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Coordinated Operation of Active Distribution Network and Mobile Energy Storage Using Stackelberg Game

IEEE Transactions on Industrial Informatics 2025年第6期21卷 4423-4434页

作者： Guo, Hui Wu, Songmei Shi, Tianling Wang, Fei Gong, Dandan Shanghai University Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronics Engineering and Automation Shanghai200444 China

To improve system flexibility and reliability, mobile energy storage (MES) is treated as a unified dispatching resource of the active distribution network (ADN) to participate in operation optimization and power supply recovery. However, the coordinated optimization of MES with ADN network reconfiguration and voltage regulation is neglected in current studies. Especially, there exists blank research on ADN and MES as independent stakeholders. Therefore, a coordinated operation strategy based on the Stackelberg game for ADN and MES is proposed. Considering multitime period dynamic reconfiguration, voltage regulation, and their joint optimization with MES, the ADN as a leader, makes a tradeoff between expected profits and reliability to formulate reasonable prices for MES. As a follower, MES models energy transfer characteristics based on the space-time network and actively participates in the operation optimization of ADN by responding to the price decision to increase revenue. Following that, Karush-Kuhn-Tucker conditions are used to transform the two-layer optimization model based on the Stackelberg game into a single-layer mixed integer linear programming problem for solution. Finally, simulations on an improved IEEE-33 bus system validate the proposed strategy, which saves 2.2% of total social costs and reduces 6% of the voltage deviation. © 2025 IEEE. All rights reserved.

关键词： Power distribution networks

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Computational and experimental investigations of a microfluidic mixer for efficient iodine extraction using carbon tetrachloride enhanced with gas bubbles

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Chinese Physics B 2023年第11期32卷 518-526页

作者： Siddique Muhammad Kashif 孙林李松晶 Department of Fluid Control and Automation School of Mechatronics EngineeringHarbin Institute of TechnologyHarbin 150001China

Numerous studies have been conducted on microfluidic mixers in various microanalysis systems, which elucidated the manipulation and control of small fluid volumes within microfluidic chips. These studies have demonstrated the ability to control fluids and samples precisely at the microscale. Microfluidic mixers provide high sensitivity for biochemical analysis due to their small volumes and high surface-to-volume ratios. A promising approach in drug delivery is the rapid microfluidic mixer-based extraction of elemental iodine at the micro level, demonstrating the versatility and the potential to enhance diagnostic imaging and accuracy in targeted drug delivery. Micro-mixing inside microfluidic chips plays a key role in biochemical analysis. The experimental study describes a microfluidic mixer for extraction of elemental iodine using carbon tetrachloride with a gas bubble mixing process. Gas bubbles are generated inside the microcavity to create turbulence and micro-vortices resulting in uniform mixing of samples. The bubble mixing of biochemical samples is analyzed at various pressure levels to validate the simulated results in computational fluid dynamics(CFD). The experimental setup includes a high-resolution camera and an air pump to observe the mixing process and volume at different pressure levels with time. The bubble formation is controlled by adjusting the inert gas flow inside the microfluidic chip. Microfluidic chip-based gas bubble mixing effects have been elaborated at various supplied pressures.

关键词： microfluidic mixer iodine extraction CFD simulation micro-mixing properties

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Observer-based event-triggered networked multi-drives speed consensus

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Digital Communications and Networks 2022年第5期8卷 763-769页

作者： Suhaib Masroor Chen Peng School of Mechatronics Engineering and Automation Shanghai UniversityShanghai200444China

The problem of having an identical speed when dealing with multiple motors always exists in the *** are several methods to address the problem,but all the methodologies have two common ***,the control design requires continuous information on the desired speed and the actual speed of motors;secondly,it is sometimes difficult to directly measure the speed *** the proposed study,both of these drawbacks are addressed by designing an observer-based event-triggered networked multi-agent *** proposed method uses the leader following consensus approach with a centralized event triggering control design so that whenever a follower's speed diverges from that of the leader,an event is triggered,which communicates and resets all the agents to the leader's ***,an observer is designed such that the ith agent uses its jth neighbor agent and observer speed information to estimate the leader's *** stability of the proposed design is formulated by Lyapunov stability,while the simulation results endorse the design concepts and energy saving.

