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Table of Content

    28 July 2025, Volume 59 Issue 7 Previous Issue   
    New Type Power System and the Integrated Energy
    Energy Interaction and Energy Storage Sharing Optimization Method for Users, Base Stations, and Charging Stations
    HU Long, FANG Baling, FAN Feilong, CHEN Dawei, LI Xinxi, ZENG Run
    2025, 59 (7):  877-888.  doi: 10.16183/j.cnki.jsjtu.2023.407
    Abstract ( 1508 )   HTML ( 8 )   PDF (5843KB) ( 201 )   Save

    The internal energy optimization within a single entity of industrial users, base stations, and charging stations is constrained by local power supply and demand limitations, resulting in low utilization of flexible resources such as energy storage and insufficient energy utilization efficiency. To address these issues, an energy sharing and interactive optimization method is proposed for industrial users, base stations, and charging stations based on the quantification of their complementarity and a game-based pricing incentive mechanism. First, a complementary quantification model is developed based on the analysis of the characteristics of industrial users, base stations, and charging stations, using the standard deviation of net load as a complementary indicator. Then, considering the adjustable capabilities of air conditioning and electric vehicles, as well as the proactive decision-making abilities of industrial users, charging stations, and base stations, a master-slave game-based pricing model is established to incentivize the sharing of energy storage and energy interaction among these entities. Next, incorporating 0-1 integer variables, a solution method utilizes the adaptive differential evolution algorithm combined with the mixed-integer optimization theory. Finally, case studies validate that optimizing the energy storage and energy dispatch of industrial users, base stations, and charging stations in different time periods can effectively leverage their complementarity, enhance the economic benefits of each entity, improve the utilization of idle flexible resources, and enhance the overall energy self-consistency of the system.

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    Optimal Operation Strategy of Cascade Hydro-Wind-Solar-Pumped Storage Complementary System Considering Flexible Regulation Ability
    XIA Jinlei, TANG Yijie, WANG Lingling, JIANG Chuanwen, GU Jiu
    2025, 59 (7):  889-900.  doi: 10.16183/j.cnki.jsjtu.2023.419
    Abstract ( 1323 )   HTML ( 1 )   PDF (3256KB) ( 279 )   Save

    In the context of “carbon peaking and carbon neutrality”, the large-scale integration and consumption of wind and solar resources is an inevitable trend in future energy development. However, as the capacity of wind and solar power integration increases, the power system also requires more flexible resources to ensure secure operation. To investigate the flexible regulation of hydropower in the system, this study focuses on the downstream stations of the hydro-wind-solar-pumped storage clean energy base in the Yalong River Basin. Considering its flexible regulation capabilities, the study conducts day-ahead optimized operational strategy research for the complementary system. First, to address the challenges of site selection and high costs associated with independent pumped storage, steady-state models for hybrid pumped storage stations in a cascade hydro-wind-solar-pumped storage system are established. To overcome the limitations of traditional models such as low predictive accuracy and the subjective selection of long short-term memory (LSTM) hyperparameters, the particle swarm optimization (PSO) algorithm is used to optimize the parameters of LSTM and the optimized LSTM model is then used to forecast the output of wind and solar power. Next, in order to fully harness the flexible regulation potential of the complementary system, a multi-objective optimal dispatching model is developed considering the economic benefits and flexible regulation margin of the complementary system in the day-ahead time. The normal boundary intersection (NBI) method is employed to solve the multi-objective problem, which can obtain the Pareto optimal solutions with an even distribution. Finally, case studies are conducted based on the actual conditions of the Yalong River Basin. By analyzing different scenarios, the effectiveness of the proposed model and the supportive role of pumped storage in enhancing system flexibility are validated. The results demonstrate that the proposed approach not only balances system profits but also fully exploits the flexible regulation potential of the system, ensuring stable operation of the system.

