23 May 2025, Volume 44 Issue 5
    

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    Treatise and Report
  • YAO Gang, YOU Xiaolong, ZHOU Lidan, LUO Chengdong, YU Tianyou, WANG Jie
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 1-11. https://doi.org/10.12067/ATEEE2407002
    Abstract ( ) Download PDF ( )   Knowledge map   Save
    At high altitudes, the low air density, reduced pressure, and weak convection make traditional air cooling insufficient for meeting the heat dissipation requirements of the energy storage converter PCS. To enhance the heat dissipation performance of the IGBT module in high-altitude areas, a novel optimization design method for PCS liquid cooling radiators using the multi-objective gray wolf optimization algorithm (MOGWO) has been proposed. Initially, a simulation model of an NPC three-level LCL grid-connected inverter was developed using PLECS software to calculate the total power loss of the IGBT module. The IGBT module was then modeled in three dimensions using SolidWorks. Subsequently, a liquid-cooled radiator with a snake-shaped flow path was designed. The radiator’s internal and external structural variables have been optimized using the multi-objective gray wolf optimization algorithm, multi-objective particle swarm optimization algorithm, and multi-objective genetic algorithm. A three-dimensional model of the radiator was created based on these optimization results. Following this, fluid-structure coupling simulations were conducted using finite element analysis in ANSYS-Fluent. The simulation results have been compared, revealing that the heat sink performance is improved the most after MOGWO optimization. Finally, hardware has been assembled based on the optimized design, and its reliability was tested and verified in a high-altitude environment.
  • YANG Guixing, SUN Yiqian, GUO Xiaolong, KANG Pengpeng, QI Hongyan, TIAN Xu, WANG Yang
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 12-22. https://doi.org/10.12067/ATEEE2306082
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    Doubly fed wind farm via DC transmission system contains a large number of nonlinear switches and controls, which is easy to cause oscillation instability. Most of the existing studies on the stability analysis of large-scale wind farms are based on simplified models, and their rationality in broadband has not been fully verified. This paper takes the doubly fed wind farm through line commutated converter high voltage direct current (LCC-HVDC) as the analysis scenario, first establishes the detailed impedance model of the wind farm, and establishes the equivalent impedance model of a single machine of the wind farm according to the equivalent method of the wind farm, and verifies the accuracy of the equivalent model through simulation comparison. On this basis, combined with the impedance model of LCC-HVDC, the impedance analysis circuit of the wind power transmission system via DC is established, and the instability factors and mechanisms of the interconnected system under different operating conditions are analyzed. It is found that both the number of wind turbines and the power of DC transmission have a significant impact on the stability of the system.
  • XU Ke, LIU Chunxi, LIN Zhiwei, HONG Fangrui
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 23-33. https://doi.org/10.12067/ATEEE2310061
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    In response to the challenges of computational burden and lengthy switching behavior encountered when employing Finite-Control-Set Model Predictive Control (FCS-MPC) for diode Neutral Point Clamped (NPC)-type three-level grid-connected inverters, this paper proposes a simplified model predictive control strategy based on an event-triggered mechanism. The strategy effectively reduces the number of switching vectors that need to be traversed and optimized by introducing a large sector division and judgment mechanism based on the traditional model predictive control method, thereby reducing computation time. Simultaneously, active damping techniques are applied to mitigate the risk of LCL-type filter resonance during system operation. Leveraging inequality approximation theory, the preset threshold of state error for event-triggered control is derived. Upon reaching the event-triggered boundary, the control rule is altered, triggering FCS-MPC, thus avoiding redundant operations and reducing the number of switching transitions, consequently lowering the system’s switching losses. The superiority of the proposed control method over traditional proportional-integral space-vector pulse-width modulation control and cost function optimization model predictive control methods is validated through comparative experiments.
  • FENG Yuyao, FENG Nan, XIONG Xuejun, ZHANG Yufan, NIU Tao
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 34-46. https://doi.org/10.12067/ATEEE2311051
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    With the integration of large-scale clean energy sources such as wind/light and the operation of more and more DC lines, the voltage safety issue of AC/DC power grids is becoming increasingly prominent, and how to determine the safe range of grid voltage under N-1 faults is an important problem to be selected it. The existing methods mostly focus on the static characteristics of the power system, and fail to fully consider its dynamic characteristics and fail to achieve an effective balance between calculation speed and accuracy. In response to this issue, this article proposes an adaptive dynamic dimensionality reduction method, which involves dimensionality reduction from the fault dimension, reactive voltage dimension, and reactive equipment dimension. The original voltage safety domain problem is simplified using the first-order trajectory sensitivity method, and error analysis is performed to verify the dimensionality reduction effect. Finally, the accuracy and effectiveness of the proposed method were tested using an improved IEEE 39 node system. And the accuracy of the proposed method is further verified in terms of reactive power reserve optimization.
