28 February 2026, Volume 46 Issue 1
    

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  • An Adaptive Suppression Method for Subsynchronous Oscillation in VSC-HVDC Systems Based on Proximal Policy Optimization Algorithm
    WEI Bo, XUHonglei, HAN Jiexiang, LIU Zhidong, ZHOU Dengyu, HE Jianjun
    Journal of Northeast Electric Power University. 2026, 46(1): 1-9. https://doi.org/10.19718/j.issn.1005-2992.2026-01-0001-09
    Abstract ( ) Download PDF ( ) Knowledge map Save
    The Voltage Source Converter based High Voltage Direct Current （VSC-HVDC）system may experience subsynchronous oscillation （SSO）due to complex dynamic interactions within its internal control structure,which can lead to equipment damage or even trigger converter blocking.However,conventional SSO suppression strategies based on parameter tuning or additional damping controllers are often designed for specific operating conditions,making them ineffective under varying operating scenarios and potentially altering the intrinsic control characteristics of VSC-HVDC systems.To address these challenges,this paper proposes an adaptive SSO suppression method based on the Proximal Policy Optimization （PPO）algorithm.First,a state-space model of the VSC-HVDC system is established using the vector fitting method to identify the system's SSO modes from operational data.Then,an overall deep reinforcement learning framework for SSO suppression is developed,in which the suppression problem is formulated as a Markov Decision Process（MDP）and used to train the PPO network.Finally,guided by a reward function constructed from the system eigenvalue characteristics,the intelligent agent autonomously generates optimal control actions that enhance system damping performance.Time-domain simulation results verify the effectiveness and adaptability of the proposed method in suppressing SSO within the VSC-HVDC system.
  • Data-driven Voltage Security Situation Awareness for Power Grids with High Renewable Energy Integration
    GAO Song, ZHANG Haifeng, ZHANG Jiajun, DONG Yunchang, YUAN Xingi, YANG Deyou
    Journal of Northeast Electric Power University. 2026, 46(1): 10-16. https://doi.org/10.19718/i.issn.1005-2992.2026-01-0010-08
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    Addressing the challenges of complex and volatile power grid operation modes and the difficulty in accurate-ly perceiving voltage stability status following the large-scale integration of renewable energy sources,this paper proposes a data-driven voltage security situation reliable awareness method based on Variational Autoencoders （VAEs）.Building upon the mathematical expression of voltage sensitivity indices,a multi-dimensional time-series data-driven mathematical analytical model for voltage sensitivity is constructed and solved using the least-squares algorithm.To address the issue of excessive sensitivity estimation errors caused by outliers in measurement time-series data,which leads to low reliability in voltage situation awareness,unsupervised artificial intelligence technology is introduced.Specifically,an outlier localization and removal method based on VAEs is proposed,eliminating the primary cause of large sensitivity estimation errors at their source.Measurement data is simulated using the Monte Carlo simulation method on a typical IEEE test system integrated with renewable energy.Voltage sensitivity indices are extracted using the proposed algorithm.Statistical analysis results demonstrate that the voltage sensitivity extracted by the proposed algorithm presented high accuracy,resulting in a more reliable power grid voltage security situation awareness.
