CSEE Journal of Power and Energy Systems

18/11/2025

https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=11202683&punumber=7054730

REGULAR PAPERS

2. Coordinated Low-carbon Optimal Dispatching on Source-demand Side for Integrated Electricity-gas System

C. Y. Li, Z. C. Yan, Y. M. Yao, Z. W. Tang, and C. Z. Shao

DOI: 10.17775/CSEEJPES.2021.08790



3. Energy Management of Integrated Electric-gas Prosumers with Peer-to-Peer Trading: A GNE Approach

C. Wang, Q. Y. Jia, and Y. L. Liang

DOI: 10.17775/CSEEJPES.2021.09390



4. Segmented Forecasting of Electric Load Under Pandemic Period Based on the ESD-ABiLSTMQR Method

Y. Lei, L. X. Yu, J. F. Zhao, S. C. Ding, X. X. Guo, and H. B. Bao

DOI: 10.17775/CSEEJPES.2022.08020



5. Electromechanical Joint Analysis for Switching Procedure of Vacuum On-load Tap Changer in UHV Converter Transformer

L. He, J. G. Bi, D. W. Ding, Y. F. Chen, Y. Xu, Y. P. Gong, and W. D. Liu

DOI: 10.17775/CSEEJPES.2023.09080



6. Mechanism of Eddy Current-induced Electromagnetic Force and Vibration Noise of Large-capacity Transformer Oil Tanks

H. N. Yang, Z. Y. Ji, J. Wen, H. X. Cong, and Q. M. Li

DOI: 10.17775/CSEEJPES.2023.01330



7. Simple-structured Control for Supercapacitor DC-DC Converters for Grid-connected Applications

X. J. Quan, X. F. Xie, Q. R. Hu, J. X. Lei, X. B. Dou, Z. J. Wu, T. K. Sun, and K. Hou

DOI: 10.17775/CSEEJPES.2021.08480



8. High-power Density Capacitive Coupler for Power Transfer System in Miniaturized Rotary Application

Y. Wu, Q. H. Chen, J. A. Yin, X. Y. Ren, and Z. L. Zhang

DOI: 10.17775/CSEEJPES.2021.08330



9. Reliability Evaluation and Sensitivity Analysis for UHVDC-HC Considering Preventive Maintenance and Inverter Capacity Levels

S. H. Li, H. J. Zhao, D. W. Tao, H. M. Zhou, and L. L. Li

DOI: 10.17775/CSEEJPES.2021.07820



10. Adsorbent Exploration of CaSO4 for C4F7N/N2 -based Insulation Devices from Experimental and Theoretical Insights

S. Xiao, F. R. Wang, H. Cui, Y. L. Xia, J. Y. Chen, S. J. Xie, and J. Tang

DOI: 10.17775/CSEEJPES.2021.07240

All CSEE JPES articles are OA published on IEEE Xplore.

16/11/2025

https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=11202683&punumber=7054730
REGULAR PAPERS
30. Decoupling Design Method for DC Virtual Inertia and Voltage Loop Stability Margin
J. T. Lei, R. J. Zhang, X. Xiang, C. S. Li, C. M. Li, W. H. Li, and X. N. He
DOI: 10.17775/CSEEJPES.2021.08240

31. Second-order Extended State-space Model of Switching Converters
R. J. Huang, F. Ma, G. Wang, and R. L. Xiao
DOI: 10.17775/CSEEJPES.2021.07070

32. Optimized Design in Current, Temperature and Stress Distributions for Paralleled Chips in Press-pack IGBT Modules
L. B. Han, L. Liang, and Y. Kang
DOI: 10.17775/CSEEJPES.2021.06360

33. Compound Line-commutated Converter with Commutation Voltage Compensation and Power Consumption Capability for Commutation Failure Suppression
C. Y. Guo, Z. G. Hai, C. Y. Zhao, and C. R. Liu
DOI: 10.17775/CSEEJPES.2021.06790

34. Design-oriented Analysis and Enhancement of Transient Power Sharing Between Inverter-interfaced Generators and Synchronous Generators
Y. L. Peng, Z. K. Shuai, W. Huang, and X. Shen
DOI: 10.17775/CSEEJPES.2021.07360

35. Output-constrained Distributed Cooperative Control Based on Dynamic Event-triggered Average Consensus for DC Microgrid Clusters
Z. K. Xie and Z. Q. Wu
DOI: 10.17775/CSEEJPES.2021.08260