  • YU Xuejuan, WANG Jun, WANG Shihan, ZHAO Yuhang, QIN Boyu
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 47-55. https://doi.org/10.12067/ATEEE2311019
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    Multi-energy systems consisting of electricity, heating and natural gas networks are recognized as an important strategy for reducing carbon emissions from the energy sector. The combination of hydrogen utilization and hydrogen-doped transportation offers great potential to achieve deep decarbonization without adding additional construction costs. However, traditional steady-state models and ideal dynamic cases are not sufficient to accurately characterize the real thermal properties of multi-energy systems, and there is a need for a more in-depth study of the dynamic energy transport process in the network. In this paper, a dynamic model of a multi-energy system containing hydrogen-rich compressed natural gas (HCNG) based on the generalized phase volume modeling approach is proposed. The model analyzes the thermodynamic behavior of energy media in various energy networks. Numerical studies demonstrate the benefits of the proposed multi-energy system model, especially in terms of operational cost reduction and renewable energy consumption.
  • WANG Zhenyi, ZHU Xinchun, HU Bin, LU Xuegang, ZHANG Bin, DU Sijun, XU Tianrui, DING Tao
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 56-65. https://doi.org/10.12067/ATEEE2302023
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    As the modern power system continues to evolve, the formation of large-scale interconnected network structures has become increasingly prominent. This development has led to a significant increase in low-frequency oscillation phenomena within the power system, posing a serious challenge to its safe and stable operation. Identifying the modes in low-frequency oscillation signals is a critical prerequisite for implementing appropriate measures or strategies to suppress these oscillations in the power system. To this end, this paper proposes a novel method for the modal identification of low-frequency oscillations in power systems based on deep learning and variational mode decomposition. This method initially employs the variational mode decomposition algorithm for noise reduction in low-frequency oscillation signals. Subsequently, a convolutional neural network is utilized to recognize the order of the denoised low-frequency oscillation signals. This recognition is then combined with the variational mode decomposition algorithm to separate the modes of the low-frequency oscillation signals. Finally, a multilayer perceptron is used to identify the parameters of each separated low-frequency oscillation mode, thereby accomplishing the modal identification of low-frequency oscillations. The effectiveness and accuracy of the proposed method in identifying low-frequency oscillation modes in power systems are validated through multiple simulation case studies.
  • WANG Fenghua, LI Haibo, DAN Yangqing, WANG Lei, ZHOU Hanze, ZHANG Lei
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 66-76. https://doi.org/10.12067/ATEEE2310068
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    In order to alleviate the double contradiction of power curtailment and power shortage caused by insufficient flexibility of power system with high proportion of new energy, an optimal operation model of industrial load aggregation response for improving the flexibility of provincial power grid was established. Firstly, the wavelet packet decomposition technology is used to calculate the electricity consumption correlation coefficient of upstream and downstream enterprises in the industrial chain. The industrial load response model, which takes into account the upstream and downstream of the industrial chain as well as process flow constraints, is established based on the concept of “virtual inventory”. Then, taking into account the operational constraints of the source-network-load-storage side of the power system, with the goal of minimizing the flexibility resource invocation cost and system flexibility gap cost, the decision variables of production equipment participating in demand response were integrated into the production simulation model, and an optimal operation model of industrial load aggregation response for the flexibility improvement of provincial power grid was established. Finally, based on the actual operation data of the provincial power grid and the actual production data of 80 enterprises upstream and downstream of multiple industrial chains, the simulation analysis is carried out. The results demonstrate that the established industrial load response model can effectively alleviate the new energy power curtailment and load power shortage in the system under the premise that the enterprise production capacity is not affected, and the flexibility adjustment potential of industrial load release is greater after considering the upstream and downstream constraints of the industrial chain.
  • DONG Jizhe, WANG Huaidong, CHEN Peiguang, CAO Jianshe, ZHENG Danchen
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 77-87. https://doi.org/10.12067/ATEEE2401010
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    The rapid development of new energy sources and the increasing variability of source-load dynamics pose numerous uncertainties and challenges to power system planning. There is an urgent need to establish a novel transmission expansion planning (TEP) model that can adapt to these uncertainties, aiming to enhance the reliability and cost-effectiveness of power grid planning. Considering the bidirectional chronological characteristics of source-load interactions, a chronological AC TEP method is proposed. The objective function is to minimize the sum of investment costs, generation operation costs, and wind abandonment costs. During the planning period, a loop chronological operational simulation model is established. The model is solved to obtain a planning solution that considers uncertainties in source-load dynamics. Finally, based on Garver’s 6 bus and IEEE 24 bus systems, simulation analysis is conducted with a stochastic TEP as a comparison. The simulation results indicate that, compared to stochastic TEP, the proposed chronological TEP can provide reasonable solutions, ensuring the reliable and cost-effective operation of the system to face the source-load uncertainties.