  • Mechanism and Mitigation of Commutation Failure in Hybrid Cascaded HVDC System Caused by Sending End AC Fault 
    BIAN Jing, YANG Xiaoxi, WANG Yao, GUO Jiazhi, WANG Hexin
    Journal of Northeast Electric Power University. 2026, 46(1): 17-28. https://doi.org/10.19718/i.issn.1005-2992.2026-01-0017-12
    Abstract ( ) Download PDF ( ) Knowledge map Save
    Due to the existence of the line commutated converter （LCC）on the inverter side of the grid,the hybrid cascaded high voltage direct current （HC-HVDC）system still faces the problem of commutation failure.Aiming at the commutation failure problem at the receiving end caused by the AC fault at the sending end of the system,the generation mechanism of commutation failure and its suppression strategies were studied.Firstly,the dynamic response of the AC/DC system during the fault is analyzed in phases according to the characteristics of electrical and control variables.Results indicate that the excessively rapid recovery and excessive magnitude of the DC current are identified as the primary causes of commutation failure at the receiving end.On this basis,the impact of firing angle deviation at the rectifier side and the constant DC voltage control of the MMC at the inverter side on DC current recovery during the fault clearance period is further studied.Subsequently,a supplementary firing angle control strategy is proposed for the rectifier side.This strategy suppresses the overly rapid DC current recovery by dynamically adjusting the firing angle command of the line-commutated converter （LCC）at the rectifier,thereby mitigating commutation failure.Finally,a simulation model is established in PSCAD/EMTDC for comparative analysis.The results validate the accuracy of the analyzed commutation failure mechanism and demonstrate the effectiveness of the proposed mitigation strategy.
  • Research on Data-driven Coordinated Control Strategy for AVC in Novel Power Systems
    ZHOU Yibo, LI Guoran, LI Dan, LIU Zihang
    Journal of Northeast Electric Power University. 2026, 46(1): 29-37. https://doi.org/10.19718/i.issn.1005-2992.2026-01-0029-09
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    With the large-scale and continuous integration of new energy,the intermittent variation in its active power output leads to large-scale and rapid shifts in power distribution across the power grid,along with an increase in reactive power and voltage regulation demands that exhibit the characteristic of uneven spatial distribution.The operation frequency of discrete voltage regulation devices （e.g.，capacitors/reactors）at some power stations has increased significantly,which may result in over utilization of voltage regulation resources,and further trigger problems such as shortened equipment service life,and rising maintenance and overhaul costs.Therefore,this paper first constructs an index system for evaluating AVC control performance,and uses measured data from an actual power grid to reveal the imbalance degree of discrete voltage regulation device operations under the current AVC strategy.Then,aiming to minimize network losses and balance the operations of discrete voltage regulation devices,a data-driven optimal model for the coordinated AVC control strategy of new power systems is proposed.Case study analysis of a large regional power grid shows that the coordinated control strategy proposed in this paper can significantly reduce the operation frequency of discrete voltage regulation devices at frequently operating nodes,improve the utilization rate of regulation devices at underutilized nodes,and extend the operation,inspection and maintenance cycle of equipment,while ensuring that network losses remain almost unchanged.This study provides effective support for ensuring the voltage quality of new power systems and the operational safety of discrete voltage regulation devices.
  • Adaptive Ride-through and Recovery Control Strategy for Renewable Energy Units Responding to Transient Voltage Evolution
    YANG Hao, SHI Xuefeng, FENG Shuo, LI Shilong, SHI Fang
    Journal of Northeast Electric Power University. 2026, 46(1): 38-51. https://doi.org/10.19718/j.issn.1005-2992.2026-01-0038-14
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    Conventional control strategies for new energy units during the ride-through phase often struggle to directly meet the requirements specified in ride-through standards,particularly in adequately responding to the ride-through duration criteria.This leads to insufficient utilization of the voltage support capability of new energy units,resulting in the issue of "sustained low-voltage ride-through."During the recovery phase,control strategies often fail to account for the evolving voltage state,which may trigger the problem of "repeated low-voltage ride-through."Additionally,in both phases,the coordination of active power is often inadequately considered during voltage support control.To address these issues,this paper responds to the voltage ride-through standards and guidelines for new energy units and proposes an adaptive ride-through and recovery control strategy that accounts for the transient voltage evolution throughout the entire voltage ride-through process.During the ride-through phase,fuzzy logic theory is applied to design a fuzzy controller capable of responding to voltage deviation and ride-through duration.An optimization model for active/reactive power coordination is constructed to enhance voltage support while reducing active power deficits.In the recovery phase,the reactive current is adjusted by tracking the voltage state,and active power is rapidly restored without compromising voltage support capability.This achieves coordinated control of reactive current and voltage,preventing new energy units from repeatedly entering voltage ride-through.Finally,based on the DIgSILENT simulation software,an IEEE 9-bus test system incorporating wind turbines is built for simulation verification.The results demonstrate that the proposed control strategy effectively enhances the voltage support capability of the new energy grid-connected system.
