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Theoretical and experimental studies on the self-healing properties of metallised capacitor films under multiple stresses

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High Voltage 2024年第6期9卷 1347-1356页

作者： Zhiyuan Wu Shangshu Liu Tong Tong Shaolong Zhong Jiantao Wang Hongbin Qi Zhimin Dang Wei Wang Beijing Key Laboratory of High Voltage and Electromagnetic Compatibility North China Electric Power UniversityBeijingChina State Key Laboratory of Power System Operation and Control Tsinghua UniversityBeijingChina

Metallised film capacitors,for the most important merits is the excellent self-healing property,have significant electrical insulation *** essential factors affecting the self-healing properties of metallised polypropylene film capacitors(MPPFCs)are first analysed,and a self-healing performance characterisation test platform for metallised polypropylene capacitor films was *** the voltage/current waveforms and discharge patterns of the self-healing process under multiple stresses including temperature,voltage and inter-layer pressure were recorded and *** correlation between self-healing performance characterisation and the carbon that appeared on the surface of the dielectric layer during the arc extinction time is ***,by virtue of an equivalent dynamic circuit model,the influence of square resistance and the equivalent capacitance of the power grid on self-healing has been theoretically studied.

关键词： films stresses film

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Research on Temperature Correction of Infrared Image based on Multi-emissivity of Substation Equipment 3

Research on Temperature Correction of Infrared Image based o...

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3rd International Conference on power systems and Electrical Technology, PSET 2024

作者： Dong, Jialong Han, Sheng Han, Xiaoqing Guo, Wei Taiyuan University of Technology Shanxi Key Laboratory of Power System Operation and Control Taiyuan China

ISBN: (纸本)9798350353204

Infrared thermal imaging technology is widely used for the inspection of substation equipment. Emissivity is necessary to calculate the temperature for infrared cameras, which varies with the different parts of substation equipment. Therefore, this paper proposes a multi-emissivity temperature correction method to obtain more accurate surface temperatures of substation equipment. Firstly, the paper explores a local parts recognition model for common substation equipment. Then, it studies the emissivity correction parameters for different parts. Finally, multi-emissivity is applied for temperature correction on various equipment parts in every infrared image. Test shows that the method can reduce temperature error than normal infrared cameras. © 2024 IEEE.

关键词： Temperature indicating cameras

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Electricity theft detection model based on feature engineering and integrated classifier 8

Electricity theft detection model based on feature engineeri...

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8th International Conference on Electrical, Mechanical and Computer Engineering, ICEMCE 2024

作者： Liu, Huijie Zhao, Qingsheng Liang, Dingkang Taiyuan University of Technology Shanxi Key Laboratory of Power System Operation and Control Shanxi Taiyuan030024 China

ISBN: (纸本)9798331506230

Focused on tackling the issue because the electricity theft detection model has low applicability and the recognition rate is greatly affected by subjective factors like manual extraction features, a power-stealing user recognition model based on feature engineering and integrated classifier is proposed. The model uses Tsfresh and Whale Optimization Algorithm (WOA) as the main feature extraction and selection tool. Then we use an integrated classifier to identify the abnormal users. Firstly, we collected the electricity consumption data of 600 different users for 583 consecutive days. Secondly, the rough feature extraction is performed by Tsfresh and the variance-based method. Thirdly, the Whale Optimization Algorithm is used to finely select the features, getting the most suitable feature parameters. Finally, the integrated classifier is used to classify abnormal users. After evaluating the performance of different classifiers ensemble, an integrated classifier is composed of a Decision Tree (DT), Support Vector Machine (SVM), and Random Forest (RF). Meanwhile, in terms of feature extraction, we compared the results of three single classifiers which consist of the integrated classifier, also compared with other feature selection and classification methods. The experimental results show that the average accuracy of this method is 96.11%, which is higher than other methods. © 2024 IEEE.

关键词： Random forests

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A data-driven topology identification method for low-voltage distribution network 3

A data-driven topology identification method for low-voltage...

