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Table of Content

    28 March 2025, Volume 59 Issue 3 Previous Issue   
    New Type Power System and the Integrated Energy
    Parameter Control of Adaptive Bistable Point Absorber Wave Energy Converter in Irregular Waves
    LI Yang, ZHANG Xiantao, XIAO Longfei
    2025, 59 (3):  293-302.  doi: 10.16183/j.cnki.jsjtu.2023.309
    Abstract ( 139 )   HTML ( 1 )   PDF (4987KB) ( 227 )   Save

    Although the adaptive bistable wave energy generation device solves the problem that the bistable system may be difficult to cross the barrier when the amplitude of the incident wave is small, its efficiency can still be improved. Previous studies have proved that the change of the parameters of the device will have a great impact on its performance, and the optimal device parameters are closely related to the spectral peak frequency at a given time. Therefore, in the control study of the device, a control scheme is designed and the device parameters are adjusted accordingly in order to improve efficiency assuming that the peak frequency within a period of time is predictable. In this study, three control parameters are selected, and the optimal device parameter library with different spectral peak frequencies is determined by simulation calculation. The control module is then added to the simulation program to control the parameters by interpolation. The results show that the device with variable parameter control improves energy capture efficiency.

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    DC-Bus Voltage Oscillation Suppressor Based on Active Capacitor and Its Control Method
    YANG Jipei, YANG Ling, WEI Maohua
    2025, 59 (3):  303-312.  doi: 10.16183/j.cnki.jsjtu.2023.327
    Abstract ( 109 )   HTML ( 0 )   PDF (8081KB) ( 121 )   Save

    The constant power load (CPL) in a DC microgrid can reduce the effective damping of the system, resulting in high frequency voltage oscillations on the DC bus, which threatens the safe and stable operation of the system. To address this issue, this paper proposes a DC-bus voltage oscillation suppressor based on an active capacitor and its control method. The oscillation suppressor is connected in parallel to the DC bus, enabling direct interaction with the DC bus. The energy storage capacitor in the oscillator suppressor effectively stores the transient energy generated by voltage oscillations, thereby reducing the amplitude of voltage oscillation and improving the voltage stability of the bus. The voltage of the power supply in the oscillation suppressor adapts to the voltage of the DC bus, allowing for stable operation in the face of load changes in the system. The design offers advantages such as plug-and-play functionality, strong applicability, and flexible control. In addition, by analyzing the operating mode and mechanism of the oscillation suppressor, a small signal model is established, and the influence of controller parameters on the stability and dynamic performance of the suppressor is analyzed, based on which the controller parameter optimization scheme is proposed. Finally, the effectiveness of the oscillatory suppressor is validated through the experimental results.

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    Influence of DC-Bus Voltage on Synchronization Stability of Grid-Following Converters
    SI Wenjia, CHEN Junru, ZHANG Chenglin, LIU Muyang
    2025, 59 (3):  313-322.  doi: 10.16183/j.cnki.jsjtu.2023.321
    Abstract ( 156 )   HTML ( 0 )   PDF (2943KB) ( 195 )   Save

    With the increasing penetration of new energy sources and the development of new power systems, grid-following converter (GFL) plays a crucial role in maintaining the stability of power systems. However, existing transient stability analyses of GFLs assume that the direct current (DC) side behaves as a constant-voltage source, neglecting the effects of DC-bus voltage control. This paper aims to investigate the transient instability mechanism of GFL considering DC-bus voltage control. First, a transient synchronous stability model considering DC voltage control is established, followed by an analysis of the transient synchronous stability of GFL under DC-bus voltage control. The findings indicate that DC voltage control increases the active current reference value and decreases the equivalent damping of the GFL, which in turn reduces its transient synchronous stability of GFL. By increasing the proportional coefficient or reducing the integral coefficient of DC-bus voltage control, transient synchronous stability can be appropriately improved. Finally, the theoretical analysis is validated through MATLAB/Simulink simulations.

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    Optimization of Frequency Control Parameters of Wind Farms Considering Inertia Security Requirement
    LI Hongxin, ZHONG Zuhao, LU Yi, WEN Yunfeng
    2025, 59 (3):  323-332.  doi: 10.16183/j.cnki.jsjtu.2023.380
    Abstract ( 76 )   HTML ( 0 )   PDF (1699KB) ( 91 )   Save

    The inertia and frequency regulation resources in power systems with a high proportion of renewable energy are scarce, resulting in prominent problems of frequency stability. To address these problems, this paper incorporates the potential frequency support capability of wind farms into the frequency control measures of the power grid, and proposes an optimization method for wind farm control parameters that considers the security requirements of system inertia. After a credible disturbance, the system inertia security requirement that meets the frequency stability constraint is calculated based on the transient frequency index limit. Then, the primary frequency regulation capability that wind farms can provide under different wind conditions is modeled with the goal of minimizing the adjustment of wind farm virtual inertia and frequency droop parameters under disturbances, and a dynamic optimization model for wind farm frequency control parameters is established. Finally, the frequency control parameters are calculated and numerical tests are conducted on the modified IEEE RTS-79 system. The results show that the proposed parameter optimization method effectively improves the transient frequency response process of wind farms, which helps enhance the frequency stability margin of the system.