关键词： Multi-agent coordination control Centralized event triggering Network control system Sylvester equation Lyapunov stability

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A Classification Method for Unordered Steel Scrap Images Based on Hybrid Convolutional Networks 24

A Classification Method for Unordered Steel Scrap Images Bas...

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3rd International Conference on Signal Processing, Computer Networks and Communications, SPCNC 2024

作者： Yu, Yan School of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9798400710834

With the development of deep learning and image recognition technologies, these methods have found widespread applications across various fields. However, the annotation of industrial application-specific data, such as steel scrap images, remains challenging due to the unordered nature of the images, which often requires domain experts to perform the annotation. To address this, we propose a feature learning method for unordered images based on hybrid convolutional networks. Utilizing a preprocessed steel scrap dataset, we employ a cascaded convolutional network to capture deep correlation features within such unordered images while enhancing their fine-grained structures. A self-supervised approach is used to train the encoder, which is subsequently fine-tuned using a minimal set of labeled samples to complete the classification and annotation of steel scrap. Experimental results on four different categories of steel scrap annotation demonstrate that the proposed method achieves accuracies of 60.47%, 61.24%, 23.45%, 62.46%, respectively, verifying the effectiveness of the method. © 2024 Copyright held by the owner/author(s).

关键词： Self-supervised learning

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Research on Reliability Improvement and Index Structure Optimization Based on B+ Trees 24

Research on Reliability Improvement and Index Structure Opti...

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3rd International Conference on Signal Processing, Computer Networks and Communications, SPCNC 2024

作者： Yu, Yan Tang, Junmiao Zhang, Hesong Zhang, Hesheng School of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9798400710834

In aerospace systems, B+ trees are typically used for data management and indexing. However, traditional B+ trees have issues with data reliability and slower indexing speeds when handling massive data volumes. To address these issues, an improved B+ tree structure is proposed. This improvement involves a custom memory pool to manage the creation and deletion of tree nodes and employs a dynamic optimization algorithm to reduce the height of the B+ tree. Additionally, an automatic snapshot and logging system is introduced to ensure the recoverability of the B+ tree in case of system failures, enhancing its performance and reliability in complex environments. Comparative experiments indicate that the improved B+ tree achieves a 14.02% increase in efficiency for node insertion operations, a 27.39% speed improvement in searching for specific keys, and reduced memory consumption due to the dynamic optimization algorithm, demonstrating significant advantages in memory-constrained aerospace systems. © 2024 Copyright held by the owner/author(s).

关键词： Memory management

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A Visual Monitoring Method for Monochromators Based on Video Super-Resolution and Kalman Filter 5

A Visual Monitoring Method for Monochromators Based on Video...

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5th International Conference on Intelligent Computing and Human-Computer Interaction, ICHCI 2024

作者： Li, Zhijuan Ma, Shiwei School of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9798350368284

To achieve real-time and precise monitoring of the main moving component of the monochromator. We have developed a visual monitoring system for monochromator based on machine vision technology for SSRF. To enhance the accuracy and stability of visual detection, this paper proposes a visual monitoring method that integrates video super-resolution (VSR) and kalman filter (KF) with YOLOv5 object detection. First, VSR is applied to enhance the quality of images captured by the camera. Then, scale numbers on a ruler are detected, and KF is employed for stable tracking of the scale numbers' detection boxes. Finally, the position of the monitored subjects is calculated based on tracking results of the scale numbers on the ruler. Experimental results demonstrate that by implementing VSR, the detection rate of scale numbers improved by an average of 12%, and in combination with the tracking algorithm based on KF, the proposed method achieves enhanced stability in the positioning of the moving component in the monochromator. © 2024 IEEE.

关键词： Kalman filters

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Sensorless Control of Synchronous Reluctance Motor Based on High Frequency Pulse Vibration Voltage Injection Method 11th

Sensorless Control of Synchronous Reluctance Motor Based on ...