36. Multi-energy Supplying Strategies in Coupled Electricity-heat-gas Markets
C. Y. Wu, W. Gu, E. B. Luo, H. Lu, Z. K. Yi, X. D. Yuan, and J. T. Zhao
DOI: 10.17775/CSEEJPES.2021.09470

37. Decentralized Optimization of Multi-area Power-transportation Coupled Systems Based on Variational Inequalities
S. W. Xie, Z. D. Chen, Y. C. Zhang, S. Cao, and K. Y. Chen
DOI: 10.17775/CSEEJPES.2022.05760

38. Pricing Strategy for Regional Integrated Energy System Considering Privacy Based on Deep Reinforcement Learning
X. Wu, B. W. Liu, S. Q. Yuan, B. R. Cao, Z. Y. Zhang, and Y. H. Hu
DOI: 10.17775/CSEEJPES.2021.08300

39. Dynamic Energy Dispatch Strategy for Integrated Energy System Based on Constrained Reinforcement Learning
Q. K. Sun, X. J. Wang, Z. Liu, W. S. Lin, J. H. He, and W. Pei
DOI: 10.17775/CSEEJPES.2021.08770

40. Hierarchical Robust Expansion Co-planning Model for Multi-energy Distribution Systems Considering Reconfiguration
T. J. Li, X. Q. Han, D. X. Zhang, and Z. H. Yin
DOI: 10.17775/CSEEJPES.2022.02350

14/11/2025

https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=11202683&punumber=7054730

REGULAR PAPERS

2. Graph Computing Based Knowledge Reasoning in Electric Power System Considering Knowledge Graph Sparsity

T. J. Pu, Y. P. Tan, Z. Y. Ma, and J. N. Xu

DOI: 10.17775/CSEEJPES.2022.04120



3. Virtual P2P Transaction Integrated Expansion Planning for Distribution Networks

J. K. Dai, Y. Xiang, and Y. T. Guo

DOI: 10.17775/CSEEJPES.2021.08980



4. Double-machine Equivalent Method for Evaluating Plant- and Unit-level Stability of Hybrid Grid-connected Renewable Power Plants

Z. X. Guo, X. Zhang, F. Li, X. X. Fu, F. Han, and J. L. Wang

DOI: 10.17775/CSEEJPES.2021.08940



5. Risk-averse Optimal Scheduling of Regional Electricity-heating Integrated Energy System Considering Interface with Microgrids

H. H. Chen, D. Wang, C. Q. Lin, R. F. Zhang, T. Jiang, and X. Li

DOI: 10.17775/CSEEJPES.2021.07120



6. Grounding Faults in Series-connected-based Offshore Wind Farms: DC Link Current Control

G. P. Guo, K. P. Zha, Y. F. Yang, F. Zhang, J. X. Wang, and W. K. Xie

DOI: 10.17775/CSEEJPES.2021.08190



7. Low Frequency Residential Load Disaggregation via Improved Variational Auto-encoder and Siamese Network

C. Qian, Z. J. Wu, D. L. Xu, Q. R. Hu, and Y. Liu

DOI: 10.17775/CSEEJPES.2022.00930



8. Faulty-feeder Detection Based on Sparse Waveform Encoding and Simple Convolutional Neural Network with Multi-scale Filters and One Layer of Convolution

J. W. Yuan, T. Wu, and Z. B. Jiao

DOI: 10.17775/CSEEJPES.2021.09140



9. Dual Clustering Detection Model of Power Theft Based on User Behavior Analysis

D. D. Zhang, F. Jiang, H. H. Goh, T. H. Liu, H. Liu, and T. Wu

DOI: 10.17775/CSEEJPES.2021.08430



10. Data-driven Approach for Electromagnetic Transient Recognition Using Transfer Learning

H. Zhang, W. X. Sima, and M. Yang

DOI: 10.17775/CSEEJPES.2021.05660



11. Steady-state-component-based Current Differential Protection for Petal-shaped Distribution Network with Inverter-interfaced Distributed Generators

X. L. Chen, S. Yuan, Z. Q. Li, J. B. Ren, and S. B. Geng

DOI: 10.17775/CSEEJPES.2021.06100

https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=11202683&punumber=7054730

13/11/2025

https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=11202683&punumber=7054730

REGULAR PAPERS

1. Simulation of Electromagnetic Fields Emitted from GIS Bushing Due to Disconnectors Switching Operation in 1000 kV Substations