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    Self-Adaptive Secondary Frequency Regulation Strategy Based on Distributed Model Predictive Control
    CAO Yongji, ZHANG Jiangfeng, WANG Tianyu, ZHENG Keke, WU Qiuwei
    2025, 59 (3):  333-341.  doi: 10.16183/j.cnki.jsjtu.2023.352
    Abstract ( 131 )   HTML ( 0 )   PDF (3126KB) ( 541 )   Save

    To address the issues of reduced adaptability of secondary frequency regulation caused by changes in power system parameters, a self-adaptive secondary frequency regulation strategy based on distributed model predictive control (DMPC) is proposed. First, a model of a multi-area interconnected power system is built. Based on the frequency response trajectory, a parameter identification model for each area of the system is established. Then, the recursive least square method is used to solve the parameter identification model and update the parameters of each area online. Additionally, with the objective to minimize the area control error (ACE), DMPC is adopted to optimize the power of generators for secondary frequency regulation. Finally, a case study is conducted to demonstrate the effectiveness of the proposed strategy.

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    Design of Two-Stage Electricity Spot Market Model Considering Carbon Emission Trading
    LIU Changxi, QI Guomin, WANG Jicheng, LI Tianye, YANG Jian, LEI Xia
    2025, 59 (3):  342-353.  doi: 10.16183/j.cnki.jsjtu.2023.299
    Abstract ( 105 )   HTML ( 0 )   PDF (1934KB) ( 164 )   Save

    To promote the process of carbon emission reduction in the electric power industry and achieve the goal of “carbon peaking and carbon neutrality”, the construction of a unified national power market system is being accelerated. A two-stage market clearing model considering load participation in carbon trading is proposed to reduce carbon emissions and facilitate clean energy substitution in the electricity sector. First, an initial carbon quota allocation method for thermal power units based on zero sum gains-data envelopment analysis is introduced, and the electricity market clearing model considering carbon trading is established. Then, based on the market clearing results from the first stage, the new energy consumption of loads is determined using the power flow tracing theory, and the Chinese certified emission reduction (CCER) is calculated. Following CCER carbon offset rules, the second stage of carbon emission trading is initiated, and the secondary electricity market subject to carbon emission constraints, is cleared based on the carbon trading results. Finally, an analysis using the improved IEEE 30-bus system is conducted to validate the effectiveness of the proposed market model. The results show that the proposed model not only helps reduce the carbon emissions from thermal power units but also increases the market share of new energy consumption and lowers average electricity prices. Additionly, the model provides a viable scheme for the large-scale marketization consumption of new energy.

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    Impact Mechanism Analysis of Carbon Price Uncertainty on Power System Dispatch
    WU Jing, LIU Xuanyu, LI Xiang, QI Xiaoyan, LI Chengjun, ZHANG Zhong
    2025, 59 (3):  354-364.  doi: 10.16183/j.cnki.jsjtu.2023.313
    Abstract ( 115 )   HTML ( 0 )   PDF (1973KB) ( 129 )   Save

    With the launch of the national carbon market, electricity industry is expected to play an important role in the carbon market. However, the impact mechanism of carbon market on low-carbon scheduling in power systems remains underexplored and warrants further study. This paper investigates the impact of the annual clearing mechanism in the carbon market on the day-ahead dispatch of power systems. A non-parametric statistical model is developed to annual represent the carbon market price. Considering the uncertainty in carbon price, this paper proposes several low-carbon economic dispatch methods for power systems with different risk preferences, including conditional value at risk (CVaR) optimization, expected value optimization, and robust optimization. The impact of carbon price uncertainty on day-ahead dispatch is analyzed through a mathematical optimization framework. The results show that, compared with traditional economic dispatch models, the low-carbon economic dispatch model can reduce carbon emissions by 8.41%. Additionally, the more risk-averse the approach to carbon pricing, the lower the carbon emissions. The smaller carbon quota coefficient further promotes low-carbon dispatch through the carbon market. Finally, this paper identifies conditions under which carbon capture systems become profitable, specifically, when the carbon price in the market exceeds the product of the unit generation cost and the energy consumption coefficient of carbon capture.

