy is verified by using a large number of numerical simulations in two different AMI network structures.

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    Steady-State Power Flow Calculation of Power System with Hybrid Power Flow Controller
    WU Xi, GUAN Chenhao, CAI Hui, WANG Rui, CHEN Xi
    2025, 59 (11):  1675-1683.  doi: 10.16183/j.cnki.jsjtu.2024.008
    Abstract ( 293 )   HTML ( 1 )   PDF (1159KB) ( 139 )   Save

    Hybrid power flow controller (HPFC) not only achieves the same control functions, but also has lower cost and broad application prospects compared with unified power flow controller (UPFC). However, the complex structure of the HPFC device and the difficulty in accurately and rapidly determining its voltage control parameters make it challenging for verifying the capacity of the HPFC. To address the above problems, a steady-state mathematical model for HPFC applicable to power flow calculations of power systems is proposed. Initially, an equivalent model for HPFC with additional nodes is established, and the power injection model for HPFC is derived by applying the superposition principle. Subsequently, an equivalent voltage source is delineated within HPFC, and the voltage of the equivalent voltage source is computed based on control objectives. Then, the voltage control parameters for HPFC are calculated according to relevant voltage configuration rules. Finally, data exchange between MATLAB and PSD-BPA software is achieved by utilizing a data exchange interface, facilitating power flow control calculations for large power grids incorporating HPFC. The accuracy and effectiveness of the proposed HPFC model and calculation method are verified by simulated examples.

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    Micro-Service Scheduling Model and Optimization for Protection and Control of Distribution Network Considering Virtualization Delay
    HU Kaiqiang, CAI Zexiang, CAI Yu, QU Jing, LIU Yuanyuan
    2025, 59 (11):  1684-1693.  doi: 10.16183/j.cnki.jsjtu.2023.540
    Abstract ( 238 )   HTML ( 0 )   PDF (1361KB) ( 124 )   Save

    The current research on distribution network terminals based on micro-service and container architecture overlooks the impact of virtualization delay in micro-service scheduling, restricting its application in scenarios with high real-time requirements such as protection and control services. To address this limitation, a micro-service scheduling framework and strategy is proposed for protection and control terminals in distribution networks based on micro-service and container architecture. Initially, an analysis is conducted on the delay performance requirements of protection and control services in the terminal and the impact of virtualization delay, leading to the formulation of a protection and control micro-service scheduling framework. Subsequently, a protection and control micro-service scheduling model is established, encompassing micro-service, delay, and metrics models. A micro-service scheduling strategy based on queue state transitions is then proposed. Finally, extensive case simulations are conducted, where the effectiveness of the proposed scheduling strategy is validated and further optimization of the scheduling strategy is performed. The results indicate that the scheduling strategy proposed can effectively avoid the impact of virtualization delay, and the adoption of first-come-first-serve (FCFS) algorithm achieves better overall performance.

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    A Coordinated Control Scheme for Fast Frequency Regulation of Thermal Power Units Based on Flexibility Transformation
    ZHANG Jianhua, YAO Yi, ZHAO Si, WANG Yongyue
    2025, 59 (11):  1694-1706.  doi: 10.16183/j.cnki.jsjtu.2023.602
    Abstract ( 412 )   HTML ( 1 )   PDF (3127KB) ( 141 )   Save

    With the popularization of renewable energy in the power system, improving the primary frequency regulation capability of thermal power units to suppress grid frequency fluctuations is currently a difficult problem to solve. However, the flexibility transformation of thermal power plants plays an important role in ensuring the safe and stable operation of the power grid. Traditional thermal units use coordinated control system (CCS) and digital electro-hydraulic control systems (DEH). With the transformation of condensate throttling (CT) and high-pressure heaters’ feedwater bypass (HPHFB), the fast frequency regulation characteristics of thermal units can also be improved. Therefore, in this paper, a new frequency regulation strategy is proposed by combining CCS, DEH, CT, and HPHFB. Additionally, gravitational search algorithm and fuzzy gain scheduling control strategy are combined to suit multiple operating conditions of thermal units to improve the fast frequency regulation performance of thermal units. The simulation results verify the effectiveness of the improved control strategy.

