Table of Content

28 October 2025, Volume 59 Issue 10 Previous Issue   

New Type Power System and the Integrated Energy

Select

Optimization Configuration of Battery Storage Coordinated with Differentiated Frequency Regulation Strategy of Wind, Solar, and Thermal Power CHENG Haowen, LI Kecheng, LIU Lu, CHENG Haozhong, SANG Bingyu 2025, 59 (10):  1407-1418.  doi: 10.16183/j.cnki.jsjtu.2024.334 Abstract ( 2023 )   HTML ( 23 )   PDF (2168KB) ( 142 )   Save Diversified frequency regulation resources are an effective and inevitable approach for addressing frequency safety issues in new power system. Based on a differentiated frequency regulation strategy that coordinates wind power, photovoltaic (PV), thermal power, and energy storage, this paper proposes a source-side battery energy storage system (BESS) optimization method under multiple scenarios by coupling long-term planning with short-term unit commitment. Joint frequency regulation strategies for thermal-storage, wind-storage, and PV-storage systems are developed, refining various functional roles of supporting battery storage to enhance flexibility during frequency regulation. The optimization configuration model aims to minimize both the investment and operational costs of wind-solar-thermal-storage systems. Frequency response capacity available from the power system is set as a security constraint, and high-order multi-machine time-domain simulations are used to verify and iterate frequency security margins in the solution process. The proposed method is validated using an improved IEEE 24-bus system. The results show that battery energy storage can flexibly switch between smoothing fluctuations, reducing renewable energy curtailment, and participating in system frequency regulation. Figures and Tables | References | Related Articles | Metrics

Select

Design Methods for Power Secondary System Simulation in New Power Systems HE Ruiwen, LU Jialiang, YANG Changxin, PENG Hao, MOHAMMAD Shahidehpour 2025, 59 (10):  1419-1430.  doi: 10.16183/j.cnki.jsjtu.2023.541 Abstract ( 1498 )   HTML ( 4 )   PDF (3327KB) ( 977 )   Save Under the new situation, there is an urgent need to model and simulate the power secondary system which highly shares information and implements real-time decision-making, in line with the modeling and simulation requirements of new power systems. In this paper, design methods are proposed for the first time to achieve simulation of power secondary systems by correlating the operating status of the power primary system. The smart substation secondary system with complex functional descriptions is taken as the research object. First, an interrelated simulation method for power primary and secondary systems is proposed, and its simulation implementation framework, data interaction method, and data synchronization management are explained, which enables the actual electrical quantity data of the primary system to be transmitted to the secondary side, solving the problem of data source in the secondary system simulation. Then, a simulation design method for the power secondary system is proposed, incorporating system-level interaction design, component-level class design, and module-level state design based on the object-oriented unified modeling language (UML). Thus, the entire process of transmission, interaction, processing, and conversion of electrical quantity data in the secondary system can be analyzed. Finally, to validate the effectiveness of the proposed method, a case study is conducted using a short-circuit fault scenario at the 110 kV side outlet of the 220/110/10 kV main transformer bay, in conjunction with a differential protection scheme. Figures and Tables | References | Related Articles | Metrics

Select

Automatic Mapping Method for Power Supply Units in Medium-Voltage Distribution Networks Based on Generative Adversarial Network CHEN Jinming, JIANG Wei, WANG Zhiwei, ZHU Zhenhan, CHEN Ye, ZHAO Yanchao 2025, 59 (10):  1431-1441.  doi: 10.16183/j.cnki.jsjtu.2023.626 Abstract ( 1557 )   HTML ( 6 )   PDF (2937KB) ( 133 )   Save With the gradual promotion of the “unit based” planning method for distribution networks, regional distribution networks have been divided into several relatively independent power supply units. However, there are multiple interconnecting lines within the power supply units, and the complexity of the structure makes the mapping of power supply units more difficult. The heuristic automated mapping methods based on rules and force orientation are inefficient and relies on manual intervention, which cannot adapt to the complex and changing distribution network application scenarios. Therefore, this paper proposes an automatic mapping method for medium-voltage distribution network power supply units based on the mean square error condition generation adversarial network. The layout generator and genetic mutation algorithm in this method can generate and optimize the layout and connection of distribution network nodes at a fine-grained level, achieving automatic mapping at various node scales. Then, it designs an evaluation function for node layout generators, which takes topology visualization performances such as node clustering degree, line crossing, and inflection points as key evaluation indicators. This function can be used to iteratively optimize the layout generator and thereby improve the mapping effect. The experimental results show that the method proposed outperforms other heuristic layout methods in terms of mapping effect. Figures and Tables | References | Related Articles | Metrics