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    Multi-Agent Coordinated Dispatch of Power Grid and Pumped Hydro Storage with Embedded Market Game Model
    LOU Wei, HU Rong, YU Jinming, ZHANG Xipeng, FAN Feilong, LIU Songyuan
    2025, 59 (3):  365-375.  doi: 10.16183/j.cnki.jsjtu.2023.354
    Abstract ( 149 )   HTML ( 0 )   PDF (2651KB) ( 383 )   Save

    In the context of large-scale energy storage stations, such as pumped storage, participating in both spot trading and grid scheduling, it is difficult for the grid to directly access the consumption of renewable energy in the spot market. In this regard, the influence of spot electricity trading on the pumped storage scheduling is considered and a multi-agent scheduling method with an embedded market game model is proposed. First, combined with the power spot market clearing model, with the objective of maximizing the benefits of the pumped storage power station in the spot market, a strategy for the pumped storage power station to participate in the spot trading of electric energy is developed. Then, combined with the two-part electricity price policy, the capacity allocation and power dispatching strategy of the grid operator about the pumped storage is formulated to minimize grid operating costs and the amount of renewable energy discarded in the entire grid. To formulate the proposed scheduling strategy, a bi-level optimization problem with an embedded game model is solved: the decision-making problem of the pumped storage power station participating in the electric energy spot market, and the optimization with the embedded marketing game model of capacity allocation and power scheduling strategy about pumped storage. The decision-making problem of pumped storage in the spot market follows a Stackelberg game model, which is integrated into the optimization problem of pumped storage capacity allocation and power scheduling strategy via the strong dual theory. The embedded bi-objective problem is solved by using the NSGA-II algorithm. Finally, based on the data from a pumped storage power station in East China, a simulation model is built to verify the effectiveness of the proposed method. The test results show that the proposed method can effectively coordinate the decision-making of direct grid dispatching and pumped storage participation in the electric energy spot market, enhancing the economic benefits of pumped storage, reducing the operating cost of the grid, and improving the consumption of renewable energy.

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    SOC Balancing Strategy for Distributed Energy Storage Units in Isolated DC Microgrids Considering Capacity Differences
    WEI Maohua, YANG Ling, WENG Liangtao, YANG Jipei, CHEN Yongqiao
    2025, 59 (3):  376-387.  doi: 10.16183/j.cnki.jsjtu.2023.271
    Abstract ( 120 )   HTML ( 0 )   PDF (13553KB) ( 32 )   Save

    In an islanded DC microgrid, there is a problem of slow state of charge (SOC) equalization between distributed energy storage units (DESUs) with different capacities. To address this issue, a fast SOC equalization strategy for DESUs, which accounts for capacity differences, is proposed. First, the SOC equalizer constructs a relationship between the droop coefficient and SOC using a power function. By selecting appropriate equalization adjustment coefficients, the droop coefficient can be adaptively controlled, thereby accelerating SOC equalization. Then, the virtual droop equalizer is introduced to mitigate the impact of line impedance on current distribution accuracy by simply adjusting the PI controller, which improves the precision of current distribution. Additionly, the selection range of control parameters for this strategy is determined by using a system stability analysis. Finally, a DC microgrid hardware-in-the-loop experimental platform is developed. The experimental results, compared with those from existing literature under various operating conditions, demonstrate that the proposed control strategy improves the speed of SOC equalization and realizes the rapid recovery of bus voltage.

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    Power Coordination Strategy for Hybrid Energy Storage in AC/DC Microgrids Based on Virtual Impedance-Fuzzy Algorithm
    ZHAO Yongxi, GAO Pengchao, FAN Hong
    2025, 59 (3):  388-399.  doi: 10.16183/j.cnki.jsjtu.2023.308
    Abstract ( 91 )   HTML ( 0 )   PDF (5007KB) ( 350 )   Save

    A hybrid energy storage system consisting of batteries and supercapacitors can be integrated into the microgrid, to mitigate the power fluctuations on both sides of the source and load sides, which is a common issue in AC/DC hybrid microgrids. This paper proposes a power coordination strategy for hybrid energy storage in AC/DC microgrids based on virtual impedance and fuzzy algorithm optimization. First, the initial power allocation for hybrid energy storage is autonomously determined using composite virtual impedance. Then, a comprehensive analysis is conducted to assess the influence of composite virtual impedance parameters and filtering time constant on power distribution. Based on this, a power distribution adjustment method is proposed, and fuzzy control rules are derived. The fuzzy algorithm is used to adaptively optimize the output power of hybrid energy storage based on the state of charge and the power demond on the supercapacitor. Finally, the power in the AC/DC interlinking converter is adaptively adjusted to enhance the regulation ability of hybrid energy storage. The simulation results in MATLAB/Simulink experiments demonstrate that the proposed strategy can effectively suppress power fluctuations on both the source and load sides, eliminate DC bus voltage deviation, and prevent the issues such as over-charging and over-discharging of supercapacitors, thereby extending the service life of the equipment.