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3rd International Conference on power systems and Electrical Technology, PSET 2024

作者： Shi, Shuo Han, Xiaoqing Li, Tingjun Zhang, Hao Yan, Hongbo Taiyuan University of Technology Shanxi Key Laboratory of Power System Operation and Control Taiyuan China

ISBN: (纸本)9798350353204

Correctly identifying the topology of low-voltage distribution grid is the key to ensure the safe and stable operation of the power system, and it is also the basis for realizing the loss analysis and fault diagnosis of the lines in the station area. Aiming at the situation that the data collected by smart meters may be missing, this paper proposes a data-driven method based on the topology identification of low-voltage distribution grids. The method firstly fills in the missing values and normalizes them according to the voltage time series data collected by smart meters. Second, the K-means clustering algorithm is used to classify and determine the upstream and downstream relationship of each user in a class in the distribution grid based on the magnitude of voltage amplitude. Then the correlation between nodes is calculated using Pearson correlation coefficient to calibrate the correctness of the topology. Finally, the feasibility of the proposed method is verified by simulation analysis of the IEEE33 node arithmetic example. © 2024 IEEE.

关键词： Network topology

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Deep Reinforcement Learning-based Multi-Scenario Multi-Scale Economic Scheduling for Integrated Energy systems 6

Deep Reinforcement Learning-based Multi-Scenario Multi-Scale...

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6th International Conference on Energy systems and Electrical power, ICESEP 2024

作者： Li, Guangxi Zhao, Qingsheng Han, Xiaoqing Li, Tingjun Taiyuan University of Technology Shanxi Key Laboratory of Power System Operation and Control Taiyuan China

ISBN: (纸本)9798350353563

The integrated energy system (IES) with multi-energy coupling and gradient utilization has become an important means to help realize the goal of 'double carbon'. The optimal operation of IES is a nonlinear, nonconvex and complex problem. With the gradual increase of intermittent energy and load uncertainty, traditional scheduling methods are limited to fixed physical models and parameter settings, which make it difficult to quickly and accurately obtain optimal scheduling strategies. In this paper, we propose a distributed proximal policy optimization (DPPO) algorithm to train the IES optimal scheduling model offline and solve the optimization online, which transforms the physical scheduling problem into a reinforcement learning sequential decision-making problem, and adaptively learns the scheduling policy through continuous interaction between the agent and the integrated energy system environment, and the multi-threaded structure enhances the exploration ability of the reinforcement learning agent in the complex environment. Example simulations show that online applications do not need to rely on accurate modeling of the physical model of the IES to achieve fast scheduling decisions in multiple scenarios and scales. © 2024 IEEE.

关键词： Deep reinforcement learning

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Identifying faults in UHVDC transmission systems using DAE and ensemble learning 8

Identifying faults in UHVDC transmission systems using DAE a...

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2024 8th International Conference on Hydrodynamics, Energy and Electric power system, HEEPS 2024

作者： Guo, Yiheng Zhao, Qingshen Liang, Dingkang Shanxi Key Laboratory of Power System Operation and Control Taiyuan University of Technology Taiyuan030024 China

The current fault identification technique for the ultra high voltage direct current transmission system has a low success rate, the process of extracting feature qualities is complex, and it is difficult to identify high resistance grounding. This research provides a defect evaluation method for UHVDC transmission system using Deep Auto Encoder (DAE) and integrated learning. Firstly, the fault voltage signal is feature extracted using DAE, and then, a series of obtained features are feature screened by XGBoost algorithm and combined with an integrated classifier consisting of Multi-Layer Perceptron (MLP), K Nearest Neighbor (KNN), and Random Forest (RF) classifiers to identify the UHVDC faults. Finally, ±800kV UHVDC transmission line models are established in MATLAB/Simulink simulation software to simulate different types of faults. The study's findings demonstrate that the fault diagnostic method introduced in this research may significantly enhance the poor detection success rate of current fault diagnostics methods and is more resilient to excessive resistance. © Published under licence by IOP Publishing Ltd.

关键词： MATLAB

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High power Density Buck Boost DC/DC Converter Using SIC MOSFET 1

High Power Density Buck Boost DC/DC Converter Using SIC MOSF...

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2024 1st International Conference on Smart Grids and power systems, ICSGPS 2024

作者： Rana, Zuraiz Meng, Runquan Ali, Kashif Haseeb, Rashid Shanxi Key Lab of Power System Operation and Control Taiyuan University of Technology Shanxi China

High power density is an advance in power electronics. Third generation wide-bandgap semiconductor devices (WBG SICs) offer significantly improved performance compared to standard silicon devices. SIC MOSFET is commonly used in power electronic equipment such as converters due to its low resistance, excellent thermal stability, and rapid switching speed. Increasing the switching frequency effectively reduces the circuit size. This article uses SIC MOSFET and STM32 single-chip MCU to design a high power density and higher frequency buck boost converter and establish a simulation model in LTspice. The driving circuit designed for SIC MOSFET is intended to maximize the converter's reliability. Synchronous rectification applies to enhance the converter efficiency. Compared to other types of converters, the size of the converter is reduced, achieving the goals of lightweight and high power density of DC/DC converters. © 2024 Published under licence by IOP Publishing Ltd.