Select

Control Strategy for Improving Active Frequency Support Capability of Offshore Wind Farm LI Yibo, ZHOU Qian, ZHU Dandan, JIANG Yafeng, WU Qiuwei, CHEN Jian 2025, 59 (10):  1442-1450.  doi: 10.16183/j.cnki.jsjtu.2023.581 Abstract ( 1459 )   HTML ( 2 )   PDF (1522KB) ( 1542 )   Save In low frequency alternating current (AC) transmission systems, offshore wind farm is unable to respond to changes in onshore grid frequency in a timely manner due to frequency decoupling and signal transmission delays between the offshore wind power system and the onshore AC system. To address this issue, a control strategy is proposed to improve the active frequency support capability of offshore wind farms by combining the system inertia. In terms of frequency signaling, an additional frequency sag controller is designed based on the V/f control strategy of the low-frequency-side structure network of modular multilevel matrix converter (M3C), combining with the system inertia. The frequency coupling link between the M3C net side and the low-frequency side is established to realize the real-time transmission of frequency information between the two sides. In terms of frequency support, when the system is disturbed to generate frequency deviation, the offshore wind turbine can adjust the power command value through additional droop control, thereby providing frequency support for the system. Finally, the effectiveness of the proposed coordinated control strategy is verified in MATLAB/Simulink by the simulation of load change and three-phase AC short circuit fault. Figures and Tables | References | Related Articles | Metrics

Select

Two-Stage Market Joint Clearance Considering Participation of Wind/Photovoltaic/Energy Storage Power Station in Flexible Ramping CHENG Mingyang, XING Haijun, MI Yang, ZHANG Shenxi, TIAN Shuxin, SHEN Jie 2025, 59 (10):  1451-1463.  doi: 10.16183/j.cnki.jsjtu.2023.570 Abstract ( 1459 )   HTML ( 0 )   PDF (2032KB) ( 227 )   Save With the integration of a high proportion of renewable energy into the grid, the volatility and uncertainty of wind and solar output will pose more severe challenges to the flexible operation of the system. Reasonable utilization of flexible resources and improvement of the flexible ramping ability of power systems will become an important approach to addressing the challenges of new energy. This article analyzes the differences in system flexibility ramping requirements under different clearing intervals, taking into account the uncertainty of renewable energy. It establishes a two-stage electricity energy and flexible ramping market joint clearing model based on a stochastic programming model. By utilizing flexible resource rich regulation methods such as wind/photovoltaic/energy storage power station, while alleviating real-time market uncertainty, it provides flexible ramping products to improve the flexible adjustment ability of the system. Finally, it conducts a case study to analyze the impact of the clearing model under different clearing methods and prediction errors. The results indicate that a two-stage market joint clearance considering the participation of wind/photovoltaic/energy storage power station in flexible ramping can improve the real-time operational flexibility and overall economic efficiency of the system. Figures and Tables | References | Related Articles | Metrics

