30 April 2026, Volume 46 Issue 2

    

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  Small Target Detection for Aerial Quadrotor Unmanned Aerial Vehicle Based on Lightweight and Multi-scale YOLOv10

  WANG Shenquan, WANG Yiran, JIANG Yulian

  Journal of Northeast Electric Power University. 2026, 46(2): 1-7. https://doi.org/10.19718/i.issn.1005-2992.2026-02-0001-07

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  Quadrotor unmanned aerial vehicle （UAV）imagery often suffers from issues like small targets,high blur-ring,and severe occlusion,primarily driven by fluctuations in flight altitude,camera angles,and complex background interference.Such constraints lead to frequent missed detections and false positives.This paper introduces a lightweight multi-scale YOLOv10-based algorithm specifically designed to enhance small target detection in these demanding aerial scenarios.First,the architecture and feature extraction mechanism of the YOLOv10 network are analyzed,identifying specific limitations in small target detection under complex backgrounds and multiple scales.Subsequently,a lightweight bidirectional feature aggregation module is proposed,specifically tailored for aerial photography,to strengthen the integration of shallow and deep features for small targets.In addition,to improve small target detection,we integrate a full-dimensional attention mechanism with a hierarchical spatial pyramid pooling structure,enabling enhanced target response and multi-scale receptive field fusion.An adaptive weighted Focal-EIoU is adopted as the model loss function to improve detection accuracy and convergence speed in complex background.Finally,experiments on the VisDrone2021and UAVDT public datasets demonstrate that the improved algorithm achieves lower false negative rates and higher detection accuracy,effectively handling small target detection tasks while maintaining strong generalization capabilities.
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  Strategy for Coordinated Consumption of Wind and Solar Power Using a Cluster of Water Thermal Storage Electric Boilers 

  YAN Gangui, JIN Xinzhi, LV Shuaishuai, WANG Yupeng, CHEN Xueyu, LAN Haitao, WANG Juexin, KONG Fangiang, YAN Jia

  Journal of Northeast Electric Power University. 2026, 46(2): 8-17. https://doi.org/10.19718/j.issn.1005-2992.2026-02-0008-11

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  Under the "Carbon Peak and Carbon Neutrality"goals,the integration of a high proportion of renewable energy into the power grid has become an inevitable trend.This paper investigates a method for utilizing water-storage electric boiler load clusters to collaboratively absorb wind and solar power.By establishing a refined model of the electric boiler heating system,the regulation potential and operational constraints are analyzed.An optimal dispatch model aimed at minimizing the total economic cost is constructed,taking into account electricity purchase costs,penalties for wind and solar curtailment,and user thermal comfort constraints.The Alternating Direction Method of Multipliers（ADMM）is adopted to achieve distributed collaborative optimization among multiple microgrids.Simulation results show that the proposed strategy reduces wind and solar curtailment by an average of 56.28%and operating costs by 26.12%in a single microgrid.In a coordinated multi-microgrid scenario,total curtailment is reduced by 99.4%and total operating costs by 27.0%.The study verifies the effectiveness of thermal-storage electric boiler load clusters in enhancing renewable energy absorption,providing theoretical support and engineering references for the coordinated dispatch of distributed thermal loads in multi-microgrid systems.
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  Decision-Making Method for Aluminum Smelters Participating in Power-Green Certificate Market Trading under the Green Power Aluminum Evaluation Mechanism 

  YU Na, XU Ankun, HUANG Dawei

  Journal of Northeast Electric Power University. 2026, 46(2): 18-26. https://doi.org/10.19718/i.issn.1005-2992.2026-02-0018-09

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  Green power aluminum evaluation is a significant initiative to promote the high-quality development of China's aluminum industry,providing a crucial pathway for aluminum smelters to achieve energy conservation,emission reduction,and green transition.Under this framework,this paper proposes a decision-making method for aluminum smelters participating in electricity-renewable energy certificate （REC）market transactions.Based on China's current electricity-REC market rules,an operational decision-making framework for aluminum smelters is analyzed.A monthly electricity purchasing decision model is established,incorporating REC trading and bilateral monthly electricity transactions,with the objective of minimizing electricity costs while considering operational constraints.Scenario analysis is employed to address uncertainties in self-owned renewable generation,enabling coordinated balance between purchased and self-generated green power at the monthly timescale.At the day-ahead timescale,an optimization model for participation in flexibility markets is developed,maximizing profits from flexibility transactions while accounting for the responsive characteristics of electrolytic aluminum loads and operational constraints of self-owned thermal power units.Case studies on an aluminum smelter verify the effectiveness of the proposed method.
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  AC/DC Probabilistic Load Flow Calculation of Photovoltaic and Energy Storage Systems Based on Latin Hypercube Correlated Sampling

