Volume 40, Issue 4 (2025)
Smart grid
Equivalent inertia estimati on of electric power system considering virtual inertia of wind power
Pin gping LUO and Jie CHEN
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.001
Large-scale wind power i ntegration weakens the inertia level of the electric power system and brings challenges to the frequency stability of the electric power system.It is urgent to accurately estimate the inertia level of the system to ensure its safe operation.Therefore，an equivalent inertia estimation method of an electric power system considering the virtual inertia of wind power is proposed.Firstly，the inertia response of the synchronous generator and wind turbine is analyzed，and the principle of system equivalent inertia estimation is explained.Secondly，the Box-Jenkins model is used to dynamically model the power generation device.Based on the active-frequency disturbance data at the connecting bus of the unit，the bias compensation recursive least squares algorithm with forgetting factors is used to identify the parameters in the model.On this basis，the inertia constants contained in the model parameters are extracted，and the equivalent inertia of the system is calculated.Finally，a simulation analysis is conducted using examples to verify the effectiveness of the proposed method.The simulation results show that the proposed method can accurately estimate the equivalent inertia of the system under different disturbance types and different wind power penetration rates.
Coordinated expansion planning m odel of new energy cluster integration and regional power grid s considering off -grid risks
Yunche SU, Yang LIU, Xi aodi WANG, Yumeng ZHEN, Tao HU, and Dawei CHEN
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.002
Against the backdrop of large-scale new en ergy clusters and base construction，faults in the grid-connection lines of new energy collection stations may cause significant power disturbances，posing risks of inducing the cascading off-grid occurrence of new energy sources and deteriorating system frequency stability.To this end，this paper builds a coordinated expansion planning model for new energy cluster integration and regional power grids，with off-grid risks considered.Firstly，the main problems in the regional grid expansion planning under the integration of new energy clusters are analyzed.Subsequently，a coordinated planning model of new energy cluster integration and the expansion of regional power grid structures is built.Then，in the optimization of new energy station clusters，by considering the constraints of the utilization rate of grid-connected lines at the collection stations，the regional grid planning model takes constraints related to large-scale new energy off-grid risks under faults of grid-connected lines at collection stations into account，including the system frequency rate of change，frequency deviation，and post-fault line flow constraints.Finally，a case analysis based on the improved IEEE RTS- 79 system is conducted to validate the effectiveness of the proposed model and planning scheme.
Multi -dimensional time -frequen cy charac terization of transient waveforms on transmission line faults in ne w electric power systems
Li ZHANG, Shengnan LI, Shiya o WANG, Shoudong XU, Xiaotian LU, and Jinrui TANG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.003
When large-scale new energy，energy sto rage，and large-capacity flexible alternative current （AC） and direct current （DC） transmission equipment are integrated into new electric power systems，steady-state power frequency phase，and sequence component of current and voltage waveforms in transmission line faults are mainly depend on the low voltage ride through strategy of power electronic equipment，emergency control strategy，and current limiting link of electronic components and devices.The performance of traditional relay protection algorithms is significantly based on the power frequency.A new relay protection algorithm based on non-power-frequency transient components can make full use of the transient charging and discharging process caused by transmission line faults to distinguish between internal and external faults.Inspired by information-theoretic methods for characterizing waveform features，a multi-dimensional time-frequency characterization approach is proposed，which is based on the amplitude and variation rate of transient components in both the time-domain waveform and spectral distribution.This method fully exploits the differences in transient waveform features between internal and external faults on transmission lines.The research results show that some time-frequency characterization indexes are less affected by the power electronic equipment in the given time window and frequency band，while exhibiting significant differences between internal and external faults.The proposed characterization method can be applied to the study and testing of new relay protection algorithms，providing strong support for the safe and reliable operation of new electric power systems.