Select

Renewable Energy Consumption Strategies of Power System Integrated with Electric Vehicle Clusters Based on Load Alignment and Deep Reinforcement Learning LIU Yanhang, QIAO Ruyu, LIANG Nan, CHEN Yu, YU Kai, WU Hanxiao 2025, 59 (10):  1464-1475.  doi: 10.16183/j.cnki.jsjtu.2023.529 Abstract ( 1249 )   HTML ( 2 )   PDF (3345KB) ( 3482 )   Save As China accelerates the construction of power systems with renewable energy as the mainstay, the large-scale integration of renewables has led to prominent issues such as wind and light curtailment. To improve the utilization of new energy consumption in power systems, this paper proposes a novel renewable energy consumption method based on load alignment and deep reinforcement learning. First, it proposes a node load line formation model based on linearized power flow calculations, which can guide adjustable loads to shift the electricity consumption period, thereby promoting the improvement of new energy consumption. Unlike the direct current (DC) power flow model, the proposed alternating current (AC) model accounts for voltage constraints and other related constraints of the power system. Compared with other AC power flow models, this model linearizes all nonlinear constraints and has lower computational costs. Then, this paper constructs a market framework for load alignment mechanism. The framework involves three main entities: independent system operators, regional power grid sellers, and electric vehicle adjustable load aggregators. It also explores the solution for load alignment incentive prices using electric vehicle clusters as adjustable loads. As the solution of the load benchmark incentive price involves a master-slave game between three entities, conventional mathematical analysis methods face high complexity. Therefore, it employs deep reinforcement learning algorithm to solve the problem. The deep reinforcement learning algorithm takes the marginal electricity price of each node as state space, the load benchmark incentive price as action space, and the cost of regional power grid sellers as feedback. The agent can find the load line incentive price that maximizes the benefits of regional power grid sellers after continuous training. Finally, the example analysis shows that the load alignment mechanism not only effectively promotes the improvement of new energy consumption level, but also enhances the interests of independent system operators, regional power grid sellers, and electric vehicle aggregators. The results further confirm that the deep reinforcement learning algorithm maximizes the benefits of regional power grid sellers. Figures and Tables | References | Related Articles | Metrics

Select

Decision-Making Model of Electricity Procurement and Sale for Electricity Retailers Considering the Uncertainty of Prosumers SUN Yi, LIU Zhuang, HUANG Ting, PENG Jie, WANG Xiaotian, LIU Chuang 2025, 59 (10):  1476-1486.  doi: 10.16183/j.cnki.jsjtu.2023.530 Abstract ( 1092 )   HTML ( 3 )   PDF (2928KB) ( 409 )   Save In the context of the new power system, traditional energy consumers are transforming into prosumers, entities that both consume and produce electricity. The emergence of a large number of prosumers has made the purchase and sale decisions of electricity retailers more complicated. At the same time, electricity retailers will also face more uncertainties, resulting in greater market risks. To address these challenges, this paper proposes an optimization method of power purchase and sales strategy for electricity retailers facing prosumers under uncertain factors. First, it establishes a two-tier optimization model for the purchase and sale of electricity by electricity retailers under uncertain conditions. The upper model focuses on the comfort and cost of prosumers, incorporates the uncertainty of photovoltaic output, and develops a robust energy optimization model for prosumers. For the uncertainty of electricity purchase and sale prices in the spot market, the lower model establishes a robust comprehensive decision-making model of electricity sales companies based on information gap decision theory (IGDT). Then, it uses the Karush-Kuhn-Tucker (KKT) condition to transform the two-tier optimization problem proposed in into a single-layer nonlinear programming problem. Finally, the simulation analysis demonstrates the economy of the retail electricity price obtained and the effectiveness of the proposed model. Figures and Tables | References | Related Articles | Metrics