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11th Frontier Academic Forum of Electrical Engineering, FAFEE 2024

作者： Yu, Zixu Song, Wenxiang Tao, Jianxun School of Mechatronics Engineering and Automation Shanghai University Shanghai200444 China

ISBN: (纸本)9789819788156

Aiming at the zero low speed operation of synchronous reluctance motor without position sensor, an improved high frequency pulse voltage injection control algorithm is proposed. Using a Simplified First-Order Linear ADRC to Replace the PI Control in the Speed Outer Loop and the rotor position information is obtained by demodulation of the stator current αβ axis component, and a simplified linearized auto-disturbance rejection control algorithm is used to optimize the speed closed-loop control of synchronous reluctance motor. This method omits the band-pass filter used in traditional approaches, simplifying the system architecture and effectively reducing motor speed fluctuations. The experimental results show that the proposed improved high-frequency pulse voltage injection method in this study exhibits excellent steady-state and dynamic performance at low speeds. The enhanced control strategy shows superior rotor position tracking capabilities across different speeds, speed transitions, and sudden load additions in the low-speed domain. These experiments validate the feasibility and effectiveness of this control approach for synchronous reluctance motors. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Disturbance rejection

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Learning to Branch in Combinatorial Optimization with Hybrid Convolutional and Attentional Graph Neural Networks

Learning to Branch in Combinatorial Optimization with Hybrid...

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2024 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2024

作者： Zhang, Xilin Gu, Shenshen School of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9798331504755

Solving combinatorial optimization problems holds significant practical importance, and many such problems can be transformed into MILP problems. Currently, Branch-and-Bound (B&B) is a typical method for solving Mixed-Integer Linear Programming (MILP) problems. In this paper, we propose a hybrid convolutional and attentional graph neural network to learn the variable selection policy in B&B. The model combines graph convolutional and graph attention mechanisms, achieving more efficient node embeddings and reducing computational time. The mathematical model of MILP is transformed into a bipartite graph structure, which effectively extracts features. The B&B solving process is mapped to a Markov decision process, and imitation learning is used to train the model. By solving a series of combinatorial optimization problems that can be transformed into MILP problems, we validate that our model can improve B&B. Experimental results show that our model outperforms state-of-the-art branching machine learning methods and generalizes to problems of different scales. © 2024 IEEE.

关键词： Mixed-integer linear programming

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Mixed Network Based on Feature Modulation and Parameter-Free Attention for Efficient Image Super-Resolution 8th

Mixed Network Based on Feature Modulation and Parameter-Fr...

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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： Qin, Yujie Li, Xin School of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9789819601875

In recent years, single image super-resolution (SISR) based on deep learning algorithms has received more attention from the research community. There are many ways to solve this task. The SR method based on convolutional neural network (CNN) is mainly effective in restoring high-frequency details, but often ignores the key low-frequency contour information. Transformer-based SR methods, although including global structural details, usually come with a large number of parameters, resulting in high computational overhead. In this paper, we propose a network that combines convolutional feature modulation with parameter-free attention to achieve lightweight image super-resolution. First, a multi-receptive field hybrid convolution module (MRHC) is used, which can capture multi-scale features and expand the receptive field. Secondly, we use feature shift mixer (FSM) to fuse features, and introduce a parameter-free attention mechanism. We use the origin symmetric activation function to directly generate weights, which greatly reduces the amount of calculation and parameters. Finally, we use convolutional channel mixer (CCM). The CCM is used to interact with channel information and achieve overall fusion of spatial features and channel information. Experimental results show that this lightweight model achieves good results for SR tasks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Mixers (machinery)

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Flexible, Breathable and Sweatproof Piezoelectric Sensors Based on Additive Manufacturing 6

Flexible, Breathable and Sweatproof Piezoelectric Sensors Ba...

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6th International Conference on Electronic Engineering and Informatics, EEI 2024

作者： Yang, Zhiqiang Guo, Zilong Lan, Weixia Liu, Yuanyuan School of Mechatronics Engineering and Automation Shanghai University Shanghai China

ISBN: (纸本)9798350353594

Flexible piezoelectric sensors have widespread applications in the field of wearable devices and human-machine interaction technologies. However, the manufacturing of these sensors mostly relies on manual assembly, lacking efficient manufacturing processes. In this paper, the 'one-step' fabrication of flexible piezoelectric sensors is achieved with a self-developed multi-component additive manufacturing composite system The sensor was designed with the electrospun PVDF functional layer, printed Ag electrode layer, and electrospun TPU encapsulation layer. The produced sensors exhibit a sensitivity of 0.04 V/N, a rapid response time of 25 ms, good breathability (600g/m2/day), and excellent sweat resistance. This method offers a promising approach for the efficient manufacturing of breathable and sweatproof flexible piezoelectric sensors. © 2024 IEEE.

关键词： Piezoelectric transducers

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