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    Sub-Synchronous Oscillations Caused by Interaction of a PMSG-Based Wind Farm with a Four-Terminal MMC-HVDC Grid
    BAI Feng, CHEN Wuhui, QIN Wei
    2025, 59 (11):  1707-1719.  doi: 10.16183/j.cnki.jsjtu.2023.574
    Abstract ( 292 )   HTML ( 0 )   PDF (2680KB) ( 312 )   Save

    Multiple occurrences of sub-synchronous oscillations have been observed following the integration of a wind farm into a four-terminal ring-structured modular multilevel converter (MMC)-high-voltage direct current (HVDC) grid in China. To address repeated oscillation, this paper develops a small-signal model of a direct-drive wind farm integrated into the four-terminal MMC-HVDC system, and reveals the underlying mechanism of the sub-synchronous oscillations observed in the actual project. It is found that a direct-drive wind farm is closely coupled only with the directly connected MMC, while other MMCs have little impact on sub-synchronous oscillation modes. Therefore, when studying the sub-synchronous oscillation issues involving the interaction between the wind farm and the flexible DC system, a simplified model can be established using a single-ended flexible DC system directly connected to the wind farm, ignoring the influence of other MMCs. It is also found that in the system where a direct-drive wind farm interacts with a directly connected MMC, both active power-coupled sub-synchronous oscillation modes and reactive power-coupled sub-synchronous oscillation modes coexist. As the output power of the wind farm gradually increases, the damping of the active power-coupled sub-synchronous mode increases, while the damping of the reactive power-coupled sub-synchronous mode decreases, reproducing the onsite phenomenon where an increase in wind farm active power aggravates sub-synchronous oscillations. The smaller the integral gain of the outer loop of the wind farm’s reactive power controller and the proportional gain of the phase-locked loop (PLL), and the larger the integral gain of the q-axis component of the AC voltage outer loop at the wind farm-side converter station, the more stable the reactive power-coupled oscillation mode becomes. By optimizing these parameters, the risk of system instability can be reduced. A simulation model of a direct-drive wind farm connected to a four-terminal flexible DC grid was built using the electromagnetic transient simulation software PSCAD (power systems computer aided design), and the correctness of the above theoretical analysis was verified.

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    Optimal Planning of Electric Vehicle Charging Stations Combined with Battery Energy Storage Systems Considering Driving Characteristics
    HAN Yiming, HE Bin, YANG Bo, LI Jiale
    2025, 59 (11):  1720-1731.  doi: 10.16183/j.cnki.jsjtu.2023.629
    Abstract ( 386 )   HTML ( 1 )   PDF (2453KB) ( 204 )   Save

    With the continuous increase in the number of electric vehicles (EVs) in China, EV charging stations (EVCS) are becoming extensively connected to distribution networks to meet the growing charging demand, which poses unprecedented challenges to the stability, safety, and economy of distribution networks. To reduce the impact of EVCS on distribution networks while ensuring the interests of investors and EV users, this paper proposes a multi-objective planning model of EVCS combined battery energy storage system (BESS) which considers the behavioral characteristics of EV users, aiming to minimize the comprehensive cost of EVCS and BESS, waiting time of users, and system voltage fluctuations to achieve the best balance between the economy and stability by planning for EVCS and BESS. Meanwhile, the non-dominated sorting genetic algorithm III (NSGA-III) is used to verify the model on the extended IEEE-33 node testing system and the university town in Chenggong, Kunming. The simulation results show that in the IEEE-33 node test system, compared with the case without BESS configuration, the voltage fluctuation and system network loss decreases by 36.73% and 35.41%, respectively, effectively improving the stability and economy of the distribution network.

