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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Fu, Guofeng Qin, Yekang Zhang, Hanting Liu, Ying Zeng, Fengna Han, Fangyuan Guigang Power Supply Bureau Guangxi Power Grid Co. Ltd. Guangxi Guigang537100 China State Key Laboratory of Power Transmission Equipment Technology School of Electrical Engineering Chongqing University Chongqing400044 China Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Guangxi Nanning530023 China

ISBN: (纸本)9789819613823

Investigating the gas production characteristics of insulation oil thermal cracking at the atomic level is of great significance for transformer fault diagnosis and condition assessment based on dissolved gas analysis. This paper simulates the thermal cracking kinetics of multi-component mixed oil using molecular dynamics, analyzing the gas production characteristics of modified natural esters and multi-component mixed oil at different temperatures. The results show that during the thermal cracking of multi-component mixed oil, C2H4 is generated in large quantities at various temperatures and is the most abundant characteristic gas. The content of H2, CO, CH4, C2H2, and C2H6 gradually increase with rising temperature, while CO2 is the first gas to be produced and tends to saturate. The contents of H2, CH4, C2H2, and C2H4 show significant trends with temperature changes and can be used as key characteristic gases for diagnosing faults and conditions of multi-component mixed oil transformers. This finding provides guidance for developing maintenance strategies for transformers using multi-component mixed oil. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Cracking (chemical)

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Monopolar Fault Reconfiguration of Bipolar DC System: Concept, Influence Factors and Implementation Method

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IEEE Transactions on Industry Applications 2025年

作者： Ma, Jianjun Deng, Yongkun Zou, Yangxin Zhu, Miao Wen, Shuli Gui, Yucheng Shanghai Jiao Tong University College of Smart Energy Shanghai China Shanghai Jiao Tong University Key Laboratory of Control of Power Transmission and Conversion Ministry of Education Shanghai China

In this article, the concept of monopolar fault reconfiguration is proposed for bipolar DC distribution system. For traditional HVDC grid, the healthy pole can maintain continuous power transmission during monopolar fault. Similarly, bipolar DC distribution system also has the potential for monopolar fault-tolerant operation. However, DC distribution system has more flexible source/load connections, various grounding types and the additional bipolar voltage balancer. To evaluate the influence of the aforementioned factors, the equivalent circuit model under monopolar fault is first established. With consideration of steady-state power flow and dynamic stability requirement, the feasibility of monopolar fault reconfiguration mode is analyzed. On that basis, the effects of PN line converter grounding resistance and bipolar voltage balancer protection delay are discussed. To reduce the protection delay, a current derivative (di/dt) detection method is proposed. The concept of monopolar fault reconfiguration, influence factors and implementation method are comparative evaluated through numerical simulations and experimental results, in verification of resilient power supply aim. © 1972-2012 IEEE.

关键词： DC distribution systems

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Resilience-Oriented transmission Expansion Planning under Hurricane Impact Considering Vulnerable Line Identification and Hardening

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Protection and control of Modern power Systems 2025年第3期10卷 98-113页

作者： Jing Zhou Heng Zhang Haozhong Cheng Shenxi Zhang Zheng Wang Xiaohu Zhang Electrical Engineering Department Key Laboratory of Control of Power Transmission and Conversion Ministry of Education Shanghai Jiao Tong University Shanghai China East China Branch of State Grid Corporation Shanghai China

Resilient enhancement measures are crucial for increasing systems' capacities to deal with extreme natural disasters. However, in the pre-disaster prevention stage of hurricanes, research that simultaneously considers load importance, vulnerable lines, and multiple resilience enhancement measures is lacking. To address this issue, a novel resilience-oriented transmission expansion planning (ROTEP) model is proposed that incorporates two resilience assessment indices: the combined loss of loads (CLL) and the vulnerable line survival proportion (VLSP). In addition, the novel function of the proposed model meets the requirements of normal and hurricane damage scenarios based on the collaborative implementation of three resilience enhancement measures (expansion planning, hardening, and unit commitment). The proposed ROTEP model is structured in two stages. The first-stage model aims to meet the load growth demand while minimizing the total planning cost of transmission lines, the operating cost of generators, and the penalty cost of wind power and load shedding across several normal scenarios. Based on the scheme obtained from the first-stage model, damage scenarios are constructed, and a fault chain set is formulated using a hurricane simulation model. Then, a cascading fault graph is constructed to identify vulnerable lines. The second-stage model further enhances the CLL and VLSP (if necessary) under several damage scenarios by hardening the highest-contributing or most vulnerable line. Finally, the efficacy of the proposed ROTEP model for enhancing resilience is validated with a modified IEEE RTS-24 system and a two-area IEEE RTS-1996 system.