关键词： Silicon carbide

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Two-stage Optimal Scheduling of Community Integrated Energy system Considering operation Sequences of Hydrogen Energy Storage systems

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Journal of Modern power systems and Clean Energy 2025年第1期13卷 276-288页

作者： Wei Kong Kai Sun Jinghong Zhao School of Electrical Engineering Naval University of EngineeringWuhanChina Department of Electrical Engineering State Key Laboratory of Power System Operation and ControlTsinghua UniversityBeijingChina

The hydrogen energy storage system(HESS)integrated with renewable energy power generation exhibits low reliability and flexibility under source-load *** address the above issues,a two-stage optimal scheduling model considering the operation sequences of HESSs is proposed for commercial community integrated energy systems(CIESs)with power to hydrogen and heat(P2HH)*** aims to optimize the energy flow of HESS and improve the flexibility of hydrogen production and the reliability of energy supply for ***,the refined operation model of HESS is established,and its operation model is linearized according to the operation domain of HESS,which simplifies the difficulty in solving the optimization problem under the premise of maintaining high approximate ***,considering the flexible start-stop of alkaline electrolyzer(AEL)and the avoidance of multiple energy conversions,the operation sequences of HESS are ***,a two-stage optimal scheduling model combining day-ahead economic optimization and intra-day rolling optimization is established,and the model is simulated and verified using the source-load prediction data of typical days in each *** simulation results show that the two-stage optimal scheduling reduces the total load offset by about 14%while maintaining similar operating cost to the day-ahead economic optimal ***,by formulating the operation sequences of HESS,the operating cost of CIES is reduced by up to about 4.4%.

关键词： Community integrated energy system(CIES) hydrogen storage operation sequence two-stage optimal scheduling

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Optimal Dispatch of Coordinated Source-Grid-Load-Storage in New power system Based on Low-Carbon Demand Response 7

Optimal Dispatch of Coordinated Source-Grid-Load-Storage in ...

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7th IEEE Conference on Energy Internet and Energy system Integration, EI2 2023

作者： Li, Yizhulin Han, Xiaoqing Li, Tingjun Zhao, Rui Yan, Boyang Tiyuan University of Technology Shanxi Key Laboratory of Power System Operation and Control Taiyuan China

ISBN: (纸本)9798350345094

In the context of China's 'double carbon' goal, energy saving and emission reduction has become one of the primary strategic objectives of the current power industry. Aiming at the carbon measurement and low-carbon regulation operation of the new power system, a low-carbon demand response scheduling strategy based on carbon emission flow is proposed. First, we analyze the carbon emission influencing factors of each link of source-network -load-storage of the new power system. Firstly, we analyze the carbon emission influencing factors of each link of source-network -load-storage of the new power system, and establish an accurate carbon measurement model based on the carbon emission flow theory. carbon emission factor is used as a guiding signal to establish a low-carbon demand response mechanism for optimised dispatch. Finally, the proposed strategy is verified through examples to stimulate the carbon emission flow theory. Finally, the proposed strategy is verified through examples to stimulate the emission reduction potential of each link in the system, reduce carbon emissions and improve the rate of new energy consumption. © 2023 IEEE.

关键词： Carbon

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Optimization of CRM Totem Pole PFC Based on Inductor Current Zero-Crossing Prediction Strategy 7

Optimization of CRM Totem Pole PFC Based on Inductor Current...

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7th International Conference on power and Energy Applications, ICPEA 2024

作者： Liu, Xin Ren, Chunguang Taiyuan University of Technology Shanxi Key Lab of Power System Operation and Control Taiyuan China

ISBN: (纸本)9798350356113

The totem-pole bridgeless PFC circuit based on GaN devices is currently a research hotspot. To achieve full-range ZVS (Zero Voltage Switching), it is necessary to select a reasonable ZCD (Zero Current Detection) sampling scheme and dead time for the inductor current in CRM (Critical Conduction Mode). Addressing the issues of large computational burden and poor reliability in current inductor current zero-crossing prediction strategies, this paper proposes optimizing the turn-off time of the freewheeling diode and the adaptive dead time to improve the reliability of inductor current zero-crossing prediction and the realization of full-range ZVS. Finally, leveraging the powerful computational capability of a high-performance DSP, the proposed method was validated through reasonable software design and the establishment of an experimental platform. © 2024 IEEE.

关键词： Gallium nitride

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