Method for fault traveling wavefront calibration based on improved optical voltage transformer
Feng LIU, Yuzhao WU, Xiaobo LI, Tiantian CAI, Junjian CHEN, Ye KUANG, Yuji WANG, Qiaohui ZHANG, Ying ZHANG, and Jiachen ZENG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.004
To address the restricted frequency band of existing electromagnetic potential transformers in transmitting fault traveling wave signals and the susceptibility of fault traveling wavefront calibration to noise interference，a fault traveling wavefront calibration method based on an improved optical voltage transformer is proposed.Firstly，the demodulation and conditioning circuits of the optical voltage transformer are improved to amplify fault traveling wave signals while reducing the influence of birefringence interference signals，thereby enhancing the transmission accuracy of traveling wave signals.Subsequently，the improved complete ensemble empirical mode decomposition with adaptive noise （ICEEMDAN ） is introduced to decompose the transmitted fault traveling wave signals，reducing noise interference in the fault traveling wave signals.Combined with the minimum entropy deconvolution （MED） algorithm，the decomposed fault traveling wave signals are enhanced to sharpen the fault pulse steepness，highlighting the characteristics of the fault traveling wavefront and achieving its calibration.Finally，simulation and experiment are conducted.The results show that the improved optical voltage transformer circuit can transmit signals in the frequency band from 10 kHz to 1 MHz，meeting the requirements for the transmission accuracy of fault traveling wave signals.The proposed method for fault traveling wavefront calibration is not affected by strong noise and can accurately calibrate the traveling wavefront.
Flexible interconnected system location of distribution networks and interconnection power optimization based on power moment
Jindong YANG, Xiran ZHANG, Chaohang REN, and Fei RONG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.005
Flexible interconnection of distribution networks can achieve dynamic capacity expansion of transformers，which is an effective way to improve the power quality of new distribution networks.This paper proposes a method for selecting interconnection points based on the minimum power moment，which comprehensively considers the source load state and its complementary relationship in the distribution network，obtaining the optimal interconnection point in the corresponding state.The location of the optimal interconnection point for the quasi full life cycle is obtained by employing the difference in load rates of interconnection lines during different periods throughout the year as the weight coefficient.Based on the proposed interconnection node，a method for calculating the injection current at the interconnection point with minimum system loss is proposed.Then，by considering line loss，transformer loss，and inverter loss，and taking the minimal total loss of the interconnected system as the objective function，the injection current at the interconnection point is obtained in the condition of satisfying the constraints of interconnection power balance and distribution network capacity，thus obtaining the interconnection power.Finally，the results are applied to practical cases.The study shows that the proposed method achieves a smaller total loss in the interconnection of two actual distribution networks than traditional head end interconnection methods.
Low -voltage distribution network topology identification method based on manifold density peak clustering
Shaokui YAN, Haili DING, Jiayi QIU, Ziwen GU, and Chun HUANG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.006
To address the problem of frequent errors and changes in the topology relationship of low-voltage distribution networks that reduce the accuracy of topology identification，a topology identification method based on manifold density peak clustering is proposed.The method consists of two stages：feature extraction and feature clustering.In the feature extraction stage，a manifold learning algorithm reduces feature redundancy and preserves the arbitrary shape distribution features of voltage data by manifold learning algorithm of extracting low-dimensional embeddings.In the feature clustering stage，based on low-dimensional manifolds of voltage data，the density peak clustering algorithm groups similar low-dimensional manifolds into the same cluster and separates different ones into distinct clusters，achieving topology identification.Experimental results have demonstrated that compared with the original density peak clustering algorithm，the proposed algorithm can identify clustering centers more accurately，improving the accuracy of low-voltage distribution network topology identification.
Static voltage optimization for active distribution networks based on Sobol ’s method
Zifa LIU, Heyang HUAI, Yusen YAO, and Mengni YE
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.007
In active distribution networks，the uncertainty of a large number of distributed energy resources increasingly accentuates voltage stability issues.Existing optimization methods typically treat the economic efficiency and voltage stability of distribution networks independently，seldom considering their interconnection，which hampers the efficient utilization of flexible resources.An interlayer connection factor is introduced，and a bi-layer voltage optimization model for distribution networks based on the Sobol ’s method is proposed.Firstly，a probabilistic load flow calculation model in active distribution networks that considers distributed energy resources in the networks and the load uncertainty is constructed，and the impact of load fluctuations on the L-index is quantitatively analyzed through global sensitivity analysis using the Sobol ’s method.Subsequently，based on the results of the sensitivity analysis，the interlayer connection factors are calculated，and these factors are used to link the upper-layer economic objectives with the lower-level stability objectives to establish a bi-layer optimization model.This model optimizes the flexible resources in the system.Finally， simulations are conducted on a modified IEEE 33-node system using the proposed optimization model.The comparison verifies that the proposed model can improve the optimization efficiency and support the economic and safe operation of distribution networks.