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    Optimization Method for Combination of Residual Current Protection and Coincidence Brake Logic in a Low-Voltage Distribution System
    XU Han, ZHU Sanli, ZHANG Tengfei, CHEN Shu, LIU Mingxiang
    2025, 59 (7):  901-911.  doi: 10.16183/j.cnki.jsjtu.2023.438
    Abstract ( 964 )   HTML ( 1 )   PDF (1714KB) ( 26 )   Save

    Low-voltage distribution systems frequently experience leakage current accidents. However, it is challenging to distinguish fault characteristics in abnormal operating conditions, such as electric shock to biological organisms and three-phase imbalance, which leads to the improper operation of existing residual current protection devices, making it difficult to balance both the safety and continuity of power supply in low-voltage distribution systems. Therefore, an optimization method is proposed for combination of the residual current protection and the coincidence reclosing logic to address the ground fault caused by the leakage of the low-voltage distribution system. First, the residual current protection device and the automatic reclosing switch are installed in the low-voltage side outlet of the transformer. When the over-threshold residual current of the fault phase is detected, the instantaneous skip circuit breaker is used to ensure the safety of the power supply. Then, the robust empirical mode decomposition-approximate entropy value and the intrinsic mode function-time domain eigenvalue of the residual current signal are extracted, followed by the establishment of a genetic algorithm-backpropagation over-threshold status identification neural network. Finally, based on the neural network model, the electrical and three-phase imbalance characteristics are effectively separated. The action logic of the residual current protection value setting algorithm and the automatic coincidence brake is optimized to ensure the continuity of power supply. The simulation analysis shows that the error of the classification results of the model after seven iterations is only 9.49×10-9 with a correlation coefficient of 0.99, confirming the feasibility of the proposed method.

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    Optimal Allocation Method of Integrated Energy System Considering Joint Operation of Multiple Flexible Resources
    DENG Qianwen, LI Qi, QIU Yibin, LI Doumeng, HUO Shasha, CHEN Weirong
    2025, 59 (7):  912-922.  doi: 10.16183/j.cnki.jsjtu.2023.457
    Abstract ( 1220 )   HTML ( 3 )   PDF (3023KB) ( 278 )   Save

    Under the “carbon peaking and carbon neutrality” strategy, the penetration ratio of renewable energy is increasing, while the lack of flexible resources becomes a growing challenge. To address this and build a safe, efficient, low-carbon, and clean energy system, an integrated energy system (IES) optimization allocation method is proposed considering the joint operation of multiple flexibility resources. First, the modeling of the two stages of the power-to-gas equipment is refined, with the introducation of the coordinated operation of the hydrogen-doped gas turbine and the power-to-gas equipment to make full use of the low-carbon characteristics of H2. Carbon raw materials are provided for the power-to-gas facilities through carbon capture equipment realizing the recycling of CO2, thereby establishing a coordinated operation framework for flexible resource with hydrogen energy as the core. Then, aimed at the uncertainty of renewable energy output, the optimal clustering number is determined by Elbow method, and typical wind speed scenarios are obtained by K-means clustering algorithm. On this basis, an optimal allocation model is established with the objective of minimizing the sum of investment cost, operation and maintenance cost, replacement cost, environmental penalty, and wind abandonment penalty cost, taking into account equipment constraints, energy balance constraints, and flexibility constraints. To solve the nonlinearity, the large M method is adopted to linearize the model and complete the model solution. Finally, the method proposed is validated through an example based on measured data from a region in southwest China. The results show that the total cost of the IES is reduced by 10.22%, the penetration rate of new energy is increased by 6.01%, and the cost of environmental penalties is reduced by 2.65%. The proposed method effectively improves the economy of the system and the consumption of new energy, and significantly reduces system carbon emissions.

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    Optimization Model for Safeguarding Vulnerable Components in Integrated Energy Systems Based on Weighted Betweenness
    ZHANG Chenwei, WANG Ying, LI Yaping, ZHANG Kaifeng
    2025, 59 (7):  923-937.  doi: 10.16183/j.cnki.jsjtu.2023.403
    Abstract ( 1461 )   HTML ( 2 )   PDF (3112KB) ( 113 )   Save