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    System Dynamics Modeling Analysis of Urban Power System Evolution Path
    YE Jun, HE Yibing, LI Xianfeng, YAN Guocan, YAN Lei
    2025, 59 (11):  1732-1741.  doi: 10.16183/j.cnki.jsjtu.2024.009
    Abstract ( 330 )   HTML ( 0 )   PDF (2441KB) ( 189 )   Save

    To investigate the evolution path of urban power system supply structures, an analysis is conducted on the factors influencing the installed capacity of various power source types in urban power systems, and a system dynamics model for the urban power system supply structure is developed, which includes modules for power balance, thermal power development, distributed photovoltaic development, centralized wind and photovoltaic development, and new energy carrying capacity. In the modeling process, the symbolic regression method is used to accurately set the model parameters, with a focus on the impact of low-carbon policies on various types of power sources, as well as the feedback effect of renewable energy carrying capacity on the installed capacity of renewable energy.The changing trends of various types of power capacity, the proportion of new energy access, and the new energy carrying capacity in future urban power systems are obtained by differentiated simulations in low-carbon policy scenarios. The simulation results indicate that low-carbon policies contribute to the development of new energy and the achievement of “dual-carbon” goals, promoting the green and low-carbon transformation of urban energy systems. However, excessive policy intensity may lead to insufficient renewable energy carrying capacity in urban power systems, causing problems in the absorption of new energy.

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    Resilience Planning of Power Distribution System Emergency Resources Considering Multiple Uncertainties Under Heavy Rain Disasters
    SHEN Zeyuan, ZHAO Haibo, WANG Chao, LI Jia, WANG Yao, LI Qi
    2025, 59 (11):  1742-1753.  doi: 10.16183/j.cnki.jsjtu.2023.594
    Abstract ( 397 )   HTML ( 2 )   PDF (2250KB) ( 649 )   Save

    In recent years, the impact of heavy rain disasters on the reliable power supply of distribution networks has become increasingly prominent, and it is extremely challenging to ensure the supply of important loads in the case of large-scale and multi-point serious faults. Rational deployment of emergency resources can help reduce the loss of important loads in the system, thereby improving the resilience of the distribution system. Therefore, a resilience planning method for emergency resources in the distribution system considering multiple uncertainties under heavy rain disasters is proposed in this paper, and a two-tier planning model for the resilience improvement of the distribution system is established considering the emergency power supply and emergency energy storage, with the upper model aiming to minimize the net cost of investment cost and load loss, while the lower model aiming to minimize the comprehensive load loss in multiple island scenarios. Additionally, a stochastic simulation generation method for multi-island scenarios in distribution network under heavy rain disasters is proposed, and a scene reduction method based on clustering algorithm is proposed based on the probability and severity of each scenario to serve the scene screening of the lower-level optimization model. The analysis of the actual 62-node system of distribution network shows that the proposed method can effectively reduce the load loss of the system in disasters while considering investment economy, and improve the power supply capacity of the distribution network for important loads.

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    Parallel Computation and Optimization of Proton Exchange Membrane Fuel Cell Models
    LIU Ke, HAO Liang, GENG Jun, CHEN Xun, LU Wei
    2025, 59 (11):  1754-1762.  doi: 10.16183/j.cnki.jsjtu.2023.636
    Abstract ( 372 )   HTML ( 1 )   PDF (4170KB) ( 288 )   Save

    To achieve highly efficient and precise simulation of proton exchange membrane fuel cells (PEMFCs) and stacks, this paper develops a three-dimensional coupled one-dimensional hybrid dimension modeling strategy based on the Fluent solver and conducts an in-depth analysis of the impact of the Fluent built-in global summations macro PRF_GRSUM on the parallel solving efficiency of fuel cell simulation. It also proposes two new parallel strategies including the data compression synchronization method and the data filter marker method, based on the data coupling characteristics of the hybrid dimension model. Then, this paper describes the principles and processes of three data synchronization methods in detail, and investigates the impact of these methods on the solving efficiency of parallel computation of PEMFC models. The results show that the data filter marker method can achieve an acceleration ratio up to 112.5 times compared with PRF_GRSUM macro when simulating a PEMFC stack with a hundred cells.

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