Method of demand forecasting and dynamic equilibrium of computing resources for grid distribution and consumption tasks based on state iteration
Tiantian CAI, Junjian CHEN, Ming HU, Xiaohua LI, and Zexiang CAI
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.008
Distributed objects on the distribution side of the network are currently massively assessed so that the tasks carried by the grid distribution and consumption terminal present the characteristics of multiple time scales and large differences in demand，which leads to the complex equilibrium problem of random fluctuation in the computing resource demand.Traditional terminals are limited by the fixed application scenarios and relatively certain resource allocation，and the terminals can only adapt passively through the “quantity for quality ” method，which is unable to solve the persistent contradiction of imbalance between the supply and demand of computing resources in terminals from the root.Therefore，a method of demand forecasting and dynamic equilibrium of computing resources for grid distribution and consumption tasks based on state iteration is proposed.Firstly，the task computing resource demand model is established based on the analysis of scenario attributes and characteristics of grid distribution and consumption tasks.Secondly，the short-term effectiveness forecasting is predicted by the traditional Markov model.Then，the first-order difference equations of the state are used to train the data and track the state fluctuation.The historical state and the forecasted state are used for state iteration to avoid the convergence of long-term forecasting.Finally，a dynamic equilibrium model is established according to the time-scale features of cyclical and non-cyclical tasks.The optimal configuration of the imbalance in computing resource requirements is achieved by shifting staggered peaks and adjusting differentiation.The results have shown that the improved Markov model based on first-order difference and state iteration has the short-term accuracy of the traditional model and the long-term traceability of data fluctuations.The dynamic equilibrium model can effectively reduce the imbalance of resource demand for computing resources and show good ability to cope with resource imbalance deviation.
Assessment method of smart electricity meter running state based on MFT model
Yuman XIE, Cong TAN, Hongq iao HUANG, Bingxiang LUO, Zhiwei JIA, and Chenhao SUN
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.009
The smart electricity meter，as the terminal device for smart grid marketing，electricity information，and energy distribution，provides strong data support in various aspects such as distribution network operation and maintenance management and customer experience optimization.However，due to the complex and variable operating environment，it is difficult to accurately assess its running state.Therefore，the modified association rules mining （MARM） method is employed，which improves upon two key importance evaluation criteria in the traditional ARM model.This enhancement not only increases the accuracy of state assessment but also improves the ability to identify potential operational risks.Additionally，to reduce uncertainty when dealing with continuous features，the traditional fuzzy inference system （FIS） is enhanced by introducing fuzzy probability （FP） and the tiered fuzzy inference system （TFIS）.Through model integration，a MARM-FP-TFIS （MFT） model that combines strong association rule identification with probability fuzzy inference is developed to solve the health assessment of the running state of smart electricity meters，realizing the evaluation of the running state of the smart energy meter.Finally，case studies verify the feasibility and functionality of the established model in practical applications，thus achieving an accurate assessment of the running state of smart electricity meters under multidime nsional data conditions.
Monitoring algorithm of non -intrusive industrial loads based on improved GAF -inception network
Hui LI, Jiajie GAO, Rongjun XI, Siying CHEN, Yiqun HUANG, and Zefan SHEN
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.010
In view of the existing problems of low recognition accuracy and weak generalization ability in non-intrusive load monitoring using low-frequency industrial data，a non-intrusive industrial load monitoring algorithm based on the combination of Gramian angular field （GAF） and an improved Inception network structure is proposed.The one-dimensional time series information of power is converted into two-dimensional data with temporal characteristics based on GAF.An improved Inception network is constructed，which leverages its sparse connection characteristics to perform multi-scale extraction of multi-parameter load characteristics，thereby reducing model complexity，improving computational efficiency，and achieving high-accuracy identification of industrial loads across multiple scenarios.Finally，the proposed algorithm is validated using the industrial appliance identification dataset （IAID）.The research results show that the proposed algorithm can effectively improve monitoring accuracy up to 94.48% and enhance computational efficiency by more than 8% compared to the existing Inception network.