    Utilizing the complex network theory to mitigate vulnerabilities mitigation in integrated energy systems is significant for enhancing the resilience of sustained energy supply, especially against deliberate physical attacks and natural disasters. To implement more precise preventive measures for vulnerable components in integrated energy systems, this paper proposes a weighted betweenness-based protection optimization model for safeguarding vulnerable segments. The model aims to minimize the weighted betweenness loss incurred post attacks and damages, while simultaneously considering strategies such as establishing backup nodes and backup lines, enhancing physical protection of nodes and lines, and adding new lines. These strategies are subject to constraints such as protection requirements, budget limitations, and constraints on the types and quantities of new lines. The model optimization provides the optimal protection strategies within the allocated budget. To address the complex betweenness computations and non-linear objective functions, the model is formulated as a bilevel structure based on the nature of protection measures first. Then, the lower-level model is solved using a local linearization technique, and a “genetic-mixed integer linear programming” algorithm is proposed for solving the model with high precision and efficiency. The simulation results demonstrate that under conditions of equivalent attack and damage, the system with the optimal protection strategy achieves reduction of 45.37% in weighted betweenness loss compared with that without protection. The optimal strategy outperforms the other five protection strategies considered within the allocated protection budget.

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    Black-Start Coordinated Control Strategy of Optical Storage Microgrid Considering State of Charge Balance of Distributed Energy Storage
    ZHOU Xia, CHEN Wenjian, DAI Jianfeng, XIE Xiangpeng
    2025, 59 (7):  938-951.  doi: 10.16183/j.cnki.jsjtu.2023.395
    Abstract ( 976 )   HTML ( 1 )   PDF (2835KB) ( 224 )   Save

    With the increasing proportion of new energy in the power grid, photovoltaic microgrids equipped with large-capacity distributed energy storage have the potential to support the black start of thermal power plants. To address this issue of frequent fluctuation in the active power of the microgrid during the black-start period, and the risk of exceeding the state of charge (SOC) limits of the distributed energy storage, which could lead to the failure of the black-start, a coordinated control strategy for the optical storage microgrid black-start is proposed considering the SOC balance of the distributed energy storage. Based on the SOC of the distributed energy storage unit, the proposed strategy combines the load tracking control of the photovoltaic system and the maximum power tracking (MPPT) control, which ensures that the photovoltaic output effectively tracks the microgrid load to prevent the SOC from exceeding its limit. When the photovoltaic output becomes unbalanced with the black-start load, the distributed energy storage system is used to smooth the active power difference of the system. Furtherfore, the droop control for the traditional energy storage units is improved to ensure the active power distribution based on the energy storage SOC, enabling the SOC balance among energy storage units. Through secondary control of the energy storage units based on distributed consensus protocol, the strategy ensures frequency stability in the active power fluctuation during the black start process. The simulation results verify the feasibility of black start and the effectiveness of the proposed control strategy.

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    Single-Phase High Frequency Inverter Narrow Pulse High-Quality Modulation Method
    ZHANG Guopeng, CHEN Dongan, TAO Haijun, LIU Yonghui, MA Yuan
    2025, 59 (7):  952-961.  doi: 10.16183/j.cnki.jsjtu.2023.426
    Abstract ( 1052 )   HTML ( 1 )   PDF (7288KB) ( 135 )   Save

    To analyze the narrow pulse issue of high-frequency single-phase two-level inverter running at high modulation ratio, the effects of modulation ratio, carrier frequency, and dead time on the narrow pulse under sinusoidal pulse width modulation (SPWM) strategy are examined, and the distribution law of the narrow pulse within the modulating wave period is derived. Based on this analysis, a high-quality modulation method without narrow pulses is proposed to eliminate narrow pulses within the modulation cycle of high-frequency inverters. To address the waveform distortion issue at the modulation peak and valley in this method, a three-beat carrier prediction method is designed to further improve the quality of the alternating current (AC) output waveform by modifying the modulation within the narrow pulse area. Finally, a single-phase full bridge inverter experimental platform is built to verify the feasibility and effectiveness of the proposed narrow pulse-free high-quality modulation method.

