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Demand-side Management Based on Model Predictive control in Distribution Network for Smoothing Distributed Photovoltaic Power Fluctuations

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Journal of Modern Power Systems and Clean Energy 2022年第5期10卷 1326-1336页

作者： Jian Xu Haobo Fu Siyang Liao Boyu Xie Deping Ke Yuanzhang Sun Xiong Li Xiaotao Peng IEEE School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China Power Dispatching and Control Center of State Grid Jibei Electric Power Company Limited Bejing 100054China

With the rapid increase of distributed photovoltaic(PV) power integrating into the distribution network(DN), the critical issues such as PV power curtailment and low equipment utilization rate have been caused by PV power fluctuations. DN has less controllable equipment to manage the PV power fluctuation. To smooth the power fluctuations and further improve the utilization of PV, the regulation ability from the demandside needs to be excavated. This study presents a continuous control method of the feeder load power in a DN based on the voltage regulation to respond to the rapid fluctuation of the PV power output. PV power fluctuations will be directly reflected in the point of common coupling(PCC), and the power fluctuation rate of PCCs is an important standard of PV ***, a demand-side management strategy based on model predictive control(MPC) to mitigate the PCC power fluctuation is proposed. In pre-scheduling, the intraday optimization model is established to solve the reference power of PCC. In real-time control, the pre-scheduling results and MPC are used for the rolling optimization to control the feeder load demand. Finally,the data from the field measurements in Guangzhou, China are used to verify the effectiveness of the proposed strategy in smoothing fluctuations of the distributed PV power.

关键词： Demand-side management multi-time-scale optimization power fluctuation smoothing load control model predictive control(MPC)

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Terahertz Spectroscopic Characterization and Thickness Evaluation of Internal Delamination Defects in GFRP Composites

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Chinese Journal of Mechanical engineering 2023年第1期36卷 190-210页

作者： Walter Nsengiyumva Shuncong Zhong Manting Luo Bing Wang Fujian Provincial Key Laboratory of Terahertz Functional Devices and Intelligent Sensing School of Mechanical Engineering and AutomationFuzhou UniversityFuzhou350108China Institute of Precision Instrument and Intelligent Measurement&Control Fuzhou UniversityFuzhou350108P.R.China School of Mechanical and Electrical Engineering Putian UniversityPutian351100China

The use of terahertz time-domain spectroscopy(THz-TDS)for the nondestructive testing and evaluation(NDT&E)of materials and structural systems has attracted significant attention over the past two decades due to its superior spatial resolution and capabilities of detecting and characterizing defects and structural damage in non-conducting *** this study,the THz-TDS system is used to detect,localize and evaluate hidden multi-delamination defects(i.e.,a three-level multi-delamination system)in multilayered GFRP composite *** obtain accurate results,a wavelet shrinkage de-noising algorithm is used to remove the noise from the measured time-of-flight(TOF)*** thickness and location of each delamination defect in the z-direction(i.e.,through-the-thickness direction)are calculated from the de-noised TOF signals considering the interaction between the pulsed THz waves and the different interfaces in the GFRP composite laminates.A comparison between the actual and the measured thickness values of the delamination defects before and after the wavelet shrinkage denoising process indicates that the latter provides better results with less than 3.712%relative error,while the relative error of the non-de-noised signals reaches 16.388%.Also,the power and absorbance levels of the THz waves at every interface with different refractive indices in the GFRP composite laminates are evaluated based on analytical and experimental *** present study provides an adequate theoretical analysis that could help NDT&E specialists to estimate the maximum thickness of GFRP composite materials and/or structures with different interfaces that can be evaluated by the ***,the accuracy of the obtained results highlights the capabilities of the THz-TDS for the NDT&E of multilayered GFRP composite laminates.

关键词： Glass-fiber-reinforced polymer-matrix(GFRP)composites Terahertz time-domain spectroscopy(THz-TDS) Nondestructive testing and evaluation(NDT&E) Stationary wavelet transform(SWT) Thickness evaluation Delamination defects

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Infrared Thermal Image Fault Detection of Electric Motor Based on Improved VGG16 Network Model 6

Infrared Thermal Image Fault Detection of Electric Motor Bas...

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6th International Conference on Communications, Information System and Computer engineering, CISCE 2024

作者： Zhu, Xianghua Hu, Shan Bing, Zhigang Zhao, Di School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Key Laboratory of Information Sensing & Intelligent Control Tianjin China Engineering Teaching Practice Training Center of Tiangong University Tianjin China

ISBN: (纸本)9798350353174

As a core component of modern industry, electric motors are widely used in important fields such as electric power, machinery and national defense, and the fault detection of their thermal images faces problems such as diverse fault types, insufficient complex data processing capability and long training time. To address the above problems, this paper proposes a method for fault detection of infrared thermal images of electric motors based on an improved VGG16 network model. In the model construction and implementation, based on the VGG16 network model, the significant optimization of training time and accuracy is achieved by improving the structure of the latter layers of the model and introducing the migration learning strategy, as well as adding the callback function, the AdamW optimizer and the focal point loss function to the model. The experimental results show that the improved VGG16 model increases the average accuracy by 12.96%, reduces the average loss rate by about 23 times, and shortens the training time by half in infrared thermal image fault detection of induction motors. In the model performance evaluation, whether adjusting the test conditions or conventional model evaluation methods, the results reflect the superiority of the improved model in the realm of infrared thermal image anomaly identification of induction motors, which has practical application value. © 2024 IEEE.