Research on optimization of electric vehicle charging scheduling in rainy season based on peak valley difference electricity price model
Zhikun LUO, Wenhao YE, Yaohong CHEN, Qin YAN, Shusheng WU, and Jinxin WANG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.011
To address the issues of increased energy consumption of electric vehicles，grid load，and peak valley difference caused by high humidity and temperature in the rainy season in Southern China，a charging price model based on peak valley difference is proposed to stimulate electric vehicles to participate in demand response，so as to stabilize the peak valley difference of grid load and improve the economic benefits of electric vehicle users.Firstly，the Monte Carlo simulation is used to analyze and predict the disordered charging load of electric vehicles，considering factors such as high temperature and humidity during the rainy season in Southern China.Then，a peak-valley differential charging price model is built to minimize the peak valley difference of the power grid and the user charging cost.Lastly，simulation analysis is conducted on the model using the MATLAB application.The research shows that the proposed model considering the high humidity and temperature of the rainy season in Southern China is more accurate.The model can reduce the peak valley difference rate，improve the economic benefits of users，and realize the smoothing and optimization of grid load.The research provides a reference for a new electric vehicle charging scheduling.
Market stochastic delay evolutionary game of multi -agent bidding and its application in electrocarbon coupling market
Shuaibo ZHANG, Fei HE, and Dejing ZONG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.012
As carbon emission trading becomes more and more important to promote the transition to a low-carbon economy in the electric power system，the bidding strategy among new energy producers，fossil energy producers，and community aggregators in the electrocarbon market has changed significantly.In view of the stochastic fluctuations shown by bidding behaviors of different agents in the market and the lagging benefits generated by carbon quotas，a stochastic delay differential equation （SDDE） model is established.Gaussian white noise and time-delay terms are introduced to simulate the dynamic evolution of the bidding process between three different firms，and the change law of the lag time threshold and the influence of the change of interference intensity and lag time on the strategy selection are discussed.Based on the supply and demand relationship between the three agents，different types of flexible loads are set up and the evolutionary game process between the supply-side time-of-use pricing strategy and the demand-side flexible load strategy in the electrocarbon market is simulated by SDDE，which proves the influence on the interests of each agent in the process of achieving Nash equilibrium and the effectiveness of peak cutting and valley filling.
Clean energy and energy storage
Forecasting model of wind -photovoltaic synergy power based on mutual information coupling DBO -BiLSTM -Attention
Yinghuan LI, Ji cheng LIU, Yunyuan LU, and Jiakang SUN
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.013
Wind-photovoltaic synergy power is the trend in the development of new electric power systems.However，both electricity generation fluctuates greatly with the environment，which exerts an impact on the forecasting accuracy for the whole system power.This paper explores an innovative model to analyze and forecast the wind-photovoltaic synergy power for the purpose of a more accurate forecasting result.Firstly，the structure of the wind-photovoltaic synergy power system and the synergy power model of wind power and photovoltaic power are analyzed.Secondly，the relationship between the influence factors of wind power and photovoltaic power is discussed using the mutual information coupling method.Thirdly，the DBO-BiLSTM-Attention model is constructed to lay the foundation for forecasting the wind-photovoltaic synergy power.Finally，the scenario analysis，method comparison analysis，and the sensitivity analysis are conducted to verify the effectiveness and rationality of the proposed model.The results show that the proposed model has good performance and can provide a valuable reference for forecasting wind-photovoltaic synergy power effectively and accurately.
Research on photovoltaic power forecasting method based on time series large model TimeGPT
Wenyu SHI, Zhenyi ZHANG, and Dechang YANG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.014
Currently，various statistical and machine models have been widely applied to photovoltaic （PV） power forecasting，but low forecasting accuracy is common with scarce PV historical data.Therefore，a time generative pre-trained transformer （TimeGPT ） is introduced into the short-term forecasting of PV power.Firstly，a time series large model is constructed based on a large-scale and diverse time series dataset of 100 billion data points （such as finance，traffic，banking，network traffic，weather， energy，and healthcare ）.Then，TimeGPT is fine-tuned using a small amount of PV power historical data to adapt to the data distribution and characteristics related to PV power forecasting.TimeGPT is simulated in the PV dataset with user privacy and compared with existing statistical and machine models.By taking case 1 as an example，the mean absolute error （MAE） of TimeGPT is reduced compared with the comparison models when the forecasting step is 1 h.Finally，the conditions for TimeGPT application and the direction of improvement are summarized for its application in new electric power systems.