关键词： Costs Systematics Target recognition Disasters Wind power generation transmission line measurements Hurricanes Planning Load modeling Resilience

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Enhanced Fault Ride-Through control Strategy for Grid-Forming Wind Turbine Generators Based on Inertia-Synchronization

IEEE Journal of Emerging and Selected Topics in Industrial E...

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IEEE Journal of Emerging and Selected Topics in Industrial Electronics 2025年

作者： Deng, Zhenyan Yang, Renxin Zhang, Yu Zhang, Chen Zhang, Jianwen Cai, Xu Shanghai Jiao Tong University Ministry of Education Laboratory of Control of Power Transmission and Conversion Department of Electrical Engineering Shanghai200240 China

Using the grid-forming (GFM) control is an important trend for grid-connected wind turbine generators (WTGs) to enhance the grid stiffness with high renewable penetration. The inertia-synchronization control (IsynC), which utilizes the DC-link dynamics for grid-synchronization, is a promising method to realize GFM control of the WTGs without affecting the maximum power point tracking target. However, most of the existing literature focuses on the steady-state operation of the IsynC-based WTGs, and the grid fault ride-through strategies are not properly designed. Existing WTGs rely on the current control loop to limit the short-circuit current(SCC) during grid faults, which not only suffers from transient overcurrent, but also fails to fully utilize the fault voltage support ability. To solve this problem, a unified SCC controller, which consists of a voltage vector limiter and an adaptive virtual resistor, is proposed. On this basis, the grid voltage support capability of the IsynC-based WTG under fault conditions is enhanced by using the phase angle compensation. A comparative simulation is conducted in PSCAD/EMTDC to highlight the advantages of the proposed method. Finally, the effectiveness of the proposed strategy is verified through the hardware-in-loop (HIL) experiment. © 2020 IEEE.

关键词： Wind Turbine Generators

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A Fast-Fixing Method for Stochastic Unit Commitment: A Trade-Off Analysis Between Accuracy and Efficiency

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IET Renewable power Generation 2025年第1期19卷

作者： Li, Ran Zhang, Lei Tao, Junyi Key Laboratory of Control of Power Transmission and Conversion Ministry of Education and Shanghai Non-Carbon Energy Conversion and Utilization Institute Shanghai Jiao Tong University Shanghai China College of Smart Energy Shanghai Jiao Tong University Shanghai China North Power Supply Branch Shanghai Electric Power Company Shanghai China

Stochastic unit commitment (SUC) addresses the uncertainties associated with renewable energy resources by generating various scenarios, which challenges the solution efficiency due to the vast number of variables and constraints involved. Existing methods apply machine learning techniques to accelerate the process by directly predicting generator outputs. However, machine learning may not deliver feasible solutions that meet all the constraints. This paper proposes a fast-fixing method (FFM) that predicts the probability distribution of unit statuses instead of directly predicting the dispatch decisions. With units on/off statuses partly prefixed, the original large-scale mixed-integer linear programming (MILP) problem will be simplified. The number of prefixed units can be adjusted by a threshold predicting acceptance (PA), providing a flexible choice for users to balance the trade-off between efficiency and accuracy. According to the case study on RTS-96 involving 15 to 30 generator units and 20 scenarios, when setting PA to 0.1, the proposed FFM significantly decreases the average solving time by 45.28% compared to CPLEX, 28.6% compared to Gurobi, and 21.43% compared to Benders decomposition, while only sacrificing a uniform 0.34% in average accuracy across all comparisons. © 2025 The Author(s). IET Renewable power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： Mixed-integer linear programming