Select

Optimization Methods and Application for Low-Carbon Transition Pathways of Power Generation Enterprises YAN Xinrong, WANG Jing, ZHENG Wenguang, GAO Xiang, DU Ershun 2025, 59 (10):  1487-1497.  doi: 10.16183/j.cnki.jsjtu.2023.555 Abstract ( 1424 )   HTML ( 4 )   PDF (2426KB) ( 120 )   Save The power sector is the largest single source of carbon dioxide emissions in China, and its low-carbon transition is a pivotal lever for achieving the dual carbon goals. However, there remains a lack of focused studies on the low-carbon transition of power generation enterprises in the existing literature. To address this gap, this paper constructs a corporate low-carbon transition planning model integrating multidimensional factors including technological, economic, and environmental considerations. It analyzes the decarbonization pathways for power generation enterprises to achieve carbon neutrality by 2060 under the current policy. Furthermore, it conducts comparative simulations of several low-carbon transition scenarios for future power companies. The findings indicate that, for power generation enterprises, advancing carbon neutrality moderately ahead of schedule can yield certain benefits, but overly aggressive timelines may lead to steep cost escalations. Additionally, future policies are likely to drive increased energy storage deployment, necessitating preparatory technological and resource investments in relevant enterprises. Finally, the paper proposes solutions for decommissioned coal-fired power units, recommending their retrofitting or the integration of carbon capture and storage (CCS) technologies, which could be assigned roles in grid peak-shaving and emergency backup. Figures and Tables | References | Related Articles | Metrics

Select

Power Allocation Strategy for Wind Power Hybrid Storage Systems Based on Variational Modal Decomposition-Multifuzzy Control LI Jianlin, SUN Haoyuan, ZHAO Wending, LIANG Ce, LIANG Zhonghao, YUAN Xiaodong 2025, 59 (10):  1498-1509.  doi: 10.16183/j.cnki.jsjtu.2023.572 Abstract ( 1513 )   HTML ( 2 )   PDF (3763KB) ( 112 )   Save A power allocation strategy based on variational modal decomposition-multifuzzy control for wind power hybrid storage system is proposed to address the poor grid-connected power quality caused by the uncertainty of wind power output and the poor power allocation of hybrid storage systems. First, Latin hypercubic sampling and Euclidean distance method are used to generate a typical scenario of wind power considering the uncertainty of wind power output. Then, the variational modal decomposition optimized by the positive cosine algorithm is used for the initial allocation of wind power to obtain the grid-connected power of wind power which is lower than the upper limit of the grid-connected fluctuation and the levelling power of the hybrid energy storage system. Finally, the load state of the hybrid energy storage system is partitioned, and a power redistribution strategy under multi-fuzzy control is proposed to achieve the correction of the power of the hybrid energy storage system by considering the system load state and the characteristics of the hybrid energy storage. Simulation results show that the proposed strategy can suppress wind power fluctuations and obtain stable grid-connected power. Additionly, it can effectively solve the overcharging and over-discharging problems of the hybrid energy storage system. Figures and Tables | References | Related Articles | Metrics

Select

Assessment and Extension Method for Stable Operation Domain of DFIG in Asymmetric Weak Grid FEI Renxiang, XU Hailiang, GE Pingjuan, CHEN Xiangyu 2025, 59 (10):  1510-1522.  doi: 10.16183/j.cnki.jsjtu.2023.512 Abstract ( 1568 )   HTML ( 0 )   PDF (5687KB) ( 395 )   Save In asymmetric weak grid, there exists a complex coupling path between the positive- and negative-sequences of the impedance between a doubly-fed wind turbine (DFIG) and the grid, leading to intricate interactions. Since grid codes require wind turbines to provide positive- and negative-sequence dynamic reactive power support, improper settings of these currents may result in system instability and oscillations. Therefore, this paper first develops a sequence impedance model of the DFIG-grid system using a harmonic linearization method, revealing the effects of positive-sequence active current, positive-sequence reactive current, and negative-sequence reactive current on system stability, and analyzes the stability mechanism induced by inter-sequence coupling. Furthermore, considering stability constraints, grid codes, and converter capacity, it characterizes the stable operating domain of the DFIG. To solve the problem of insufficient stable operating range in weak grid, it proposes an adaptive oscillation suppression phase-locked loop (PLL) method, which adaptively suppresses the oscillatory component in the PLL input, thereby extending the stable operating domain of the DFIG. Finally, simulation results verify the correctness of the theoretical analysis and the effectiveness of the proposed control method. Figures and Tables | References | Related Articles | Metrics