Method for generating medium and long -term photovoltaic output scenarios based on generative adversarial networks
Tingji GUAN, Pingping LUO, Jikeng LIN, and Chaoli ZHANG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.015
A new method for generating medium and long-term photovoltaic output scenarios based on generative adversarial networks is proposed to address the problem of high variable dimensions in generating annual photovoltaic output sequence scenarios.Firstly，the fuzzy C-means clustering （FCM） algorithm is used to divide daily meteorological states，and the temporal nature of daily meteorological information is simulated based on generative adversarial networks.Then，a state division network is introduced，and a state generative adversarial network is constructed to simulate the distribution pattern of meteorological states during the week.Photovoltaic output sequence scenarios are generated by layering from weekly and daily scales.Finally，historical meteorological and photovoltaic output data from a photovoltaic power station in China are used to verify the effectiveness and accuracy of the proposed method.
Scheduling method for carrying capacit y enhancement of new energy based on nuclear storage coordination under peak s having–frequency regulation constraints
Tao TIAN, Ming HUANG, S enwei CHANG, Changpeng LIN, Minhui XUE, and Yi LIU
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.016
With the increasing proportion of renewable energy，the pressure on peak shaving and frequency regulation in power systems is gradually intensifying，and existing scheduling methods cannot consider both system security and new energy consumption.This paper proposes a scheduling method for carrying capacity enhancement of new energy based on the coordination between nuclear power and energy storage.Firstly，by analyzing the spatiotemporal complementary characteristics of nuclear power units and energy storage devices，the coordinated role of both in peak shaving and frequency regulation is fully explored to build a scheduling model for nuclear storage coordination.Then，a collaborative transmission and distribution scheduling framework is constructed to develop reasonable day-ahead optimization strategies by decoupling the scheduling requirements of transmission grids and distribution networks，and improve the carrying capacity of new energy in power systems.Additionally，frequency security constraints are introduced to analyze their influence on power syste m stability and renewable energy consumption.Finally，case analysis is conducted to validate the effectiveness and practicality of the proposed method.The results show the proposed method has significant advantages in reducing the total costs of systems，enhancing renewable energy consumption，and improving frequency regulation.As a result，theoretical support can be provided for nuclear power units to deeply participate in peak shaving and frequency regulation of power grids.
Optimization of hydrogen production efficiency in wind -solar grid -connected system considering voltage impact at grid connection point of electrolytic cell
Kankai SHEN, Bingqin g XIA, Heng NIAN, Jianyong ZHAO, and Leilei CHEN
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.017
Optimization of hydrogen production power，electrolytic cell model，and voltage fluctuation at the grid connection point of the electrolytic cell can enhance the efficiency of hydrogen production in the system and increase the hydrogen yield and profits.The voltage variability at the grid connection point of the electrolytic cell results in changes in the reactive power demand of the electrolytic cell，which affects electrolytic current and diminishes hydrogen production efficiency.An energy management optimization strategy considering the voltage impact at the grid connection point of the electrolytic cell is introduced.First，a model of the reactive power demand of the electrolytic cell and its impact on hydrogen production efficiency is established.Then，system hydrogen production efficiency is optimized by comprehensively considering objectives such as hydrogen production and line losses，and the reactive power outputs of photovoltaics，wind power，and the power grid are coordinated.Finally，the effectiveness of the proposed management strategy is verified through examples.The research results demonstrate that the proposed energy management strategy can enhance hydrogen production by 7.51%，mitigate voltage fluctuations at the grid connection point of the electrolytic cell，and significantly improve the hydrogen production efficiency of the electrolytic cell，while ensuring electrolytic cell consumption and full consumption of power generation with an increase in line loss.
Anomaly warning of gearbox oil temperature in wind turbine generator system based on iForest -DBSCAN -RF and optimized CATBoost
Liangyu MA, Likai HAN, and Liangliang ZHAI
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.018
Data cleaning，feature selection，and the estab lishment of a prediction model are indispensable steps to realize anomaly warning of the wind turbine generator system based on data collection and supervisory control and data acquisition （SCADA）.Firstly，isolated forest （iForest） and density-based spatial clustering of applications with noise （DBSCAN ） algorithm are combined to effectively clean the data outliers of SCADA，and random forest （RF） and Pearson correlation coefficient method are used to optimize the input parameters of the model.Based on the categorical boosting （CATBoost ） algorithm optimized by Optuna，a prediction model of gearbox oil pool temperature in the wind turbine generator system under normal operating conditions is established.Then，the state evaluation index is constructed with the sliding window method，and the interval estimation theory is employed to determine its critical threshold for anomaly discrimination of oil temperature.Finally，the anomaly warning of oil temperature is realized.The real historical fault data of oil temperature anomaly in the SCADA system of the wind turbine generator system are used to verify the effectiveness of the method.
