31 December 2025, Volume 45 Issue 6
    

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  • Battery Optimization Strategy for Electric-vehicle Battery Swapping Stations Based on Dynamic Time Windows and Coordinated Battery Management 
    YAN Gangui, HUANG Kaiqi, LV Shuaishuai, WANG Yupeng, LAN Haitao, KONG Fangiang, ZHAO Lei
    Journal of Northeast Electric Power University. 2025, 45(6): 1-8. https://doi.org/10.19718/i.issn.1005-2992.2025-06-0001-08
    Abstract ( ) Knowledge map Save
    The immediate charging mode of electric vehicle battery swap stations can easily exacerbate the peak-valley difference in grid load and the imbalance in the utilization of battery energy storage resources,thereby restricting the economic operation of the swap stations and the security of the grid.To address this issue,this paper constructs a mixed-integer linear programming model with the objective of minimizing the cost of charging and purchasing electricity,while considering the constraints of battery state coordination and resource balance.It also proposes a battery charging optimization strategy based on dynamic time windows and battery collaborative management.Through the dynamic time window mechanism,the charging tasks are temporally and spatially shifted,and combined with battery state collaborative management,the overall charging load distribution is optimized while meeting the users' battery swap demands,reducing the cost of purchasing electricity and enhancing the security of the grid.Compared with the rapid response of the immediate charging mode,this strategy focuses more on system-level resource balance, providing a feasible solution for large-scale battery swap stations to participate in power demand response.Taking an actual battery swap station in a certain area as the verification object,the load regulation effect and comprehensive benefits of different time window lengths were evaluated.The results show that this strategy significantly improves load balance and reduces the cost of charging and purchasing electricity.In addition,through sensitivity analysis,the intluence laws of key parameters on system performance were revealed,providing a practical optimization method and decision support for large-scale battery swap stations to participate in power demand response,which is of great significance for promoting the coordinated development of the electric vehicle industry and the grid.
  • Electric Vehicle based on Geographic Information and Multi-level Trip Chain Charging Load Simulation
    YU Na, JIANG Yeyu, HUANG Dawei
    Journal of Northeast Electric Power University. 2025, 45(6): 9-17. https://doi.org/10.19718/j.issn.1005-2992.2025-06-0009-09
    Abstract ( ) Knowledge map Save
    Aiming at the simulation problem of electric vehicle charging load in time and space distribution,this paper proposes a simulation method of electric vehicle charging load based on geographic information and multi-level trip chain.By establishing a regional road network model and dividing functional blocks,the vehicle movement trajectory is combined with road information to construct a complete mobile chain model of travel starting point-multi-destination stay-return path'.The path planning algorithm is used to simulate the user's daily travel mode,and the space-time simulation model of charging demand is constructed.The results show that this method can effectively simulate the charging load change trend of different regional types and urban functional areas,and accurately identify the electricity consumption characteristics of residential areas,work areas and other scenes.Compared with the traditional single trip chain model,the multi trip chain model constructed in this paper can more accurately simulate the spatial and temporal distribution characteristics of electric vehicle charging load.
  • Joint Planning Method of Storage-transmission Considering Resource-line Dual Flexibility Margin
    SHI Shengyao, FAN Zekun, YANG Xiuyu, JIANG Minglei, ZHANG Zhipeng, XING Wenyang
    Journal of Northeast Electric Power University. 2025, 45(6): 18-26. https://doi.org/10.19718/j.issn.1005-2992.2025-06-0018-09
    Abstract ( ) Knowledge map Save
    Driven by the "dual-carbon"strategic goals,the penetration of renewable energy in power grids continues to increase,placing unprecedented pressure on the regulation capability of power systems.Most existing flexibility assessment and planning methods for power systems focus primarily on supply-demand balance,while paying insufficient attention to the role of transmission capacity in ensuring flexibility.To address this issue,this paper proposes a joint storage-transmission planning method that considers both resource and transmission flexibility margins.First,starting from the system operation mechanism,the influence of transmission network capability on meeting flexibility requirements is analyzed,and the node-level flexibility demand is mapped onto transmission lines.On this basis,two quantitative indices-resource flexibility margin and transmission flexibility margin-are constructed to enable multidimensional flexibility assessment.Subsequently,a joint storage-transmission planning model incorporating both resource and transmission flexibility margins is developed,in which energy storage deployment and transmission expansion are treated as coordinated decision variables to achieve a balance between flexibility enhancement and economic optimization.Finally,simulations based on an improved IEEE RTS-24 bus system are conducted.The results demonstrate that wc piopuscu icuou call mpiuve ucAwuy iaigis wic coiuvig wolal sysicm cust,cuccuvcly aucviaung upciauvnal stress caused by renewable energy fluctuations,and enhancing the accommodation capability of new energy sources.