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Distributed Consensus control for Multi-Bus DCMGs under Time-Varying Delays and Compound Noises

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IEEE Transactions on power Systems 2025年

作者： Sun, Shengxin Hailati, Gulizhati Xie, Da Ministry of Education Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Key Laboratory of Power Transmission and Power Conversion Control Shanghai200240 China Xinjiang Institute of Engineering Department of Electrical Engineering and Intelligent Control School of Energy Engineering Urumqi830023 China

Distributed controls in DC microgrids (DCMGs) are susceptible to interference from fading channels within their communication networks. There is also a lack of effective control and consensus performance analysis under communication delays and noises. Therefore, this paper proposes a distributed consensus control to mitigate the adverse effect of time-varying delays and compound noises, enabling rapid average bus voltage regulation and accurate current sharing in a multi-bus DCMG operating under a directed and sparse communication graph. Firstly, we establish the stochastic delay differential equation (SDDE) of the controlled system. Based on stochastic stability theory and algebraic graph theory, the sufficient conditions achieving a mean-square strong consensus are then derived through consensus performance analysis. Subsequently, a quantitative assessment of parameter impact is introduced by solving a nonlinear constrained optimization problem using the established theorem and corollary. Finally, this research studies the impact of the consensus gains on the upper bound of delay, admissible noise intensity, and convergence rate. Comprehensive simulations validate the accuracy and effectiveness of the theoretical analysis. Comparison results demonstrate the superiority of the proposed control in terms of the capability of resisting time delays and noise interferences. © 1969-2012 IEEE.

关键词： Constrained optimization

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Bi-level Low-carbon Optimal Operation Model of Multi-energy Aggregator in Energy and Flexibility Market

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IEEE Transactions on Industry Applications 2025年

作者： Xiong, Zhan Wang, Lingling Jiang, Chuanwen Zhou, Shichao Li, Yifan Ministry of Education Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering the Key Laboratory of Control of Power Transmission and Conversion Shanghai200240 China State Grid Shanghai Procurement Company Shanghai200235 China

Under the background of low-carbon transition, the development of renewable energy is an inevitable trend, making an increasing demand for flexibility. Multi-energy Aggregators (MEA) with multi-energy coupling devices can coordinate various energy sources to reduce carbon emissions, and provide flexibility for the electricity system as well. This paper proposes an interdependent electricity and natural gas market framework considering carbon-related costs and the flexibility market deployment to facilitate MEA to participate in the energy and flexibility trading. This problem is constructed as a bi-level optimization model. In order to promote carbon emission reduction, the upper model considers carbon-related costs when constructing the market model, and proposes the energy-carbon integrated pricing method. Furthermore, the clearing models of electricity, natural gas and flexibility markets are established. The lower-level model focuses on the optimal operation model of MEA to minimize its operational cost. The proposed bi-level model is transformed into a single-level mixed-integer second-order-cone programming (MISOCP) model by Karush-Kuhn-Tucker (KKT) conditions and duality theory. The case study verifies the effectiveness of the proposed model and solution method. © 2025 IEEE.

关键词： Low emission

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Resilience Enhancement of Coordinated transmission and Distribution System via Risk-based Decentralized Planning Against Typhoons

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IEEE Transactions on Industry Applications 2025年

作者： Yuan, Zijun Zhang, Heng Cheng, Haozhong Liu, Lu Liu, Jianqin Wang, Ying Cai, Defu Shanghai Jiao Tong University Key Laboratory of Control of Power Transmission and Conversion Ministry of Education Shanghai200240 China State Grid Economic and Technological Research Institute. Ltd. Beijing102209 China Electric Power Research Institute of Hubei Power Grid Corporation Wuhan430048 China