Microgrid and integrated energy
Optimal scheduling of integrated energy system considering dynamic energy pricing mechanism
Xin SUN, Keying XIANG, and Jingdong XIE
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.019
To better promote the interaction between supply and demand sides，stimulate the potential for demand side response，and fully consider the complex response characteristics of demand side users，a dual-layer optimization model based on a dynamic energy pricing mechanism is proposed.Firstly，the interaction behavior between multiple entities on both sides of supply and demand is considered，and a user dissatisfaction conversion coefficient is introduced.A dynamic energy pricing mechanism that takes into account the factors of user dissatisfaction is established to provide upper-layer dynamic energy prices for a comprehensive dual-layer optimization model.Then，based on the dissatisfaction factors affecting dynamic energy prices，the user dissatisfaction cost is optimized in the lower-layer model to achieve dynamic optimization and regulation of the integrated energy system.Simulation results verify that the proposed optimization model can fully tap into the potential of demand side regulation，and it is effective in promoting the consumption of renewable energy，improving economic efficiency，and meeting user demand satisfaction.
Low -carbon optimization of regional integrated energy systems considering flexible and coordinated source -load response and refined utilization of hydrogen energy
Yan ZHANG and Xiaohui YANG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.020
Building an efficient and low-carbon integrated energy system is an important way to achieve the carbon peak and carbon neutrality goals.Therefore，a regional integrated energy system （RIES） considering flexible and coordinated source-load response，and refined utilization of hydrogen energy is proposed.Firstly，a refined utilization model of hydrogen energy，including wind power hydrogen production，hydrogen fuel cells，hydrogen energy storage，and methane devices，is introduced on the source side，and the heat loss during operation is considered to construct an electricity-heat-gas-hydrogen efficient coupling model.Secondly，a waste heat power generation unit with an organic rankine cycle （ORC） is introduced on the source side to decouple the constraint of heat to electricity in cogeneration，and the demand response is supplemented on the load side to form a flexible and coordinated source-load response model.Finally，to address the impact of uncertainty in wind and photovoltaic power on system operation，a RIES low-carbon economic optimization model considering the conditional risk value theory is established，by comprehensively considering the costs of tiered carbon trading，equipment operation and maintenance，wind abandonment，and energy procurement.The proposed model is solved using the Gurobi solver.The research results show that the proposed model can effectively improve the level of new energy consumption，reduce the carbon emissions of systems，and improve energy utilization efficiency.
Power electronics
Robust control of output voltage of DAB converter by super -twisted sliding mode method
Jianlin LI, Laixin GUO, and Penghui HAN
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.021
The traditional sliding mode control （SMC） used for the isolated dual active bridge （DAB） converter is robust and can improve the dynamic performance of nonlinear systems.To address the disadvantages of buffeting and decreasing tracking performance，a super-twisted sliding mode control （ST-SMC） method is proposed to enhance the output voltage regulation ability and robust control ability of the converter.The ST-SMC method is adopted，and the technical advantages of the sliding mode controller are combined to effectively eliminate the buffeting problem.During the design of the sliding mode controller，the average mathematical model of the DAB converter under single-phase shift control is fully considered，and the design process is effectively simplified.The stability and robustness of the direct current （DC） output voltage of the DAB converter are improved effectively，and accurate reference voltage tracking is realized.In addition，the method provides robust control over parametric uncertainties，and the steady-state output voltage of the DC converter contains fewer ripple components than traditional SMC and PI controllers.Finally，based on the TMS 320F28335 digital controller，a 1kW DAB converter prototype is installed to verify the effectiveness of this new control method.