  ZHAO Xu, GAO Zichun, XIA Dapeng, SUN Yinfeng

  Journal of Northeast Electric Power University. 2026, 46(2): 27-37. https://doi.org/10.19718/ij.issn.1005-2992.2026-02-0027-11

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  The vigorous development of new power systems has added complexity and uncertainty to the power grid,especially when flexible DC networks are embedded in traditional power systems,making the operating conditions more complex and variable.To better evaluate the volatility and uncertainty of new energy in new power systems,this paper considers the random output correlation of photovoltaic,studies the probabilistic load flow distribution of AC/DC hybrid systems,and proposes a probabilistic load flow calculation method of AC/DC hybrid system combining Latin hypercube correlated sampling and unified iteration method.Firstly,for different control methods of inverters,a unified iteration method is used for conventional AC/DC power flow calculation.Secondly,the probability model of photovoltaic,energy storage,and load are established.Then,the Latin hypercube correlated sampling is used to obtain the input variable sample matrix.Finally,the mean and standard deviation of the node voltage and line power of the AC/DC hybrid system are calculated by the unified iteration method which can consider the AC/DC coupling.Based on the modified IEEE34 node system and three-terminal DC network,four scenarios are used to verify the effect of the proposed method in accurately reflecting the inherent uncertainty of new energy,the correlation of input variables,and the convergence and operation efficiency.
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  A Joint Planning Method for Soft Open Point and Energy Storage in Medium-Voltage Distribution Networks Considering Source-Load Matching and Flexibility

  FENG Hailin, GAO Ziyang, WANG Pengshun, KONG Lingguo

  Journal of Northeast Electric Power University. 2026, 46(2): 38-48. https://doi.org/10.19718/j.issn.1005-2992.2026-02-0038-11

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  With the continuous increase in the penetration rate of new energy sources,distribution networks are facing problems such as unbalanced temporal and spatial distribution of source-load and insufficient flexible adjustment capability of the network.To address this issue,this paper proposes a joint planning method for soft open points （SOP）and electrochemical energy storage （EES）in distribution networks that comprehensively considers the source-load matching characteristics and flexibility of the network.Firstly,source-load matching indexes reflecting the utilization rate of the SOP and the adaptability of EES to the uncertainty of the net load are constructed,to characterize the priority of configuring the SOP on the tie line and the incremental benefit of the ESS capacity configuration.On this basis, the flexibility profit index is integrated into the objective function,with the maximization of annual profit as the optimization goal.A joint planning model for the optimal configuration of SOP and EES is established by comprehensively considering the regulatory role of SOP and the operational constraints of the distribution network.With reference to the source-load matching index,an internal and external nested algorithm considering the priority of SOP configuration is proposed to solve the proposed planning model.Simulation calculations are carried out using the improved IEEE 33-bus system as an example to verify the effectiveness of the proposed model and method.
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  Short-term Wind Speed Prediction of MTCN Based on Time Series Clustering of Wind Speed Attributes 

  PAN Chao, ZOU Shoukun, WANG Chao, SUN Hui, LI Zaiyuan, SHI Xiaohang

  Journal of Northeast Electric Power University. 2026, 46(2): 49-60. https://doi.org/10.19718/1.issn.1005-2992.2026-02-0049-12

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  Accurate wind speed prediction is crucial for building a safe and efficient integrated energy system.A multi-channel time convolution network prediction model based on multi-dimensional wind speed attribute time series samples and compression-excitation module optimization is proposed in this paper.Firstly,the sequence is divided into two parts,deterministic and stochastic,according to the law of wind speed variation.Then,Considering the spatial and temporal distribution characteristics of wind speed,the multi-dimensional wind speed attribute fragments are used as the core to construct the temporal sample set,and the spatial and temporal separation of density peaks is optimized by K proximity to realize the multi-dimensional temporal sample clustering.Finally,The compression-excitation module is introduced into the multi-channel time convolutional network model to improve the prediction efficiency.The sample sets after clustering are trained in parallel,and the combined results of single value prediction and interval prediction are output.Finally,a coastal wind field is simulated to verify the accuracy and feasibility of the proposed model.
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  Research on Primary Frequency Modulation Control Strategy of Doubly-fed Wind Turbine Based on Supercapacitor

  LI Weiguo, WU Zhiyu, CAI Tingting

  Journal of Northeast Electric Power University. 2026, 46(2): 61-71. https://doi.org/10.19718/j.issn.1005-2992.2026-02-0061-11