  • Reservation Charging Guidance Strategy for Electric Vehicles Considering the Interaction of Multi-source Information 
    WANG Yijun, ZHANG Xidong, SUN Jianchun, QIN Yerong
    Journal of Northeast Electric Power University. 2025, 45(6): 27-38. https://doi.org/10.19718/j.issn.1005-2992.2025-06-0027-12
    Abstract ( ) Knowledge map Save
    As an environment-friendly vehicle,electric vehicle has achieved large-scale development,at the same time,the access of a large number of charging loads has caused a great impact on the traffic network and distribution network.Due to the lack of charging infrastructure and the disorderly charging of car owners,car owners may also face the problem of waiting in line for a long time during the charging peak.For this reason,an electric vehicle booking charging guidance strategy considering dynamic traffic information and available charging resources of charging stations is proposed in this paper.Firstly.the user travel characteristics.dynamic traffic network.charging station and distribution network are modeled；secondly,a global optimal path planning algorithm considering cross-period road resistance update is proposed；then,based on the maximum acceptable load of charging stations in the region,a hierarchical adjustment model of dynamic service charge is established according to the real-time load rate of each charging station.Finally,combined with the charging needs of car owners,a reservation charging guidance strategy aiming at the lowest charging cost,total travel time and slow charging cost is established,and the optimal charging scheme is planned for car owners.Ihe simulation results show that the proposed reservation charging guidance strategy can effectively improve the charging satisfaction of car owners,reduce the load variance between charging stations,stabilize the load fluctuation of distribution network,and maintain the safe and stable operation of distribution network.
  • Research on Charging and Discharging Strategy of Electric Vehicles Considering the Paid Peak Shaving Mechanism of New Energy
    ZHANG Liang, LONG Yanliang, ZHANG Chaorui, WANG Dianbin, YIN Shucong, ZHANG Jiajun, YANG Jingying
    Journal of Northeast Electric Power University. 2025, 45(6): 39-50. https://doi.org/10.19718/j.issn.1005-2992.2025-06-0039-12
    Abstract ( ) Knowledge map Save
    Aiming at the current mismatch between new energy output and base load,a set of multi-level refined dynamic peaking compensation mechanism is proposed；an additional dynamic incentive mechanism is proposed between aggregators and grid trading centers to set the peaking compensation price according to the peaking shortfall, which guides the aggregators to integrate the dispatchable resources to provide peaking auxiliary services for the grid； and a response compensation apportionment strategy is proposed between the aggregators and the electric vehicle users.It also proposes a response compensation sharing strategy between aggregators and EV users,which defines the concept of sharing coefficient from the dimensions of dispatchable capacity and load transfer demand during the access time to explore the dispatch potential of the user group.At the optimization level of charging and discharging scheduling scheme,Adjusted Grey Wolf Optimization （AGWO）is used to solve the control model with the objectives of maximizing the revenue of EV aggregator and minimizing the load fluctuation of the system；combined with the user dispatch response model,it is proved that the proposed strategy can tap the potential of EV dispatching according to the demand of grid,which makes the management more flexible.Combined with the user dispatch response model,the proposed strategy proves that it can exploit the potential of EV dispatch according to the grid demand,manage vehicle charging and discharging more flexibly,reduce the charging cost of EV users,increase the revenue of aggregators, reduce the net load fluctuation,and increase the rate of new energy consumption.
  • Interval Forecasting of Electric Vehicle Charging Load Based on FMD-LSTM-Bootstrap 
    HAN Yuhao, LIU Hongpeng
    Journal of Northeast Electric Power University. 2025, 45(6): 51-59. https://doi.org/10.19718/j.issn.1005-2992.2025-06-0051-09
    Abstract ( ) Knowledge map Save
    With the increasing number of electric vehicles,the substantial charging demand has imposed certain impacts on the power grid while introducing challenges for grid dispatching.Consequently,predicting the charging load of electric vehicles has gradually become a research hotspot.To address the randomness of electric vehicle charging loads and the accuracy issues in deterministic predictions,an interval prediction method based on FMD-LSTM-Bootstrap is proposed.Using real historical electric vehicle charging load data collected,the dataset is preprocessed to eliminate erroneous data caused by equipment factors.The processed data is then divided into training and testing sets according to a certain ratio.Aiter tuning with the training set,the testing set is used to validate the prediction pertormance of the FMD-LSTM-Bootstrap method.The performance of the prediction intervals is further verified by combining the average bandwidth and interval coverage rate.Simulation results demonstrate the superiority of the proposed algorithm.