J. Zhao, W. J. Chen, J. G. Zhang, Y. Xia, W. He, and K. J. Li

DOI: 10.17775/CSEEJPES.2025.01260



2. Coordinated Operation of Active Distribution Network, Networked Microgrids, and Electric Vehicles: A Multi-agent PPO Optimization Method

W. L. Shi, D. X. Zhang, X. Han, X. Y. Wang, T. J. Pu, and W. Chen

DOI: 10.17775/CSEEJPES.2022.05640



3. Frequency-domain Equivalent Model of District Cooling Systems for Primary Frequency Regulation

P. P. Yu, H. C. Zhang, and Y. H. Song

DOI: 10.17775/CSEEJPES.2023.02350



4. Impedance-based Islanding Detection for DC Microgrid with Multiple Distributed Generators

H. Y. Chen, T. L. Shi, Q. H. Huang, X. Xiang, C. S. Li, W. H. Li, and X. N. He

DOI: 10.17775/CSEEJPES.2022.00020



5. Bi-level Hybrid Stochastic/Robust Optimization for Low-carbon Virtual Power Plant Dispatch X. Wei, Y. L. Xu, H. B. Sun, and H. T. Zhao

DOI: 10.17775/CSEEJPES.2021.07140



6. Ultra-short-term Photovoltaic Power Prediction Based on Improved Temporal Convolutional Network and Feature Modeling

H. Xiao, W. T. Zheng, H. Zhou, and W. Pei

DOI: 10.17775/CSEEJPES.2023.06130



7. Security Constrained Stochastic Unit Commitment Considering Fast Correction Control of Battery Storage and VSC

Z. L. Zeng, Y. Tan, Y. J. Cao, Y. Li, and P. Q. Li

DOI: 10.17775/CSEEJPES.2021.08390



8. Time-varying Tracking Algorithm for Active Distribution Grid Energy Management Considering Uncertainty of Feeder Parameters

J. X. Wu, M. B. Liu, W. T. Lu, K. J. Xie, and M. Xie

DOI: 10.17775/CSEEJPES.2021.09160



9. Optimal Configuration of Off-grid Hybrid Renewable Energy System with PV/Wind/Hydrogen/Cooling

L. J. Ge, J. H. Liu, Z. G. Wang, and M. U. Rafiq

DOI: 10.17775/CSEEJPES.2021.07430



10. Real-time Economic Dispatch Considering Voltage-sensitive Loads

F. Li, H. Y. Jin, T. Niu, L. Xue, T. E. Huang, and L. X. Tian

DOI: 10.17775/CSEEJPES.2021.06040

https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=11202683&punumber=7054730

All CSEE JPES articles are OA published on IEEE Xplore.

03/11/2025

This paper, published in the CSEE Journal of Power and Energy Systems, presents a cutting-edge scheduling framework that utilizes the flexibility of thermostatically controlled loads (TCLs) to enhance renewable energy integration within a virtual power plant (VPP) environment. The research team proposes a two-stage, multi-time-scale control strategy where TCLs function as virtual generators on the hour-level and as virtual batteries on the minute-level, addressing forecast errors in renewable energy output across different time scales. To account for user preferences, a transactive energy market is designed to guide TCL behavior via price signals. Furthermore, a distributionally robust optimization method, based on the Wasserstein metric, is incorporated to handle uncertainty in renewable forecasts. By transforming the problem into a mixed-integer linear program using affine decision rules and duality theory, the approach remains computationally efficient. Comparative simulations validate that this method outperforms conventional robust and stochastic strategies, demonstrating superior performance in managing variability in VPP operations through comprehensive TCL coordination.



Coauthored by Meng Song; Xiaoyuan Xu; Ciwei Gao; Zheng Yan; Mohammad Shahidehpour from Southeast University, Nanjing, China, Shanghai Jiao Tong University, Shanghai, China and Illinois Institute of Technology, Chicago, USA.



You can check on the whole article on IEEE Xplore by:

https://ieeexplore.ieee.org/document/10165671

All CSEE JPES articles are OA published on IEEE Xplore.