关键词： Electric motors

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Modeling and sliding mode control based on inverse compensation of piezo-positioning system

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中国光学(中英文) 2025年第1期18卷 170-185页

作者： LI Zhi-bin XIN Yuan-ze ZHANG Jian-qiang SUN Chong-shang College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Center for Advanced Control and Smart Operations Nanjing UniversitySuzhou 215163China

In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are *** model is used to represent the dynamic hysteresis nonlinear characteristics of piezo-positioning *** static nonlinear part and dynamic linear part of the Hammerstein model are represented by models obtained through the Prandtl-Ishlinskii(PI)model and Hankel matrix system identification method,*** model demonstrates good generalization capability for typical input frequencies below 200 Hz.A sliding mode inverse compensation tracking control strategy based on P-I inverse model and integral augmentation is *** results show that compared with PID inverse compensation control and sliding mode control without inverse compensation,the sliding mode inverse compensation control has a more ideal step response and no overshoot,moreover,the settling time is only 6.2 *** the frequency domain,the system closed-loop tracking bandwidth reaches 119.9 Hz,and the disturbance rejection bandwidth reaches 86.2 *** proposed control strategy can effectively compensate the hysteresis nonlinearity,and improve the tracking accuracy and antidisturbance capability of piezo-positioning system.

关键词： piezo-positioning system hysteresis nonlinearity Hammerstein model Prandtl-Ishlinskii(P-I)model system identification sliding mode control

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A 3D Spiral-Zigzag Gas Leakage Source Search Algorithm Based on Olfaction and Vision 6

A 3D Spiral-Zigzag Gas Leakage Source Search Algorithm Based...

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6th International Conference on Industrial Artificial Intelligence, IAI 2024

作者： Han, Ze-Rong Li, Ji-Gong Yang, Jing School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China School of Information Technology Engineering Tianjin University of Technology and Education Tianjin China

ISBN: (纸本)9798350356618

Accidents such as fires and chemical leakage, which occur from time to time, seriously endanger public safety. The use of robot to discover and track the source of gas/chemical plume can replace traditional manual search, greatly reducing the risk and cost of search and improving efficiency. Most of the existing gas leakage source search methods are applied in two-dimensional environments, and for the scenarios where the plume is visible, the efficiency of searching and the success rate of source localization only relying on the olfaction is usually low. To this end, this paper proposes a plume finding and tracing method based on olfaction and vision with a drone in 3D outdoor environments. In the plume finding phase, olfactory information is combined with visual object detection in the 3D Spiral algorithm to improve plume finding efficiency. During the plume tracing phase, the drone performs a 3D Zigzag motion to rapidly approach the source of the gas leakage. If the plume is lost during tracing, the 3D Spiral algorithm, which combines olfactory and visual information, is used again in local area with a view to find the plume again. Experimental and simulation results show that the efficiency of plume finding can be significantly improved by using visual object detection for the plume, and the proposed plume finding and tracing method combining olfactory and visual information has high search efficiency and success rate. © 2024 IEEE.

关键词： Object tracking

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Linear active disturbance rejection control of brushless dc motor based on improved gray wolf optimization algorithm 3

Linear active disturbance rejection control of brushless dc ...

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3rd International Conference on Intelligent Mechanical and Human-Computer Interaction Technology, IHCIT 2024

作者： Luo, Peiyue Zhang, Hongxin Tian, Liguo Xie, Ziyang Sun, Miao School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin300222 China

ISBN: (纸本)9781510683105

In this paper, an improved gray wolf optimization linear active disturbance rejection control (IGWO-LADRC) had been proposed by improving the grey wolf population initialization, convergence factor, and grey wolf position updating strategy of the traditional grey wolf optimization algorithm. The problems of standard gray wolf optimization algorithm in linear active disturbance rejection control parameters tuning, such as low efficiency of optimization search and easy fall into local optimal solution, had been solved. A brushless DC motor control system based on IGWO-LADRC and a brushless DC motor control system based on gray wolf optimization linear active disturbance rejection control (GWO-LADRC) had been built. The comparison had shown that IGWO-LADRC had a fast optimization-seeking speed, high control accuracy, quick response speed, and strong anti-interference ability. © 2024 SPIE.