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    Physics-Informed Fast Transient Stability Assessment of Non-Fixed Length in Power Systems
    LI Xiang, CHEN Siyuan, ZHANG Jun, KE Deping, GAO Jiemai, YANG Huanhuan
    2025, 59 (7):  962-970.  doi: 10.16183/j.cnki.jsjtu.2023.452
    Abstract ( 1488 )   HTML ( 1 )   PDF (1706KB) ( 814 )   Save

    Against the backdrop of “dual carbon” goals, the construction of a new power system with new energy as the main component is the main direction and key way for the transformation and upgrading of the power industry. Research into fast and accurate evaluation of transient power angle stability in the context of new power systems is of great significance. To address this, a new transient power angle stability evaluation method is proposed for power systems with grid-forming new energy based on the physics-informed sequence-to-sequence (PI-seq2seq) neural networks and cascaded convolutional neural networks models. First, the PI-seq2seq network structure is used to predict the future power angle trajectory, and a loss function with physical loss terms is constructed to guide the model training process, which avoids the long-duration time-domain simulation to ensure fast transient evaluation. Then, predicted power angle trajectory is taken as input by the cascade convolutional neural networks to evaluate the transient stability and its confidence level. A threshold judgment mechanism for the evaluation confidence level is configured to realize the transient stability judgment of the non-fixed evaluation length, which overcomes the impact of the fixed power angle curve length on the evaluation results. Finally, the method proposed is verified in the Kundur system, and the simulation results show that it has obtained satisfactory results in both the power angle curve prediction and the stability evaluation.

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    Transient Modeling and Characteristic Comparative Analysis of Grid-Forming VSC with and Without Current Control
    REN Xiancheng, LI Shangzhi, LI Yingbiao, HU Jiabing, XU Taishan, BAO Yanhong, WU Feng
    2025, 59 (7):  971-982.  doi: 10.16183/j.cnki.jsjtu.2023.416
    Abstract ( 1093 )   HTML ( 2 )   PDF (2357KB) ( 2290 )   Save

    As the support capacity of renewable energy generation equipment for the power grid needs enhancement, grid-forming control has attracted extensive attention, among which the virtual synchronous generator (VSG) has emerged as a key research frontier and is already being applied in engineering demonstration. Voltage source converter (VSC) with VSG as the synchronization link can be classified into voltage and current dual loop control and direct voltage control according to whether there is a current control loop in the structure. The difference in the two control structures has a significant impact on the transient characteristics of VSC. To study the difference between transient characteristics of two kinds of VSCs, the transient models are developed based on the “power excitation-internal voltage response” model, and the formation mechanism of internal voltage and transient characteristics are comparatively analyzed. Since the VSG simulates the operation characteristics of the synchronous machine, the equivalent inertia and equivalent damping of the VSC are analytically obtained at the electromechanical scale, and their transient behaviors are compared. It is found that the equivalent inertia and damping of a VSC with direct voltage control remain constant, while those of a VSC with voltage and current dual loop control exhibit time-varying characteristics and are numerically smaller than of the direct voltage control system. Finally, the validity of the theoretical analysis is confirmed by electromagnetic transient simulation.

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    Characteristics of Surface Charge Accumulation on Direct Current GIL Insulators Under Different Dominant Mechanisms Considering Surface Trapping Effect
    WANG Yaogang, WANG Zheming, LI Ke, JIA Bowen, YANG Hua, YAN Wu, LU Wu
    2025, 59 (7):  983-994.  doi: 10.16183/j.cnki.jsjtu.2023.420
    Abstract ( 777 )   HTML ( 0 )   PDF (33886KB) ( 12 )   Save

    The existing mathematical models for charge accumulation at the gas-solid interface can hardly illustrate some microscopic mechanisms, which need improvement. Therefore, based on the theory of bipolar charge transport at insulating interfaces, a charge transport model is proposed for gas-solid interfaces including the mechanisms of trapping and de-trapping of nonequilibrium carriers, which is incorporated into a three-dimensional simulation model for the charge accumulation on the surface of direct current gas-insulated transmission lines (DC GIL). Numerical simulations of the surface charge accumulation with the dominance of gas-side charge and solid-side charge are conducted, respectively. The simulation results show that in the charge accumulation process dominated by the solid-side charge, halo-like charge and unipolar charge spots appear on the insulator surface. With the increase of energization time, the number of unipolar charge spots increases and the distribution area expands. In the process dominated by gas-side charge, in addition to the appearance of halo-like charge and unipolar charge spots, a pair-distributed bipolar discrete charge speckle occurs at a later stage. Subsequently, the simulation results are analyzed for mechanisms, on the premise that the simulation results are in good contrast with some of the experimental phenomena. The findings of this study can deepen the understanding of the impact of surface trapping effects on charge accumulation behavior.

