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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...

引用

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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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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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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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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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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Coordinated control Strategy of Secondary Ripple in DC Microgrid Based on Impedance Model 5th

Coordinated Control Strategy of Secondary Ripple in DC Micro...

引用

5th International Conference on Energy Storage and Intelligent Vehicles, ICEIV 2022

作者： Li, Xuejin Ren, Chunguang Pang, Fangyuan Deng, Haonan Wang, Yifan Qin, Yue Shanxi Key Lab of Power System Operation and Control Taiyuan University of Technology Taiyuan China

ISBN: (纸本)9789819910267

When DC microgrid is connected to a single-phase AC load, it will cause the DC bus to generate double-frequency voltage pulsation, which seriously affects the normal operation of important units. To solve the above problems, from the perspective of impedance modeling, this paper proposes a secondary ripple coordinated control strategy of DC microgrid based on impedance model. Firstly, the origin of the secondary ripple voltage of the DC microgrid is firstly analyzed, and the input and output impedance models of each unit of the DC microgrid are established. On this basis, the paper introduces band-pass and band stop filters to reshape the output impedance of each key converter at 100 Hz, so as to realize the effective suppression of secondary ripple current by energy storage converter. In order to further reduce the influence of secondary ripple power on each unit connected to the DC bus and ensure the voltage quality of DC bus. The active capacitor converter is introduced to actively control the secondary ripple power by adjusting the virtual capacitance of the active capacitor, so as to suppress the secondary ripple voltage of the DC bus. Finally, the effectiveness of the control strategy proposed in this paper is verified by simulation. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： power quality

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Study of improved active-clamped phase shift full bridge converter 3

Study of improved active-clamped phase shift full bridge con...

引用

3rd International Conference on Electrical Engineering and control Science, IC2ECS 2023

作者： He, Xin Meng, Runquan Li, Ruishu Taiyuan University of Technology Shanxi Key Lab of Power System Operation and Control Taiyuan China

ISBN: (纸本)9798350382426

Aiming at the drawbacks of the conventional phase-shifted full-bridge topology in terms of high voltage stress in the synchronous rectifier switches and high switching loss of the primary-side switch under low load conditions, a phase-shifted full-bridge circuit with improved control of an active clamp circuit is proposed. The converter utilizes the resonance of the switch parasitic capacitance with the primary-side resonant inductor to achieve ZVS (Zero- Voltage-Switch) under light load, and effectively improves the efficiency under heavy load by zeroing the primary-side current in the circulating current stage. In this paper, the topology, operating principle and operating characteristics of the proposed scheme are described in detail, and the feasibility of the scheme is verified by simulation in PLECS platform. © 2023 IEEE.

关键词： Active clamp component LC resonance Phase-shifted full bridge Switched capacitor Zero-voltage switching

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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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Robust optimization scheduling of microgrid considering a tiered carbon trading mechanism and flexible loads 3

Robust optimization scheduling of microgrid considering a ti...

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2024 3rd International Conference on Green Energy and power systems, ICGEPS 2024

作者： Li, Xiaoxu Yang, Qianjie Qin, Wenping Shanxi Key Lab of Power System Operation and Control Taiyuan University of Technology Shanxi Taiyuan030024 China State Grid Yuncheng Power Supply Company Shanxi Yuncheng044000 China

Considering the comprehensive demand response, stepwise carbon trading, and uncertainty of wind power output for cogeneration microgrids, relevant optimization scheduling research will be carried out. The electric heating load is divided into non-dispatchable electric heating load and dispatchable electric heating load. By introducing electric heating demand and tiered carbon trading, the economic and low-carbon operation of microgrids can be achieved. The fluctuation of the output of new energy units is reflected using probability scenario sets in statistics, and a robust optimization model with related distributions is constructed using the C&CG algorithm to calculate and solve the established model. The simulation and comparison of numerical examples show that the microgrid energy management scheme formulated by the model established in this paper has good economic and environmental friendliness, and it also simultaneously validated the superiority of distributed robust optimization methods over traditional optimization methods © Published under licence by IOP Publishing Ltd.

关键词： Numerical methods

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