  • Interpretable Intelligent Identification Model for Frequency Disturbance Events Considering PMU Optimization Placement
    WANG Xiaoya, YANG Shiwei, YANG Yile, SUN Zhenglong, JIANG Chao, CHEN Weihan
    Journal of Northeast Electric Power University. 2026, 46(1): 52-62. https://doi.org/10.19718/i.issn.1005-2992.2026-01-0052-11
    Abstract ( ) Download PDF ( ) Knowledge map Save
    With the growth of the scale of interconnected power systems and the increase in the proportion of renewable energy grid connected generation,frequency disturbances in power systems occur from time to time.Quickly and accurately determining the type of frequency disturbance is of great significance for taking reasonable suppression measures and improving grid stability in the future.This paper proposes a frequency disturbance event recognition method that considers the optimization of phasor measurement units （PMUs）layout.Firstly,by interconnecting Python and simulation software DIgSILENT,the construction of a feature dataset for frequency disturbance events（FDEs）discrimination is completed；Secondly,establish a convolutional neural network model for FDEs classification；Furthermore,a greedy algorithm for embedding convolutional neural network model training is proposed to address the problem of PMU optimization placement.Under partial observability,the most suitable PMU placement position is obtained,and FDEs discrimination is ultimately achieved accurately,quickly,and economically.The effectiveness of the proposed method is verified in an IEEE 39 node system；Finally,in response to the "black box"problem in deep learning network models,a attribution analysis framework based on SHAP （Shapley Additive Explanning）theory is proposed.By calculating the Shapley value to obtain the importance relationship of FDEs feature quantities in the power system,the interpretability and credibility of the model's output resulsare improved.
  • Research on the Mechanism and Scenario Construction of Climate Change Impact on Power Generation and Load Sides of Power System
    KONG Lingxu, SUN Lehua, ZHANG Hao, LIU Chang, YANG Xiuyu, YANG Cheng
    Journal of Northeast Electric Power University. 2026, 46(1): 63-72. https://doi.org/10.19718/j.issn.1005-2992.2026-01-0063-10
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    Against the background of rising renewable energy penetration and profound transformation of power load structures, frequent extreme weather exacerbates power fluctuation and supply-demand imbalance risks on both generation and load sides of power system. This paper proposes a refined extreme scenario construction method coupled with key meteorological factors. Firstly, the influence mechanism of temperature, wind speed and illumination on wind-photovoltaic output and temperature-controlled load is analyzed, and meteorology-coupled generation-load models are established. Secondly, typical extreme weather characteristics are summarized, and two typical scenarios of "extreme high temperature & windless" and "extreme low temperature & cold wave" are constructed. Finally, case simulation is carried out based on measured meteorological data of Northeast China. The results show that the constructed scenarios have physical authenticity, and can effectively quantify the supply-demand imbalance under extreme weather, providing reliable scenario support for power system risk assessment and defense strategy formulation.
  • Research on Thermocouple Measurement Deviation Based on CPR1000 Upper Plenum Temperature Field Modeling
    TIAN Guangzheng, SHA Hongwei, LI Guangfeng, YANG Zihan, CHEN Jingshi, FAN Jianhua
    Journal of Northeast Electric Power University. 2026, 46(1): 73-80. https://doi.org/10.19718/j.issn.1005-2992.2026-01-0073-09
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    Aiming at the problem of thermocouple measurement deviation in the upper plenum of CPR1000 nuclear power plant, a three-dimensional temperature field numerical model is established to simulate the internal flow field and temperature distribution characteristics. The influence mechanism of thermocouple installation position, layout mode and flow disturbance on measurement accuracy is analyzed. Numerical simulation is used to calibrate the measurement error and reveal the formation law of temperature deviation, and installation optimization and error correction methods are proposed. The research results can provide theoretical basis and technical reference for accurate temperature monitoring and thermocouple layout optimization of nuclear reactors.