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  The Doubly-Fed Induction Generator (DFIG) is the most widely used wind generator in wind power generation. Its rotational speed is decoupled from the grid frequency. The DFIG participates in the system frequency regulation through measures such as overspeed load shedding control and adjustment of the pitch angle. Such measures can indeed reserve a part of the active power to participate in the primary frequency regulation of the system, but it will reduce the power generation efficiency of the generator set, make the control of the turbine pitch angle operate frequently, and increase the maintenance cost. In order to improve the power generation efficiency of wind turbines, improve the possibility of wind turbines participating in primary frequency regulation, and enhance the operational stability, according to the characteristics of doubly-fed wind turbines, an energy storage device is configured for a single wind turbine to participate in the primary frequency regulation of the system, and a dynamic proportional coefficient frequency regulation strategy is proposed. From the perspective of State of Charge (SOC), combined with the characteristics of virtual inertia control and virtual droop control, dynamic coefficients are allocated for the two frequency regulation methods to reduce the frequency deviation and frequency change rate caused by load disturbance. Simulation results verify that the doubly-fed wind turbine equipped with supercapacitors has significantly improved primary frequency regulation capability, providing broad ideas for the modification of already operating doubly-fed wind turbines.
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  Power Coordination and Stable Operation Control of Photovoltaic Storage AC Microgrids Based on Virtual Synchronous Generators

  WANG Yijun, YOU Xiangyu, GAO Min, WAN Shangjin, HOU Yuxuan

  Journal of Northeast Electric Power University. 2026, 46(2): 72-82. https://doi.org/10.19718/j.issn.1005-2992.2026-02-0072-11

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   In an AC microgrid composed of multiple photovoltaic-energy storage units interconnected with virtual synchronous generators (VSG), the power coordination and stable operation mechanisms exhibit significant complexity. To address the issues of power coordination and stable operation in such a microgrid, this paper proposes the following strategies: first, the state of charge (SOC) adaptive gain is employed to regulate the frequency regulation characteristic parameters of the VSG, thereby achieving SOC consistency among the lithium battery energy storage units; second, the SOC of supercapacitors is utilized to adjust their respective power sharing ratios, effectively smoothing the power fluctuations of the lithium batteries; finally, a virtual power loop is introduced and multiple VSG units participate in pre-synchronization, enabling smooth switching between grid-connected and islanded modes. Simulation results demonstrate that the proposed approach improves power sharing, balances SOC among units, and achieves seamless transition.
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  Research on Economic Optimal Coordination of Wind-Thermal-Storage Stations with Electricity-Carbon Coupling

  FAN Yiwei, YAN Xing, WANG Guangxing, HUA Hanxiao, SHAO Wencai

  Journal of Northeast Electric Power University. 2026, 46(2): 83-92. https://doi.org/10.19718/j.issn.1005-2992.2026-02-0083-10

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  With the advancement of the "dual-carbon" goals, achieving coordinated development of economic efficiency and low-carbon performance in power systems has become an urgent and critical challenge. This paper proposes a bilevel optimization model considering electricity-carbon coupling to enable coordinated low-carbon and economic operation of a wind-thermal-storage system. The upper-level model aims to minimize the integrated cost by jointly optimizing system operation costs and reducing carbon emissions; the lower-level model, based on upper-level constraints, minimizes the mean square error of system power balance deviation to smooth equivalent net load fluctuations. To address the nonlinear and multi-constrained characteristics of the model, an Improved StarFish Optimization Algorithm (ISFOA) is proposed based on Levy flight strategy and triangular walking strategy, which enhances solution accuracy by dynamically balancing global search and local optimization processes. Case studies demonstrate that the proposed model can effectively improve renewable energy accommodation capacity as well as the low-carbon and economic performance of system operation.
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  Research on Ordered Charging and Discharging Scheduling of Electric Vehicles Based on Improved Dung Beetle Algorithm 

  YAN Jun, LIU Liangliang, LIU Conghao, LI Wenlong, QI Yuqian, QIN Peijun

  Journal of Northeast Electric Power University. 2026, 46(2): 93-101. https://doi.org/10.19718/j.issn.1005-2992.2026-02-0093-10