  • Strategies for Enhancing the Resilience of High Proportion New Energy Grid under the Influence of Strong Sandstorms
    LI Xue, YAN Jiabo
    Journal of Northeast Electric Power University. 2025, 45(6): 60-72. https://doi.org/10.19718/j.issn.1005-2992.2025-06-0060-13
    Abstract ( ) Knowledge map Save
    In response to the issue of large-scale failures in power grids with a high proportion of new energy caused by severe sandstorms and the rapid recovery after a significant decline in the output of new energy units, this paper proposes a collaborative optimization method for line fault repair and new energy unit cleaning aimed at enhancing the resilience of transmission networks. Firstly, a high-proportion new energy grid model incorporating concentrated solar power plants and energy storage systems is constructed, which can effectively characterize the dynamic changes in the output power of concentrated solar power plants and energy storage after load variations. Then, the impact of severe sandstorm weather on new energy output and transmission line faults is quantitatively characterized. Further considering factors such as system grid strength and source-load imbalance, a post-disaster transmission line repair and unit cleaning sequence model is proposed with the objective function of maximizing system load recovery. Finally, the effectiveness of the proposed method is verified through an improved IEEE-30 node system, demonstrating that the proposed resilience enhancement strategy can accelerate system recovery, reduce system load loss, and achieve resilience enhancement in power grids with a high proportion of new energy.
  • Commutation Failure Suppression Strategy Considering the Critical Extinction Angle Characteristics of Converter
    XIN Yechun, YI Binxiang, WANG Tuo
    Journal of Northeast Electric Power University. 2025, 45(6): 73-81. https://doi.org/10.19718/j.issn.1005-2992.2025-06-0073-09
    Abstract ( ) Knowledge map Save
    There are differences in the critical extinction angle characteristics of high-voltage direct current transmission systems under different operating conditions. A small angle can easily cause commutation failure, while a large angle is not conducive to system economy and safety. In order to reduce the impact of the dynamic characteristics of the critical extinction angle on commutation failure, firstly, the effects of forward current, current zero crossing change rate, and junction temperature on the critical extinction angle were analyzed, and an approximate calculation model for the critical extinction angle was established to characterize the recovery and blocking ability of thyristors. Then, based on the approximate calculation model of the critical extinction angle, a commutation failure suppression strategy for dynamic compensation of current deviation angle is proposed by analyzing the stage of the effect of the critical extinction angle of the converter on commutation failure in the control system. Finally, simulation experiments were conducted based on the CICRE high-voltage direct current testing model under different operating conditions, and the results showed that this strategy improved the suppression effect of commutation failure under different operating conditions, effectively avoiding the occurrence of subsequent commutation failures.
  • Multi-time Scale Assessment of Daily Regulation Capacity Demand for High Proportion of Renewable Energy Power System based on Haar Wavelet
    LI Longhui, AN Jun, ZHANG Rongxi, ZHAO Jule
    Journal of Northeast Electric Power University. 2025, 45(6): 82-90. https://doi.org/10.19718/j.issn.1005-2992.2025-06-0082-09
    Abstract ( ) Knowledge map Save
    In the high-proportion renewable energy (High Proportion Renewable Energy, HPRE) power system, thermal power units are largely replaced, and the contradiction between supply and demand of system daily regulation capacity is becoming increasingly prominent. Configuring multi-time scale regulation resources on demand can effectively alleviate the above contradiction. However, the strong uncertainty and volatility brought by large-scale wind power and photovoltaic access make it difficult to evaluate the daily regulation capacity requirements of the system. In this paper, a multi-time scale assessment method for daily regulation capacity demand is proposed for HPRE power system. Firstly, based on the perspective of 'adjustable' matching 'non-adjustable' intra-day power balance, a scenario set generation method is proposed to describe the uncertainty of non-adjustable power through Gaussian mixture model (Gaussian Mixture Model, GMM) and K-means clustering. Secondly, according to the hourly fluctuation characteristics of daily non-adjustable power, a multi-time scale evaluation system of daily regulation capacity demand is established. Then, a multi-time scale decoupling evaluation model of daily regulation capacity demand based on Haar wavelet coefficient is constructed by quantifying demand intensity with regulation power and regulation electricity as indicators. Finally, the example results show that the proposed method can provide some reference for the planning and allocation of multi-time scale adjustment resources.