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    Online Steady-State Scheduling of New Power Systems Based on Hierarchical Reinforcement Learning
    ZHAO Yingying, QIU Yue, ZHU Tianchen, LI Fan, SU Yun, TAI Zhenying, SUN Qingyun, FAN Hang
    2025, 59 (3):  400-412.  doi: 10.16183/j.cnki.jsjtu.2023.344
    Abstract ( 164 )   HTML ( 0 )   PDF (4192KB) ( 1163 )   Save

    With the construction of new power systems, the stochasticity of high-proportion renewable energy significantly increases the uncertainty in the operation of the power grid, posing severe challenges to its safe, stable, and economically efficient operation. Data-driven artificial intelligence methods, such as deep reinforcement learning, are becoming increasingly important for regulating and assisting decision-making in the power grid in the new power system. However, current online scheduling algorithms based on deep reinforcement learning still face challenges in modeling the high-dimensional decision space and optimizing scheduling strategies, resulting in low model search efficiency and slow convergence. Therefore, a novel online steady-state scheduling method is proposed for the new power system based on hierarchical reinforcement learning, which reduces the decision space by adaptively selecting key nodes for adjustment. In addition, a state context-aware module based on gated recurrent units is introduced to model the high-dimensional environmental state, and a model with the optimization objectives of comprehensive operating costs, energy consumption, and over-limit conditions is constructed considering various operational constraints. The effectiveness of the proposed algorithm is thoroughly validated through experiments on three standard test cases, including IEEE-118, L2RPN-WCCI-2022, and SG-126.

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    Detection of Foreign Bodies in Transmission Line Channels Based on Fusion of Swin Transformer and YOLOv5
    XUE Ang, JIANG Enyu, ZHANG Wentao, LIN Shunfu, MI Yang
    2025, 59 (3):  413-423.  doi: 10.16183/j.cnki.jsjtu.2023.301
    Abstract ( 205 )   HTML ( 0 )   PDF (26717KB) ( 391 )   Save

    To address the challenges of complex detection background and poor detection performance for small targets, a transmission line channel security detection algorithm based on the fusion of window self-attention network and the YOLOv5 model is proposed. First, the Swin Transformer (S-T) is employed to optimize the backbone network, expanding the perception field of the model and enhancing its ability to extract effective information. Then, the adaptive spatial feature fusion (ASFF) module is improved to enhance the feature fusion ability of the model. Finally, considering the mismatch between the real frame and the predicted frame, the structural similarity intersection over union (SIoU) is introduced to optimize the boundary errors and improve the generalization ability of the model. The experimental results show that the model proposed achieves a multi-target intrusion detection accuracy of 90.2%, and with significant improvements in the detection of small targets. This approach better meets the requirements of foreign object detection in transmission line channels compared to other object detection algorithms.

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    Calculation Method for Underground Metal Corrosion Due to Stray Current Based on Ground Potential Distribution
    TANG Yuhang, YU Kun, ZENG Xiangjun, NI Yanru, CHENG Xinxiang, HAN Wei
    2025, 59 (3):  424-434.  doi: 10.16183/j.cnki.jsjtu.2023.334
    Abstract ( 95 )   HTML ( 0 )   PDF (11732KB) ( 185 )   Save

    Urban rail transit construction plays an important part in supporting the “dual carbon” goals and accelerating the development of new-type power system. However, stray currents generated during subway operations can lead to soil polarization and corrosion of buried metal pipelines. To analyze the impact of stray currents on buried metal pipelines, a method is proposed to calculate the corrosion current density of buried pipelines based on ground potential distribution. First, a long-line four-layer grounding network reflux model with multiple trains is established based on the actual subway traction power supply system, which enables the real-time dynamic calculation of stray current distribution and rail potential. Next, the rail potential distribution is treated as a line voltage source, which is integrated into the subway line model to calculate ground potential distribution. Then, a soil-pipeline circuit model including anti-corrosion coating is established to realize dynamic calculation of pipeline corrosion current density based on ground potential distribution. Finally, the influencing factors of the pipelines corrosion current density are studied, such as rail direct current (DC) resistance, transition resistance, and soil resistivity. The simulation results show that the pipeline corrosion current density is linearly related to rail DC resistance. When the transition resistance between the rail and the drainage network increases from 5 Ω·km to 50 Ω·km, the corrosion current density of the two buried pipelines reduces by 65.94% and 67.45%, respectively. Additionly, a higher soil resistivity has a certain inhibitory effect on stray current propagation, providing a degree of mitigation against corrosion.

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