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  The uncoordinated charging and discharging behaviors of Electric Vehicles （EVs）are prone to exacerbate load fluctuations in distribution networks,hindering the promotion of Vehicle-to-Grid （V2G）technology.To address this issue,this paper analyzes the load characteristics of uncoordinated EV charging and their impact on the distribution network,and constructs a multi-objective optimization model aimed at minimizing the daily peak-to-valley difference rate, user charging costs,and battery degradation.The model comprehensively considers the travel patterns of private EVs, State of Charge （SOC）constraints,and time-of-use electricity pricing mechanisms,proposing an orderly charging and discharging scheduling strategy.An Improved Dung Beetle Optimization Algorithm （IDBO）is employed for solution,which enhances local exploitation capability through a spiral search strategy,improves global search performance by integrating Levy flight,and incorporates t-distribution perturbation to avoid local optima.Simulation results demonstrate that the proposed method effectively mitigates load fluctuations in the distribution network.Within an EV penetration range of 20%to 35%， the peak-to-valley difference rate is reduced by 20.97%to 32.81%，and user charging costs are lowered by 66.65%to 97.93%compared to uncoordinated charging.In specific scenarios,positive revenue can be achieved by charging during off-peak periods and discharging during peak periods.This research provides technical support for enhancing V2G coordination efficiency and promotingthe low-carbon synergistic development of the transportation and energy sectors.
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  High-Frequency Transformer Simulation Analysis under Electromagnetic-Fluid-Thermal-Structural-Noise Multiphysics Coupling

  HE Shuang, ZHAO Rui, DONG Le, LI Xiangnan, MO Jingshan

  Journal of Northeast Electric Power University. 2026, 46(2): 102-113. https://doi.org/10.19718/j.issn.1005-2992.2026-02-0102-12

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  High-Frequency Transformer (HFT) is a core component of power electronic transformers and dual-active-bridge DC-DC converters. The distribution characteristics of its temperature and stress fields are crucial for system reliability and environmental friendliness. In this study, a 5kHz/10kVA HFT was analyzed using finite element simulation software. A full-chain multiphysics coupling simulation covering electromagnetic, fluid, thermal, structural, and acoustic domains was conducted to obtain the distribution patterns of electromagnetic, temperature, stress, and other multiphysics fields under nonsinusoidal excitation. The results reveal that the core loss of the high-frequency transformer is 52.7W, with high-voltage and low-voltage winding losses of 13.23 and 3.01W, respectively. The maximum magnetic flux density under sinusoidal excitation reached 0.746T, while under square wave excitation it reached 0.923T. The hotspot temperature was located approximately two-thirds along the core column at 115℃, with the lowest temperature recorded at 92.3℃ beneath the high-voltage winding. Forced air cooling demonstrates significant cooling efficiency below 4m/s wind speed, with cooling rates slowing thereafter. At 4m/s wind speed, core stress amplitudes under sinusoidal and square wave excitation were 2.81×106 and 3.65×106N/m2, respectively, with sound pressure level amplitudes of 78.1 and 94.9dB. When further considering the effect of thermal stress, under natural air cooling and square wave excitation, the core stress rises to 3.92×106N/m2, the vibration acceleration increases to 64.3m/s2, and the maximum sound pressure level reaches 97.3dB, representing increases of 7.4%, 6.8%, and 2.4dB, respectively, compared with the forced air cooling condition. Owing to its rich harmonic content, square wave excitation leads to significantly greater deformation, stress and noise than sinusoidal excitation, while thermal stress, as a secondary factor, further exacerbates vibration and noise levels. Through multiphysics simulation, the influence mechanism of waveform excitation and thermal stress on the comprehensive performance of transformers is revealed, providing a theoretical basis for multi-objective optimization of high-frequency transformers.
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  Simulation and Experimental Study on the Characteristics of Branched UHVDC Grounding Electrode

  LIU Wei, LI Yong, BAO Minghui, ZOU Binyang, YU Xinxi

  Journal of Northeast Electric Power University. 2026, 46(2): 114-120. https://doi.org/10.19718/j.issn.1005-2992.2026-02-0114-07

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  To address the challenges in determining the appropriate burial depth and achieving uniform current distribution of grounding electrodes for ultra-high voltage direct current (UHVDC) transmission projects in complex terrain conditions, this study takes the receiving-end converter station of the ±800kV Hami-Chongqing transmission project as a representative case. The performance optimization measures for China's first branched UHVDC grounding electrode were comprehensively investigated. An electrical performance simulation model was developed using CDEGS, and the effects of grounding electrode burial depth, shallow soil resistivity, and the number of segments on grounding characteristics were systematically analyzed. The research shows that increasing the burial depth of the grounding electrode and reducing the shallow soil resistivity can effectively limit the ground step voltage, and the optimal number of segments that balances current sharing performance and economy was determined through simulation. Field tests show that the maximum step voltage increases by more than 40% under dry conditions compared with the surface wet period, indicating that dry surface conditions should be the key reference for the design margin of grounding electrode burial depth. The current division difference among the 11 grounding electrode branches is only 1.8%, which proves the rationality of the core parameter segment number setting in the grounding electrode design scheme. The research results can provide theoretical basis and engineering reference for the design and optimization of UHVDC grounding electrodes in complex terrain.