关键词： Disturbance rejection

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Research on Geospatial Object Recognition Algorithm in Power Transmission and Transformation engineering Based on FIseg-YOLO 1

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8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Ouyang, Peng Pi, Yufei Zhang, Pengcheng Zhang, Kun School of Electrical Engineering and Automation Nantong University Nantong China Nantong Key Laboratory of Intelligent Control and Intelligent Computing Nantong Institute of Technology Jiangsu Nantong China

ISBN: (数字)9789819603138

ISBN: (纸本)9789819603121

The preliminary work of power transmission and transformation engineering design tasks relies on the precise survey of terrain to ensure the high-quality completion of design tasks. Therefore, developing a technology that can accurately and efficiently survey the construction area has become a hot topic in the field of electrical design research. However, identifying the location and precise boundaries of geospatial targets of different scales and densities from high-resolution natural environment images captured by drones remains a challenge. To address this issue, we improved upon the YOLOv8 algorithm by incorporating the concept of the YOLACT algorithm, proposing a novel instance segmentation algorithm—FIseg-YOLO, specifically designed for recognizing geospatial targets in power transmission and transformation line projects. This algorithm integrates various attention mechanism modules in the backbone network, effectively improving the accuracy of target recognition against complex backgrounds. Simultaneously, we optimized the neck network structure by enhancing the multi-path fusion of the network, achieving multi-level feature fusion between different layers. Additionally, the algorithm adds a multi-scale detection head to the basic network structure to extract shallow information from the input image and combine it with the feature fusion network to detect objects across a broader scale. Experimental validation on the geospatial orthophoto dataset shows that the mAP@.5 of the FIseg-YOLO model reached 67.3%, a 6.6% increase compared to the YOLOv8 base model, indicating a significant improvement in model performance. This improvement is of great significance for enhancing the efficiency of preliminary survey tasks in power transmission and transformation engineering. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning

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Estimation of Plant Growth Environment Temperature based on Plant electrical Signals 7

Estimation of Plant Growth Environment Temperature based on ...

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7th IEEE Information Technology, Networking, Electronic and automation control Conference, ITNEC 2024

作者： Wang, Yifan Tian, Liguo Li, Meng College of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin300222 China

ISBN: (纸本)9798350370782

electrical signals are an important type of signals in plants, which can not only regulate normal physiological activities, but also reflect the current environmental temperature of plants to a certain extent. The plant electrical signal was collected and the Peak value, Peak to peak and Mean value were extracted as eigenvalues, and the BP neural network was trained to obtain the correspondence model between the eigenvalues of the signal and the ambient temperature. The mean square deviation (MSE) and correlation coefficient (R) of the trained BP neural network model were 0.0058 and 0.9408, respectively. In the re-collected data, 90% of the estimated values fall between 01, and the judgment effect is good, which proves that the model has a high accuracy of judgment. In the future, plant electrical signals can be combined with neural network models to detect temperature, humidity and other parameters in plant growth states, which has high application value in smart agriculture. © 2024 IEEE.

关键词： BP neural network model judgment plant electrical signals relational model smart agriculture Temperature detection

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Research on operation optimization of rural hybrid renewable energy systems based on Nash bargaining 8

Research on operation optimization of rural hybrid renewable...

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8th International Conference on Energy System, Electricity, and Power, ESEP 2023

作者： Zhuang, Xin Gao, Qiang Xu, Zhao Chen, Jiaqi Zhang, Zhengyang Liu, Junjie College of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory of Complex System Control Theory and Applications Tianjin300384 China

ISBN: (数字)9781510679801

ISBN: (纸本)9781510679795

The Rural Hybrid Renewable Energy System (RHRES) holds great significance as a prospective energy system development. Ensuring its economic viability and low-carbon operation is crucial in order to fully harness its potential. Consequently, this research paper presents a multi-party cooperation operation model for RHRES, based on the Nash bargaining theory. To effectively differentiate between the various parties involved in carbon trading and guarantee the system's low-carbon operation, a ladder-type multi-party carbon trading model is formulated. The proposed RHRES cooperation operation model, grounded in Nash bargaining, is approached in two steps: determining the transaction volume between parties and resolving the transaction price through the concept of equivalent transformation. To address concerns regarding party privacy, the alternating direction multiplier method is employed for solution. The numerical findings demonstrate that the suggested cooperation operation model substantially reduces RHRES operating costs and carbon emissions, while enhancing the utilization of wind and solar power. Consequently, this model holds significant practical and promotional value. © 2024 SPIE.

关键词： Solar energy

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A Proposal Of An Iterative Learning control Method For Simulating A Flyback Converter Using PSCAD 9

A Proposal Of An Iterative Learning Control Method For Simul...

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9th International Conference on Applying New Technology in Green Buildings, ATiGB 2024

作者： Cao, Trung Thanh Van, Cuong Trinh Van, Hung Pham Nguyen, Minh Quang Hoang, Anh Hanoi University of Science and Technology School of Electrical and Electronic Engineering Hanoi Viet Nam Ha Noi University of Industry Department of Automation and Control Hanoi Viet Nam

ISBN: (纸本)9798331505042

DC-DC converters are essential components in power supply applications, portable electronics, renewable energy systems, and various other industries. An accurate system model is crucial for the development of the controller for a DC-DC converter. This research study focused on the development of an iterative learning control that operates without requiring the system model. The study employs PSCAD simulation software to simulate and analyze the effectiveness of an iterative learning control and a sliding mode controller for flyback converter. Detailed simulation results and comparisons between the two methodologies will be presented. © 2024 IEEE.

关键词： Sliding mode control

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