Select

Three-Vector Model-Free Predictive Current Control Method for Grid-Connected Inverters with Sampling Noise Compensation CAO Wenping, WANG Yao, ZHANG Yue, LUO Kui, HU Cungang, RUI Tao 2025, 59 (10):  1523-1532.  doi: 10.16183/j.cnki.jsjtu.2023.499 Abstract ( 1549 )   HTML ( 3 )   PDF (5000KB) ( 103 )   Save To address the issues of large current ripple, stagnant current gradient update, and sampling noise interference in the model-free predictive current control method for grid-connected inverters based on look-up table, a three-vector model-free predictive current control method with sampling noise compensation is proposed. First, the output current of each control period is predicted by using the current gradient corresponding to the three-voltage vectors, and the action time of each vector is determined by a cost function to reduce the current ripple. Then, based on the overlapping relationship between the coordinate components of the three vector and the basic vector, a two-step updating method is used to eliminate the stagnation phenomenon. Finally, according to the impact of sampling noise on current gradient updating, a second-order generalized integrator is employed to estimate and compensate the gradient error, thereby improving the accuracy of current gradient. The feasibility and effectiveness of the method proposed is verified by simulation and experiment. Figures and Tables | References | Related Articles | Metrics

Select

Junction Temperature Algorithm of IGBT for Interface Converter in Optical Storage Microgrid System Considering Three-Dimensional Transverse Heat Conduction XU Yang, XIAO Qian, JIA Hongjie, JIN Yu, MU Yunfei, LU Wenbiao 2025, 59 (10):  1533-1545.  doi: 10.16183/j.cnki.jsjtu.2023.577 Abstract ( 1405 )   HTML ( 0 )   PDF (6989KB) ( 717 )   Save It is difficult for the existing junction temperature algorithms of insulated gate bipolar transistor (IGBT) to evaluate the impact on the thermal diffusion angle of the IGBT module under varying output power and heat dissipation conditions of optical storage unit interface converters in optical storage microgrids, which results in limited accuracy of junction temperature algorithm and poses a huge challenge to system thermal management. To address the above issues, a junction temperature algorithm of IGBT in interface converters in optical storage microgrid systems is proposed considering three-dimensional transverse heat conduction (3-D THC). First, a physical thermal model of power devices is established considering the thermal coupling between multiple chips in the optical storage microgrid system. Then, a junction temperature algorithm considering 3-D THC is further proposed based on the established physical model, and a thermal network model considering 3-D THC is established, which effectively improves the calculation accuracy of current state thermal parameters and power module thermal diffusion angle. Finally, the accuracy of the proposed model is verified using finite element analysis in the PinFin heat sink structure. The simulation results show that compared with various junction temperature algorithms, the proposed algorithm has the smallest error in junction temperature calculation under steady-state and sudden power change conditions, with approximately 3.11% and 3.65% respectively, which increases accuracy by 11.53% and 61.93% respectively compared with the algorithm not considering thermal diffusion angle (α=0). The proposed algorithm also has the highest junction temperature accuracy and the smallest error under different heat dissipation conditions. Figures and Tables | References | Related Articles | Metrics

Select

Effect of Potential Distribution of Main Shield on Internal Insulation Performance of Vacuum Interrupter CHENG Xian, LI Guanjun, GE Guowei, DU Shuai, ZHANG Wanlong 2025, 59 (10):  1546-1557.  doi: 10.16183/j.cnki.jsjtu.2023.553 Abstract ( 1214 )   HTML ( 1 )   PDF (8618KB) ( 110 )   Save As an environmentally friendly switchgear technology, vacuum circuit breakers have a wide range of application prospects. However, both single and break vacuum circuit breakers face the issues of uneven potential distribution in the main shielding case of the vacuum arc extinguishing chamber, with more prominent potential imbalance in the tank structure. To study the effect of the potential distribution of the main shielding cover on the internal insulation performance of a vacuum interrupter, a partial voltage model of the main shielding case of a vacuum interrupter is established. The COMSOL software is used to calculate and analyze the effect of the main shielding case potential change on the internal electric field by placing an external capacitor around the vacuum interrupter to adjust the share of the main shielding case potential in the inter-fracture potential. Based on the simulation results, power frequency and lightning impulse withstand voltage experiments are conducted on a 10 kV vacuum arc extinguishing chamber at different main shielding case voltages. The results show that the internal electric field strength decreases and then increases as the main shielding case potential rises, with the minimum peak field strength inside the vacuum interrupter occurring at 50% main shielding voltage. The simulation and experimental results are basically consistent. At a contact distance of 6 mm, the power frequency breakdown voltage increases by 5.4% and the lightning impulse voltage increases by 6.7% when the potential of the main shielding case is 50% of the inter fracture potential. This study provides reference for improving the internal insulation performance of vacuum arc extinguishing chambers and for the application of higher voltage level vacuum circuit breakers. Figures and Tables | References | Related Articles | Metrics