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    Feature Extraction and Anomaly Identification Method for Power Customer Price in Power Market Enviroment
    ZHU Feng, SHAN Chao, WU Ning, CAI Qixin, ZHU Yunan, LIU Yunpeng, ZUO Qiang
    2025, 59 (7):  995-1006.  doi: 10.16183/j.cnki.jsjtu.2023.448
    Abstract ( 1546 )   HTML ( 1 )   PDF (2218KB) ( 328 )   Save

    Identifying electricity price anomalies and exploring the underlying reasons in such a complex market environment, especially with incomplete data, is a key issue for promoting the orderly operation of power market and ensuring the reasonable interests of power customers. Therefore, a method is established for feature extraction and anomaly identification of electricity prices for power customers. First, an electricity price feature vector is constructed, and its dimensionality is reduced using a spectral clustering algorithm. Then, typical electricity price characteristics are extracted as the basic standard for determining price anomalies. Next, the similarity between each power customer and typical electricity price characteristics is calculated. Finally, electricity price anomalies are identified in two stages. The causes of anomalies are initially and rapidly identified based on electricity consumption and trading behavior, and then further identified in-depth. Case analysis shows that this method can quickly and effectively extract typical electricity price features and identify anomalies. The reasons behind these anomalies are further analyzed from both electricity consumption and trading behaviors, and corresponding improvement measures are proposed.

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    Energy Services Demand Forecasting Combined with Feature Preferences and Bidirectional Long- and Short-Term Memory Networks
    KANG Feng, TAN Huochao, SU Liwei, JIAN Donglin, WANG Shuai, QIN Hao, ZHANG Yongjun
    2025, 59 (7):  1007-1018.  doi: 10.16183/j.cnki.jsjtu.2023.458
    Abstract ( 1421 )   HTML ( 2 )   PDF (5048KB) ( 179 )   Save

    Accurate and efficient demand forecasting of customer energy services is crucial for quality and risk management in grid customer service. Therefore, this paper proposes a user energy service demand prediction model based on feature selection. The methodology includes introducing a sampling algorithm to solve the class imbalance problem in the data on the basis of analysing the user energy service data, reducing the dimensionality of the data based on an autoencoder to ensure efficient clustering of the K-mean algorithm, constructing a feature selection algorithm based on a lightweight gradient lifting machine to filter the effective features and improve the training efficiency of the prediction model, and establishing a bidirectional long- and short-term memory neural network multi-label predicting model based on an attentional mechanism to refine the user’s energy service demand. Through the analysis of 720 000 work order data from Guangdong Power Grid over three years, showing that the model proposed can effectively improve the prediction accuracy and speed.

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    Naval Architecture, Ocean and Civil Engineering
    Evolutionary Topological Optimization Method for Local Rib Addition in Single-Layer Shell Structures
    WANG Rungu, DONG Xiao, GONG Jinghai
    2025, 59 (7):  1019-1028.  doi: 10.16183/j.cnki.jsjtu.2023.490
    Abstract ( 114 )   HTML ( 0 )   PDF (30863KB) ( 39 )   Save

    This paper investigates the topological optimization of locally reinforced single-layer reticulated shell structures to enhance their economy and overall stability. Using steel consumption as the evaluation index, a topological optimization method based on the evolutionary structural optimization algorithm is proposed for single-layer reticulated shell structures. The strain energy is calculated based on the internal force distribution of the structural members, and a grid strength evaluation criterion is established considering the specific characteristics of single-layer reticulated shell structures. In the iterative calculation, pyramids are added to strengthen the grid with excessive strain energy, while new pyramids with insufficient strain energy are removed. The steel consumption and the overall stability of the reticulated shell structure before and after optimization are compared to verify the effectiveness of the structural optimization method. After topological optimization, the locally reinforced single-layer reticulated shell structure exhibits a reduced steel consumption and improved overall stability compared to the initial structure. The results can provide technical references for optimizing the local reinforcement design of single-layer reticulated shell structures, and also provide references for similar structural optimization problems.