Thermostatically controlled loads (TCLs) have huge thermal inertia and are promising resources to promote consumption of renewable energy sources (RESs) for car

01/11/2025

This paper investigates the subsynchronous oscillation (SSO) phenomena in direct drive wind farms connected to weak AC grids, introducing a novel analysis method based on the complex torque coefficient model. The wind farm system is decomposed into a DC capacitor component and an electrical control component, allowing the derivation of an analytical expression for damping torque from the electrical side. The mechanism of SSO is analyzed through damping characteristics, with system stability evaluated via a damping coefficient criterion (negative indicating instability). The study explores how grid strength, operating conditions, and control parameters affect SSO behavior and shows that adding a subsynchronous oscillation damping controller (SSDC) effectively mitigates the oscillation risk. Furthermore, a complex torque model for multi-substation wind farms is developed, enabling preliminary insights into dynamic interactions among sub-farms. Time-domain simulations in EMTDC/PSCAD verify the correctness of the proposed analytical model and its practical value for improving wind farm-grid integration stability.



Coauthored by Wenchao Zhai; Qi Jia; Gangui Yan from Northeast Electric Power University, Jilin, China.



You can check on the whole article on IEEE Xplore by:

https://ieeexplore.ieee.org/document/9862565

All CSEE JPES articles are OA published on IEEE Xplore.

Based on subsynchronous oscillation (SSO) caused by the connection of a direct drive wind farm to a weak alternating current (AC) grid, a complex torque model i

27/10/2025

Published in the CSEE Journal of Power and Energy Systems, this paper presents a novel optimization model for enhancing static voltage stability in power systems under multiple N−1 contingencies while accounting for wind power uncertainty. The proposed approach combines preventive and corrective control strategies to minimize control adjustment costs, including load shedding penalties across different contingency scenarios. The model incorporates chance constraints related to static voltage stability margins (SVSMs) and transforms them into deterministic formulations using approximate probability functions. To efficiently solve the model, the authors develop a sequential convex QP iteration method with fast second-order matrix approximation and apply a Naive Bayes classifier to identify the most critical contingencies. Case studies on the IEEE-39 bus system and a real-world provincial grid validate the method’s effectiveness in improving computational efficiency and system robustness under uncertainty.



Coauthored by Yuerong Yang; Shunjiang Lin; Qiong Wang; Mingbo Liu; Qifeng Li from South China University of Technology, Guangzhou, China and University of Central Florida, Orlando, FL, USA.



You can check on the whole article on IEEE Xplore by:

https://ieeexplore.ieee.org/document/10520197



All CSEE JPES articles are OA published on IEEE Xplore.

An optimal preventive-corrective control model for static voltage stability under multiple $N-1$ contingencies considering the wind power uncertainty is establi

25/10/2025

This paper, published in the CSEE Journal of Power and Energy Systems, tackles the complex problem of optimal bidding and portfolio optimization in the Financial Transmission Rights (FTR) auction market. Under the price-taker assumption, FTR market participants aim to maximize their profit, which hinges on the gap between uncertain FTR revenues and auction clearing prices. To address this uncertainty, the authors introduce a novel online learning-based methodology that continuously updates bidding strategies based on real-time market observations. The approach leverages a tree-based bid searching (TBS) algorithm, which offers both fast convergence to optimal bidding prices and a favorable linearithmic time complexity. The algorithm is further coupled with a budget-constrained portfolio optimization model to allocate financial resources efficiently across promising FTR options. Comparative evaluations demonstrate the superiority of the proposed method in terms of both learning speed and bidding performance, offering a powerful decision-making tool for participants navigating increasingly dynamic electricity markets.



Coauthored by Guibin Chen; Ye Guo; Wenjun Tang; Qinglai Guo; Hongbin Sun; Wenqi Huang from Tsinghua University, Shenzhen, Guangdong, China.



You can check on the whole article on IEEE Xplore by:

https://ieeexplore.ieee.org/document/10165643

All CSEE JPES articles are OA published on IEEE Xplore.

We consider the problem of optimal bidding and portfolio optimization for bidders in the financial transmission rights (FTR) auction market. Based on the price-

13/10/2025

This paper proposes a novel approach to harmonize price-based and incentive-based demand response (DR) in microgrids, addressing the temporal mismatch between their respective optimization horizons. Recognizing that these two types of DR—price-based demand response (PBDR) operating on a day-ahead scale and direct load control (DLC) functioning hourly—are often treated independently, the authors introduce a multi-agent deep reinforcement learning (MA-DRL) framework to enable temporally coordinated operation. Specifically, a multi-agent deep deterministic policy gradient (MA-DDPG) algorithm is developed, where each DR type is managed by an individual agent, and a shared critic ensures alignment toward a global revenue-maximizing objective for the microgrid. The coordination between time scales enhances the microgrid’s ability to cope with uncertainties from renewable energy sources. Case studies on a modified IEEE 33-bus and a heavily loaded 69-bus distribution system demonstrate that the proposed MA-DRL method significantly improves operational efficiency and economic performance compared to traditional approaches, paving the way for smarter and more resilient microgrid management.