Research on resonance mechanism and suppression method of HERIC soft -switching inverter
Yu HAN, Qian LI, Yingjie WANG, Bolin YAN, Li JIANG, and Yao SUN
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.022
To improve the operational efficiency of the highly efficient and reliable inverter concept （HERIC），auxiliary branches are often introduced to achieve zero voltage switching （ZVS） of the power switches.However，when the auxiliary branches realize soft switching，the parasitic capacitance of the auxiliary switch resonates with the auxiliary inductance，which aggravates the voltage stress on the auxiliary switch and affects the safe operation of the circuit.To address this issue，a clamping technique is proposed to mitigate the additional voltage stress caused by resonance.First，the resonance mechanism of the inverter is analyzed，and the potential difference between the auxiliary branch and the direct current （DC） bus is calculated under non-resonant conditions.Then，based on this potential difference，a transient voltage suppressor （TVS） is selected，and anti-series diodes are used to form a clamping branch.When the TVS is reverse-broken down by a large resonance voltage，the auxiliary branch voltage is clamped by the bus voltage to achieve resonance suppression.Additionally，this branch serves a suppressive role only during the resonance occurrence，without affecting the normal operation of the circuit.Finally，experimental results show that the clamping branch can effectively suppress the resonance voltage，with the peak resonance voltage of the auxiliary branch under full load being reduced by 49.4 % compared to that without the branch.
Wideband oscillation suppression strategy of direct -drive wind farms based on coordination between impedance sensitivity and additional control
Xintong YU, Jiahui WU, Bo WANG, and Rui WANG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.023
Wideband oscillations caused by the integration of direct-drive wind farms into weak alternating current （AC） power grids seriously affect the safe and stable operation of power grids.To this end，a control strategy based on coordinated impedance sensitivity and the adjustment of additional controller parameters is proposed.Firstly，a sequence impedance model of direct-drive wind farms with different control methods is built.Meanwhile，the impedance sensitivity method is employed to analyze the influence of various control parameters on system stability and identify the dominant turbine groups that affect the grid-connected oscillation characteristics.Additionally，combined with the current spectrum analysis on the feeder of the dominant turbine group，a design strategy for the control parameters in the additional controller of the static synchronous compensator （STATCOM ） is proposed.Finally，a simulation model is built on the MATLAB/Simulink platform for verification.The results show that the additional control strategy can effectively suppress the wideband oscillation phenomenon and improve the stability of the power grid system.
Feedforward strategy of adaptive improvement for grid -connected inverter with extremely weak grid
Tieying ZHAO, Peijian TIAN, Junran LI, Zhiyuan HUANG, and Yuang QI
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.024
With an extremely weak grid，grid-connected inverters introduce the grid voltage proportional feedforward control strategy to enhance the amplitude gain in the low-frequency band and suppress the background harmonic interference of the grid.However，when the impedance parameter of the grid increases，the phase margin of the system significantly decreases，and instability occurs.Based on the impedance characteristic analysis method，the internal mechanism of the deterioration of the system ’s phase margin is first revealed，and then proposes to connect a second-order low-pass filter on the feedforward channel in series to improve the system ’s phase margin and retain its gain effect at low frequencies as much as possible.However，since the parameters of the added controller are too complex and not flexible enough by using the traditional parameter design method，an adaptive parameter design method combining online impedance detection technology and a genetic optimization algorithm is proposed to improve the parameter design efficiency and thereby enhance the robustness of grid-connected inverters in extremely weak grid environments.Finally，its effectiveness is verified through simulation and experimental results.
Research on transient voltage stability in distribution networks based on new hybrid transformer
Zhiwei CHEN, Jie WANG, NG Nianwen XIA, Jie WU, Haitao YANG, Lijian DING, Weiguo LI, and Chong LIU
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.025
The proportion of voltage sag faults in the voltage quality problem is more than 80%，which seriously threatens the safety，economy，and efficiency of electricity consumption.To solve this problem，a voltage quality control system of distribution networks for hybrid transformers is proposed.By hybrid transformers and the integration of photovoltaic units and energy storage units，three operational modes are built，including grid-connected inverter mode，islanding inverter mode，and grid-connected rectifier mode.The grid-connected power supply of photovoltaic units，compensation of voltage sag of energy storage units，and charging function of energy storage units by distribution networks are realized，respectively.Then，the functions of the system are verified by simulations. Finally，a hardware prototype test platform is built，where the rated power of the system is 1 kW.A voltage regulator is used to simulate a unidirectional grid voltage of 220 V，with a load voltage of 110 V，and a tapped transformer with a turn ratio of 10：5：4，for further verification.The research results show that the proposed system is capable of effectively mitigating voltage quality problems in distribution networks across the three operating conditions.