  • AI Liwang, MA Pengfei, MIAO Sen, JIANG Siyuan, XU Xiaozhuo,
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 88-96. https://doi.org/10.12067/ATEEE2312053
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    Due to the dual-rotor motion system and the strong nonlinear conductivity of the high-temperature superconductor (HTS), the numerical modeling of the HTS magnetic coupler is complicated and the calculation convergence is unsatisfactory. Therefore, a two-dimensional numerical modeling method for axial-type HTS magnetic couplers is developed by coupling the magnetic vector H and the magnetic scalar φ. Firstly, two numerical modeling methods derived from the H-φ formulation are introduced: moving grid method and generalized stretching operator method. The power-law exponential E-J relationship is used to characterize the strong nonlinear conductivity of the superconductor. The relative motion of the HTS-PM system is simulated by using the moving grid interface and the generalized stretching operator of the software COMSOL, respectively. Then, experimental validation confirmed the feasibility of both methods, which were then employed to establish two-dimensional simulation models for axial-type high-temperature superconducting magnetic couplings. Finally, the current density distribution, magnetic flux density distribution and transmission torque characteristics of the superconductor are obtained by simulation. The analysis shows that the results obtained by the two methods are basically consistent within the allowable error range, but the solution speed of the generalized stretching operator method is 6 times that of the moving grid method. Therefore, the generalized stretching operator method based on H-φ is given priority for the electromagnetic characterization of axial high temperature superconducting magnetic couplers.
  • New Technolog Application
  • ZHANG Jiening, OUYANG Sen, KANG Lan, GUO Yifan, ZHANG Jinming
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 97-107. https://doi.org/10.12067/ATEEE2405072
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    Under the development trend of distributed PV with high penetration rate into the distribution network, there is a real and urgent need to accurately recognize the area of roofs where PV can be constructed. In response to the demand for further identification processing for the lack of accurate roof area identification and the influence of roof foreign objects on the construction of PV power supply, this paper proposes a method for extracting the effective area of the roof of a building by integrating the image classification mechanism. First of all, this paper takes into account the influence of foreign objects on the effective roof area, and makes a new classification of different types of building roofs according to the geometric characteristics of the roof, edge characteristics, and the degree of utilization of the internal area, so as to reduce the influence of the complexity of the roof on the extraction accuracy. Then, this paper adopts image classification network and improved Mask-RCNN network to realize the classification and extraction of building roofs. Among them, increasing the image classification network reduces the influence of multi-type roofs on the learning ability of the network, and improving the Mask-RCNN network is based on the original network, introducing the attention mechanism module and optimizing the FPN network to improve the feature learning and extraction ability of the network. Finally, based on the constructed image sample library of roofs of single buildings, the effectiveness and accuracy of the method proposed in this paper are verified.
  • WANG Jinmei, WANG Yan
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 108-117. https://doi.org/10.12067/ATEEE2405030
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    Acetylene is a characteristic gas generated by high temperature overheating and various discharge faults inside transformers. Acetylene causes oil degradation and reduces insulation performance, as well as acid corrosion of metal surface inside transformers; The alarm value for acetylene content during operation of ultra-high voltage transformers is determined to be 1 μL/L, but the current research on dissolved gas prediction models in transformer oil has a significant prediction error for gas concentrations below 1 μL/L. This paper proposes a VMD-LSTM prediction model to accurately predict the low concentration of acetylene in transformer oil. Variational mode decomposition(VMD)is used to decompose acetylene time series data into intrinsic mode function(IMF), and the tolerance parameters are adjusted to reduce the impact of data noise on the model. The long short-term memory(LSTM)is combined for prediction. The prediction performance of the proposed model is verified, the root mean square error of the prediction model is 0010 9, the mean absolute error is 0008 7, and the mean absolute percentage error is 1641%, it means that a very ideal predictive effect is achieved.
  • CAO Jianwei, MA Wenbo, HUANG Zhihua, ZHOU Kaiyun, LAI Xunyang, SONG Guobing
    Advanced Technology of Electrical Engineering and Energy. 2025, 44(5): 118-128. https://doi.org/10.12067/ATEEE2310021
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    Zero-sequence voltage and current based single phase grounding fault detection and location methods in non-effectively grounded distribution network have limitations in practical use due to the lack of zero-sequence CT and PT in some cases. To deal with this problem, transient characteristics of the fault components of phase current under single phase grounding fault are analyzed based on the Karrenbauer Transformation and the single phase grounding fault detection method and section location method are proposed. PSCAD-based simulation results and verification results based on fault recording data show that the proposed method behaves well when single phase grounding fault with different impedances occurs in different sections. Besides, the proposed method can select the faulty phase automatically without using voltage signals, which is suitable for all IEDs.