The occurrence of high-impact low-probability (HILP) natural disasters such as typhoons poses a significant threat to the secure operation of transmission and distribution (T&D) network system. Simultaneously, the rapid advancement in power distribution grid technologies contributes to the efficient interaction between transmission network and distribution network, thereby providing more possibilities for defending against disasters from a cooperative perspective in T&D network system. To explore the resilience enhancement potential of coordinated transmission and distribution system (CTDS) in defense of probabilistic typhoon impact, a risk-based decentralized planning model for CTDS is proposed aiming at mitigating load reduction at the transmission-distribution level considering random typhoon impact. The planning decision incorporates the investment in transmission line hardening, transmission network expansion at transmission level and distribution line hardening, mobile emergency generator (MEG) deployment as well as automatic switch deployment at distribution level. To address the decentralized model with multiple scenarios, a novel integrated solution procedure is proposed which embeds the alternating direction method of multipliers (ADMM) into a bundle-based progressive hedging algorithm (BPHA), thereby enhancing computation efficiency. The effectiveness and superiority of the proposed resilience enhancement method is demonstrated on a T6D3 system and a T118D7 system. © 1972-2012 IEEE.

关键词： Decentralized systems

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Active Thermal control for Enhancing Fault Current Output Capability of Grid-Forming Converters

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IEEE Transactions on power Electronics 2025年

作者： Deng, Zhenyan Cao, Siyu Ma, Ke Wang, Han Zhou, Dangsheng Cai, Xu Shanghai Jiao Tong University Ministry of Education Laboratory of Control of Power Transmission and Conversion Department of Electrical Engineering Shanghai China Shenzhen Hopewind Electric Company Ltd. Shenzhen518055 China

Implementing grid-forming (GFM) control is increasingly considered as a solution to facilitate power-electronics-dominated power systems. Despite its potential, limited by the thermal stress of power devices, the excessive output current under grid faults needs to be curtailed. The low-level fault current of GFM converters will significantly reduce the fault voltage support capability compared with conventional synchronous generators (SGs). Although direct modifications to the physical structure of power devices, i.e., oversizing IGBTs, can be effective to some extent, the additional costs and value streams for over-designing have not been clearly defined. To fill this gap, an active thermal control of GFM converters that utilizes the inherent current tolerance of power devices is proposed in this paper. This method enables online monitoring of junction temperature via a frequency-domain electrothermal model. Moreover, the switching frequency and modulation strategy are dynamically adjusted based on estimated temperature to enhance the short-time fault current output capability during grid faults. The proposed method is verified through comprehensive simulation, and the experiments based on a practical 1 MW converter are conducted to demonstrate the effect of fault current enhancement. © 1986-2012 IEEE.

关键词： active thermal control Grid-forming control junction temperature monitoring power module switching frequency modulation

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Modeling Human-Like Car-Following Model for Intelligent Vehicles Based on Deep Reinforcement Learning

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International Journal of Automotive Technology 2025年 1-10页

作者： Wang, keyin Liu, Yiyang Zhang, Jianhui School of Automotive Engineering Hubei University of Automotive Technology Shiyan 442002 China Automotive Power Transmission and Electronic Control Key Laboratory of Hubei Province Shiyan 442002 China

This paper proposed a human-like car-following model for intelligent vehicles based on deep reinforcement learning (DRL). To enhance anthropomorphic performance, a concise yet effective reward function is devised, incorporating desired inter-vehicle distance. Concurrently, the model’s state set, action set, neural network structure, and environment update strategy are meticulously crafted. The proposed model is then trained and tested on car-following events selected from the NGSIM dataset based on predefined selection rules. Then, a novel evaluation method employing the root mean square error (RMSE) of time headway (THW), time to collision inverse (TTCi), and acceleration is introduced to assess the anthropomorphic performance of the car-following model. Subsequently, the model’s efficacy is compared with benchmarks including the intelligent driver model (IDM), artificial neural network (ANN) models, model predictive control (MPC) models, and another variant of DRL models. Simulation findings unequivocally demonstrate the superior anthropomorphic performance of the proposed car-following model. © The Author(s), under exclusive licence to The Korean Society of Automotive Engineers 2025.

关键词： Car-following model Driving style DRL Human-like NGSIM

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