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    Inversion and Simulation Algorithm of High-Density Surface Wave Method for Pseudo Co-Seismic Source and Its Application
    JIN Tao, GAO Bin, WANG Qiangqiang, ZHOU Hang, HE Wen, FENG Shaokong
    2025, 59 (7):  1029-1040.  doi: 10.16183/j.cnki.jsjtu.2023.430
    Abstract ( 115 )   HTML ( 1 )   PDF (21108KB) ( 85 )   Save

    Accurate detection of karst is of utmost importance for infrastructure construction. However, traditional surface wave methods for data acquisition and processing fall short in meeting the requirements of large-scale infrastructure projects in karst areas. In order to address these limitations, an improved approach called the high-density pseudo-source surface wave method has been proposed based on the traditional surface wave method. This method involves the collection of a large volume of data through high-density data acquisition, where multiple measurements at the same location with different pseudo-sources are combined during the inversion process, significantly enhancing the efficiency and utilization of the detection process. A workflow for establishing numerical models using the high-density pseudo-source surface wave method has been developed and validated. Additionally, field applications of this method have been conducted. The research findings demonstrate a strong correlation between the results obtained from the high-density pseudo-source surface wave method and those from drilling exploration, highlighting a significant improvement in karst detection. These achievements provide valuable insights and references for the rapid and accurate detection of karst in large-scale infrastructure projects.

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    Fast Prediction for Roll Motion of a Damaged Ship Based on SVR
    LIU Han, SU Yan, ZHANG Guoqiang
    2025, 59 (7):  1041-1049.  doi: 10.16183/j.cnki.jsjtu.2023.431
    Abstract ( 182 )   HTML ( 1 )   PDF (5899KB) ( 785 )   Save

    ANSYS-AQWA is applied to analyze the rolling motion response of the damaged ship DTMB5415 under various working conditions. The results are compared with those in exiting literature to validate the practicality of the hydrodynamic model. Additionly, the rolling motion response database for the damaged ship is constructed. The support vector regression (SVR) algorithm is used to model the rolling motion database for identification, exploring the relationship between the operating condition factors and coefficients in the equation of roll motion. Finally, a fast prediction model for rolling motion is constructed and validated, offering a significant improvement in the prediction efficiency compared with traditional computational fluid dynamics models.

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    Materials Science and Engineering
    First-Principle Investigation of Reaction Pathways for Nitrate Reduction on (101) Surface of Anatase TiO2
    HE Xiyu, YANG Fan, ZHANG Junliang
    2025, 59 (7):  1050-1058.  doi: 10.16183/j.cnki.jsjtu.2023.456
    Abstract ( 261 )   HTML ( 1 )   PDF (6026KB) ( 209 )   Save

    To understand the nitrate reduction process on the (101) surface of anatase TiO2-x, two surface models one with oxygen vacancies and one without are established. Density functional theory calculations are then employed to reveal the effects of oxygen vacancy on the surface electronic structure, nitrate adsorption configuration and energy, reduction pathways, competitive reactions, and product selectivity. The results show that oxygen vacanies alter the adsorption configuration and significantly reduce the nitrate adsorption energy on the surface, and shift the potential determining step from nitrate adsorption to the subsequent hydrogenation processes. In addition, oxygen vacancies dramatically increase the desorption energy of intermediates such as NO2 and NO, thus inhibiting the formation of by-products and improving electrocatalytic selectivity. The promotion of the competitive hydrogen evolution reaction by oxygen vacancies is far less pronounced compared to that of nitrate reduction reaction. Therefore, oxygen deficient TiO2-x emerges as a promising catalyst for electro-catalyzing nitrate reduction to produce ammonia.

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