High voltage and insulation
A quantification method of moisture degree of oil -paper insulation based on Stacking heterogeneous integration
Menghong FANG, Yang ZOU, Xiaoxuan CHEN, Yu HUANG, and Tao JIN
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.026
To address the issues of the limitations of the current transformer oil-paper insulation system moisture assessment model selection and the low directivity of the feature indexes for insulation moisture assessment under the synergistic effect of aging and moisture，a quantification method of the moisture degree of oil-paper insulation based on Stacking heterogeneous integration is proposed.Firstly，the mechanism analysis is conducted about the change trend of the macro insulation state under the synergistic effect of aging and moisture synergism at the micro-medium level，and multi-source heterogeneous moisture feature indexes that can eliminate the interference of aging are extracted，forming a highly correlated feature set with moisture.Secondly，based on four types of heterogeneous algorithms that are integrated based on the fusion learning idea of Stacking，the primary assessment system of the overall model is constructed，and output noise is reduced through the Optuna hyper-parameter tuning framework.Finally，the stack data after weight assignment is utilized to train the sub-assessment system，and then a weighted and improved Stacking model is built to quantify the moisture degree of the oil-paper insulation system.Lastly，the effectiveness of the proposed model is validated in moisture assessment by taking the measured data as an example.The model can serve as a reference for assessing moisture in transformer oil-paper insulation systems.
Research on effect of low -voltage photovoltaic power flow reversal on cable life expectancy
Yan LI, Wenqian ZHAO, Yunpeng LIU, Yongcai TIAN, Xiangrui ZENG, Xiaojun LIU, and Yubo WANG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.027
With the increase in the penetration rate of distributed photovoltaic power，the power flow may be sent back to the grid side，posing new aging challenges to low-voltage （LV） photovoltaic cables.In view of the insufficient research on cable aging under the photovoltaic power flow reversal，a cable life estimation method for the LV photovoltaic power flow reversal scenario is proposed.Firstly，based on Kirchhoff ’s current law，the current distribution of the cable under different gradients is calculated，and the temperature field of the cable is analyzed using finite element simulation software.Secondly，the Arrhenius lifetime model is used to evaluate the expected lifetime，aging rate，and lifetime loss of the cable under different operating conditions.Finally，uncertainty analysis of the temperature and lifetime of the cable is conducted through a Monte Carlo simulation.The research results show that in the scenario of photovoltaic power flow reversal，the average insulation temperature of the cable is generally higher than the normal operating temperature，and there is a 52.93% probability that it will be higher than the rated working temperature of 80 ℃.The cable lifetime is generally lower than the normal operating temperature，and there is a 53.78% probability that it will be shorter than the lifetime under the rated working temperature.
Shape design of energy leakage hole of explosion -proof high voltage cable joint
Yawen HE, Youcai LI, Qiyan LI, Yongli YU, and Zhisong JIANG
Date posted: 10-22-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.04.028
In view of the lack of optimization method for the s hape design of energy leakage hole of explosion-proof high voltage cable joint，this paper uses the finite element calculation method coupled with temperature field，fluid field，and displacement field to simulate the explosion process inside the joint，and puts forward the design principle of optimizing the shape of the energy leakage hole in the copper shell of explosion-proof cable joint.An optimization method that uses the tangent value of the convergence angle of the ejected airflow from the energy leakage hole as the key parameter is proposed.Through the examples，the airflow velocity at the edge of the three typical energy leakage hole shapes is decomposed into three directional velocity components，and the maximum and average values of the three velocity components are obtained.The trajectory of gas ejection of the energy leakage hole in the copper shell of a 220 kV explosion-proof high voltage cable joint with different opening shapes，is calculated.According to the design method of the shape of the energy leakage hole，it is obtained that when the shape of the energy leakage hole is circular，the gas ejection is the most restrained，and the explosion-proof effect is the best.The design ideas and important parameters according to the optimal design of the energy leakage hole of the explosion-proof high voltage cable joint can provide valuable guidance.