Coauthored by Chunchao Hu; Zexiang Cai; Yanxu Zhang from South China University of Technology, Guangzhou, China.



You can check on the whole article on IEEE Xplore by:

https://ieeexplore.ieee.org/document/9862552

All CSEE JPES articles are OA published on IEEE Xplore.

Price-based and incentive-based demand response (DR) are both recognized as promising solutions to address the increasing uncertainties of renewable energy sour

11/10/2025

This paper addresses the growing flexibility challenges in power systems with high pe*******on of variable renewable energy (VRE) by introducing a novel modeling and planning framework for multi-timescale flexible resources. Recognizing that power system flexibility spans from seconds to months, the authors propose a characteristic domain transformation method to represent the operational boundaries of diverse flexibility resources. This transformation enables the integration and balancing of flexibility across multiple timescales through algebraic formulations, making it possible to rigorously quantify multi-timescale flexibility adequacy. Based on this model, the study develops a flexibility-aware planning approach, which is tested using real-world data from China’s Xinjiang power grid. Simulation results demonstrate that the method can accurately characterize and plan for system flexibility, ensuring reliable operation amid high levels of renewable energy variability.



Coauthored by Hai Li; Ning Zhang; Weihan Bao; Yue Fan; Ling D**g; Pengcheng Cai from Tsinghua University, Beijing, China.



You can check on the whole article on IEEE Xplore by:

https://ieeexplore.ieee.org/document/9862546

All CSEE JPES articles are OA published on IEEE Xplore.

The high pe*******on of variable renewable energy raises a flexibility challenge in the power system. This raises the necessity of considering the adequacy of f

11/10/2025

This paper, published in the CSEE Journal of Power and Energy Systems, investigates large-disturbance stability mechanisms in modern power systems integrating both synchronous generators (SG) and voltage source converter (VSC)-interfaced renewable energy sources. The study develops a hybrid system model and performs time-domain simulations under varying wind power pe*******on levels. Findings reveal two distinct instability modes: rotor angle instability dominated by SGs under low renewable pe*******on, and outer-loop control-induced instability under high pe*******on. The analysis further explores how VSC control limits—such as voltage and power boundaries—trigger new instability mechanisms, and examines the influence of different low-voltage ride through (LVRT) switching strategies on fault clearing times. These insights provide a deeper understanding of emerging stability risks in power-electronics-dominated systems and inform the development of more resilient control frameworks.



Coauthored by Liangshuai Hao; Lei Chen; Yong Min; Yalou Li; Shiyun Xu from Tsinghua University, Beijing, China and China Electric Power Research Institute, Beijing, China.



You can check on the whole article on IEEE Xplore by:

https://ieeexplore.ieee.org/document/10106198

All CSEE JPES articles are OA published on IEEE Xplore.

It is essential to study large-disturbance stability of power systems with high proportion of power electronic devices to discover new instability modes of rene

28/09/2025

Published in the CSEE Journal of Power and Energy Systems, this paper addresses the growing challenge of peak demand in distribution networks due to large-scale integration of DC loads such as electric vehicles (EVs) and air conditioners. The authors propose an innovative peak shaving operation management model based on interactive game theory among multiple stakeholders—namely distribution network operators, energy storage owners, and EV users—within an AC/DC hybrid distribution network. The model utilizes time-of-use pricing strategies to coordinate supply-demand balance via DC links, leveraging EVs and energy storage systems. Structured as a master-slave game framework, the study not only proves the existence and uniqueness of the game equilibrium but also ensures that all parties achieve optimal economic benefits. Simulation results confirm that this game-based management scheme significantly reduces the peak-to-valley load differences while promoting fair and efficient participation among stakeholders, offering a practical solution for smarter and more balanced grid operations.



Coauthored by Hongjun Gao; Lei Zhong; Cheng Wang; Lingzhu Zhang; Shafqat Jawad; Youbo Liu from Sichuan University, Chengdu, China.



You can check on the whole article on IEEE Xplore by:

https://ieeexplore.ieee.org/document/9606940

All CSEE JPES articles are OA published on IEEE Xplore.

The large-scale integration of DC loads, such as electric vehicles and air conditioners, has increased the peak demand of the distribution network. Therefore, t