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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.

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A review of demand response capability assessment based on CPSS perspective
Kairui ZHANG, Hao MING, and Ciwei GAO

Date posted: 4-22-2024
DOI: https://doi.org/10.19781/j.issn.1673-9140.2024.01.003

The combination of cyber-physical-social systems and demand response assessment is reviewed. First, the history and framework of cyber-physical systems are analyzed. Then, summaries are provided for the existing research on demand response, including the significance, classification, and evaluation methods of demand response potential assessment, as well as the data sources for demand response capability assessment, including questionnaire surveys and operational data collection. In terms of the combination of cyber-physical-social systems and demand response, the physical domain, information domain and social domain foundation of demand response are analyzed respectively, and the corresponding modeling methods and research contents are introduced. Finally, prospects are provided for market assessment mechanisms, rapid simulation and modeling technologies, and demand response management under integrated energy systems.

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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.

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Summary of research on electricity theft behavior detection methods
Yu XIAO, Zhi YE, Rui HUANG, Mouhai LIU, Rui XIA, and Yunpeng GAO

Date posted: 11-6-2023
DOI: https://doi.org/10.19781/j.issn.1673-9140.2023.04.001

The non‑technical losses caused by electricity theft in the power system have always been a pressing issue for power grid companies to urgently address. With the deployment of a large number of smart meters in the power grid, the use of user‑side data collected by the power metering automation system to accurately detect electricity theft has attracted widespread attention from researchers and power grid companies. Firstly, the basic classification of users' electricity stealing behavior, evaluation indicators and existing electricity theft detection data sets are introduced. Then, from the four aspects of grid state analysis, machine learning, game theory and hardware, the existing detection methods of electricity theft behavior are comprehensively sorted, analyzed and compared, and the basic ideas, advantages and disadvantages of each method are summarized. Finally, the current challenges in the field of electricity theft behavior detection are deeply analyzed, and a prospective outlook on the focus of future research work is provided.

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Resilience enhancement strategy for distribution network considering coordination of intelligent soft open points and multiple emergency resources
Zifa LIU and Wenbo XUE

Date posted: 7-23-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.03.001

In view of the significant impact of extreme events on power system security, enhancing grid resilience has become a research hotspot. Therefore, a pre-event prevention and post-event coordinated recovery strategy considering intelligent soft open points (SOPs) and multiple emergency resources is proposed to improve the resilience of the distribution system. In the pre-event stage, to effectively reduce post-event resource scheduling time, a robust optimization model considering the uncertainty of power output is constructed based on predicted fault scenarios. A column-and-constraint generation algorithm is used to obtain pre-event deployment decisions. In the post-event stage, to minimize the curtailed load power through dynamic scheduling, a coordinated recovery strategy using intelligent SOPs and multiple emergency resources is developed, combined with pre-event deployment decisions and traffic network conditions. To address the computational complexity of the multi-source recovery model, an auxiliary induction objective function acceleration algorithm is designed to speed up the solution. Finally, the effectiveness of the proposed strategy in improving the distribution network resilience is verified using an improved IEEE 33-node distribution system case study.

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Power system and comprehensive energy knowledge graph based on Neo4j graph database
Xiaolong REN, Xi CHEN, Hengbin SI, and Shuang TIAN

Date posted: 7-23-2025
DOI: https://doi.org/10.19781/j.issn.1673-9140.2025.03.023

At present, the scale of the power grid is expanding, and the amount of knowledge in power systems is increasing explosively. In order to organize, manage, and utilize mass knowledge effectively, knowledge graph technology is introduced into the field of power systems and comprehensive energy systems. Common relational databases of Oracle and structured query language (SQL) need to use tables to store data and query and analyze data through complex relationships, which is more complicated when dealing with complex relationships. The Neo4j graph database represents data as nodes and edges, which makes the correlation between entities and relationships intuitively expressed and stored, and it is especially suitable for application scenarios that need to deal with complex relationships and conduct graph analysis. Therefore, a research method for power system and comprehensive energy system knowledge graph based on the Neo4j graph database is proposed. By introducing knowledge graph technology into the power system and comprehensive energy, the power knowledge is stored in an orderly manner by using the Neo4j graph database. Then, a knowledge graph of the power field is built, and a search engine with a B/S framework is designed, realizing the interactive function between users and knowledge graph through front-end coding and handling the data related to knowledge graph through back-end coding, including data storage, query, update, and other operations. The test results show that this method can effectively improve the search efficiency of knowledge graphs of power systems and comprehensive energy systems and enhance the retrieval speed of massive data.

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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.

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Research review on microgrid of integrated photovoltaic‑energy storage‑charging station
Qin YAN and Guoxiang YU

Date posted: 4-22-2024
DOI: https://doi.org/10.19781/j.issn.1673-9140.2024.01.001

To address the challenges posed by the large-scale integration of electric vehicles and new energy sources on the stability of power system operations and the efficient utilization of new energy, the integrated photovoltaic-energy storage-charging model emerges. The synergistic interaction mechanisms and optimized control strategies among its individual units have also become key issues urgently needing resolution in smart grid development. Due to the characteristics of integrated generation, load, and storage, mutual complementarity of supply and demand, and flexible dispatch, the photovoltaic-energy storage-charging (PV-ESS-EV) integrated station micro-grid (ISM) mode, incorporating "PV- PV-ESS-EV + intelligent building" features, has become a focal point for energy conservation, carbon reduction, and energy transition in China. In consideration of the challenges faced by the operational mode of microgrids, such as the strong uncertainty of distributed energy sources and the unclear interaction mechanisms during islanded and grid-connected operation, various aspects of the PV-ESS-EV ISM are reviewed, including its unit modules, key technologies, and operational states. Additionally, the current research status of PV-ESS-EV is summarized while future development trends are discussed, and the challenges that need to be addressed are examined. The research findings have important theoretical and practical implications for exploring the regulatory potential of various demand-response resources under economic incentives, ensuring the reliability of power grid supply, and serving as valuable references for both theory and practice.

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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.

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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.