  • Research on Time-frequency Characteristics of Wind-photovoltaic base Co-generation Power based on the db6 Wavelet Transforms
    YUE Fei, ZHONG Wuzhi, XU Zongxin, CUI Yang, LI Jiayu
    Journal of Northeast Electric Power University. 2025, 45(6): 91-101. https://doi.org/10.19718/j.issn.1005-2992.2025-06-0091-11
    Abstract ( ) Knowledge map Save
    Wind, solar resource-rich areas usually appear a variety of new energy (wind, solar) co-generation, in-depth study of wind-solar joint power fluctuation characteristics of power grid safety operation is of great significance. In this paper, based on the measured data of large-scale wind power base in the northern part of Shanxi Province, the time-frequency characteristics of wind and light co-generation power are empirically analyzed by using db6 discrete wavelet transform. First, the wavelet transform is used to decompose the output power of different power generation clusters, and at the same time, the fluctuation rate, the extreme value difference and the fluctuation confidence interval index are calculated for each frequency band. Then, the integrated weight coefficient method is used to analyze the impact of the integrated fluctuation characteristic indexes of each frequency band on the power grid. Finally, based on the results of the time-frequency characterization of different wind farms in the northern part of Shanxi, the integrated fluctuation characteristic indexes of each frequency band of the wind-solar co-generation cluster are compared with those of the single wind/photovoltaic cluster, and the optimal capacity allocation ratio of the wind-solar co-generation cluster is obtained. The results show that compared with single wind/photovoltaic power generation cluster, the overall volatility of wind/photovoltaic co-generation cluster is smaller, which is more conducive to the safe operation of the power grid, and there exists an optimal ratio of wind/photovoltaic installed capacity.
  • Integrated Energy Optimization of Multi Energy Interaction and Multi Microgrid Considering Self Elasticity Coefficient and Peak shaving Fluctuation Excitation under Zero Carbon Target
    JIN Guobin, ZHANG Haiyang, YANG Yang, DANG Ruofeng
    Journal of Northeast Electric Power University. 2025, 45(6): 102-111. https://doi.org/10.19718/j.issn.1005-2992.2025-06-0102-10
    Abstract ( ) Knowledge map Save
    Aiming at the problems of large demand side load fluctuations, high carbon emission base, and conflicting interests of multiple parties in the integrated energy system of multi microgrids with electricity and hydrogen energy interaction, this paper proposes an optimization of the integrated energy system of multi microgrids with zero carbon target considering self elasticity coefficient and peak shaving fluctuation incentives. Firstly, the benefit objectives and decision variables of each interaction party are analyzed, and an upper level cooperative game framework is constructed with the energy system operator of multi microgrids as the leader, and a lower level one master multi slave game model with user aggregator and shared energy storage operator as followers. Secondly, considering the dispersion coefficient of demand side loads, Pearson correlation coefficient with regional distribution networks, and load self elasticity coefficient, an incentive based and price based comprehensive demand response model is constructed. Finally, genetic algorithm was used to solve the problem, and simulation analysis was conducted. The comparison of the four schemes showed that the proposed strategy not only considers the benefits of multiple agents under the constraint of zero carbon emissions, but also improves the ability of demand side load fluctuations and grid peak shaving and valley filling through the reduction of system dispersion coefficient and Pearson correlation coefficient.
  • The Power System Transient Stability Unit-tripping Regulation Strategy based on Boundary Energy
    WANG Xiangdong, LIU Cheng, ZHANG Yanjun, ZHANG Yuchi, LI Wenbiao
    Journal of Northeast Electric Power University. 2025, 45(6): 112-120. https://doi.org/10.19718/j.issn.1005-2992.2025-06-0112-09
    Abstract ( ) Knowledge map Save
    A high percentage of new energy is accessed, which decreases the system's inertia and speeds up response times. This can lead to several issues, such as poor unit-tripping regulation strategy and an erroneous evaluation of the system stability boundary. The traditional unit-tripping regulation strategy is no longer sufficient for the current power system. To ensure quick stable operation after optimal unit-tripping regulation, provide a boundary energy-based power system transient stability unit-tripping strategy. First, define the individual machine energy function to determine the system's boundary energy. through calculating and analyzing the boundary energy, assess the system's stability using the stability index; Second, create the generator sensitivity index and determine how the unit's active power and stability index relate to one another, and through the calculation of the sensitivity index, screen out the units that need to be regulated as a priority. Use the optimization model to calculate the minimum required unit-tripping amount to restore system stability, and take corresponding unit-tripping operation based on the judgment results; Finally, it has been verified that this method can effectively regulate unit-tripping quantity to achieve the goal of restoring stable system operation in actual power system.
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