Electronic Information and Electrical Engineering

Select

An Improved Multi-Objective Evolutionary Algorithm for Grid Map Path Planning DONG Dejin, WANG Changcheng, CAI Yunze 2025, 59 (10):  1558-1567.  doi: 10.16183/j.cnki.jsjtu.2024.032 Abstract ( 370 )   HTML ( 0 )   PDF (4493KB) ( 1277 )   Save Multi-objective path planning on large-scale grid maps is characterized by a large number of nodes and multiple targets. Existing algorithms struggle to balance the speed and quality of solving the Pareto front (PF). Therefore, studying efficient optimization algorithms based on the PF has certain theoretical significance. First, a weighted graph modeling method based on cost vector is proposed, and optimization algorithms for solving large-scale problems are studied accordingly, which significantly saves time and costs compared with graph search algorithms. Then, to address the issue of low quality of the PF solutions, an improved multi-objective evolutionary algorithm is proposed, which includes a new initialization strategy. Individual and environment selection strategies are designed based on the concepts of angle and shift-based density. These improvements take both population diversity and convergence into account, thereby improving the solving efficiency. Finally, comparative simulation experiments are conducted to verify the effectiveness of the improved algorithm. Figures and Tables | References | Related Articles | Metrics

Select

Detection of Roadside Vehicle Parking Violations Under Random Horizontal Camera Condition ZHAN Zehui, ZHONG Ming’en, YUAN Bingan, TAN Jiawei, FAN Kang 2025, 59 (10):  1568-1580.  doi: 10.16183/j.cnki.jsjtu.2023.578 Abstract ( 394 )   HTML ( 0 )   PDF (46166KB) ( 2447 )   Save Investigation and punishment of vehicle parking violations is important in urban traffic management. Considering the time-consuming and labor-intensive nature of manual law enforcement, as well as the limited scope of fixed camera monitoring and detecting, exploring more flexible and efficient automatic detection methods has a great practical significance. Thus, a cruise detection technology is proposed, which is suitable for mobile carriers requiring no stopping and can be completed in a single pass. First, a vehicle parking violation image dataset named XMUT-VPI is collected and constructed under the conditions of approximate horizontal views and random shooting angles, laying a data foundation for the research. Then, a multitask parking network (MTPN) is constructed as an encoder to extract the key element information required for stop violation judgment. With the aid of the self-designed deformable large kernel feature aggregation module (DLKA-C2f) and cross-task interaction attention mechanism (CTIAM), a highest average detection accuracy of 90.3%, a minimum average positioning error of 4.4%, and a suboptimal average segmentation intersection ratio accuracy of 78.5% are achieved. Finally, an efficient decoder is designed to further extract the skeleton features of the parking space line and fit the visible area of the main parking space, which helps match the target vehicle and analyzes the positional condition between its tire ground-touching points and the main parking space. In addition, a judgment principle is provided for three typical behaviors of illegal parking, improper parking, and standardized parking. Experimental results show that the algorithm attains a comprehensive accuracy rate of 98.1% for vehicle parking violation detections across diverse complex interference scenarios, which outperforms existing mainstream methods and can provide technical supports for fully automate road cruise management of parking violatic. Figures and Tables | References | Related Articles | Metrics