  • Research on Lightning Protection Performance of Wind Turbine Blades Under Different Air Termination Systems
    LEI Yuhang, ZHANG Zimu, WANG Yubo, WANG Hongze
    Journal of Northeast Electric Power University. 2026, 46(1): 81-91. https://doi.org/10.19718/j.issn.1005-2992.2026-01-0081-08
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    To optimize the lightning protection design of wind turbine blades, the protection characteristics of traditional air terminals and distributed lightning strips are compared. Combining electromagnetic transient simulation and scaled experiments, the surface electric field distribution, discharge development path and lightning current shunt characteristics of blades under lightning impulse are analyzed. The influence of different layout and installation spacing on lightning attraction effect and protection reliability is studied, and the adaptability of various air termination systems is evaluated. The results show that the distributed air termination system can effectively suppress blade edge discharge, and its protection performance is better than traditional structures, which can provide reference for lightning protection engineering design of wind turbine blades.
  • Internal Fault Modeling and Fault Current Analysis of Fractional Pole-Path Ratio Pumped Storage Motor
    XIAO Shiyong, QI Shuai, XUE Lizhu
    Journal of Northeast Electric Power University. 2026, 46(1): 92-100. https://doi.org/10.19718/j.issn.1005-2992.2026-01-0092-07
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    Aiming at the special winding structure and complex internal fault mechanism of fractional pole-path ratio pumped storage motor, a multi-loop mathematical model of the motor is established, and simulation models for stator inter-turn, inter-phase and grounding faults are constructed. The amplitude, harmonic characteristics and transient variation law of fault current under different fault conditions are analyzed. The influence of pole-path ratio parameters on fault characteristics is explored, and the internal fault evolution mechanism of fractional pole-path ratio motor is revealed, which provides theoretical support for motor fault diagnosis and protection setting.
  • Variable Power Virtual Inertia Control Strategy for DFIG Considering Secondary Frequency Drop Suppression
    ZHAO Jinhu, CHEN Wei
    Journal of Northeast Electric Power University. 2026, 46(1): 101-119. https://doi.org/10.19718/j.issn.1005-2992.2026-01-0101-09
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    Virtual inertia control of doubly-fed induction generators (DFIG) can effectively support grid frequency, but traditional fixed inertia parameters are prone to cause secondary frequency drop. Therefore, a variable power virtual inertia control strategy for secondary frequency drop suppression is proposed. By real-time sensing the grid frequency change rate and deviation, the virtual inertia coefficient is adaptively adjusted to balance the requirements of primary frequency modulation support and secondary drop suppression. A wind power grid-connected simulation model is built to compare the frequency response characteristics of traditional and proposed strategies. The simulation results show that the strategy can effectively suppress frequency fluctuations, eliminate secondary drop, and improve grid frequency stability.
  • Multi-time Scale Low-carbon Scheduling Strategy of Virtual Power Plant Considering Compressed Air Energy Storage and Hydrogen Energy
    GAO Yang, XI Xiao, ZHANG Chuchen
    Journal of Northeast Electric Power University. 2026, 46(1): 110-120. https://doi.org/10.19718/j.issn.1005-2992.2026-01-0110-08
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    Aiming at the demand of high-proportion new energy consumption and low-carbon operation of virtual power plant, a multi-time scale low-carbon scheduling model is constructed by integrating compressed air energy storage, hydrogen energy storage and controllable loads. Considering the temporal characteristics of day-ahead and intra-day real-time scheduling, dual-objective optimization of economic cost and carbon emission is carried out to coordinate energy storage charge and discharge, hydrogen production and flexible load regulation. Numerical examples verify that the proposed strategy can suppress new energy fluctuations, reduce carbon emissions and operation costs, and realize the economic and low-carbon coordinated operation of virtual power plants.
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