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3rd International conference on Energy, Power and Electrical Engineering, EPEE 2023

作者： Wu, Qiaofeng Liu, Zhaoyu Zhang, Manying Shao, Lanxin Sun, Yikai Economic Research Institute of State Grid Zhejiang Electric Power Co. Ltd Hangzhou China College of Electrical Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9798350318180

With the continuous development of microgrids, multiple microgrids in certain regions integrate and form multi-agent microgrids (MAMG) systems, which is beneficial to coordinated control, operational stability, and economy. Compared with a single microgrid, the MAMG system features multiple stakeholders. Besides, the energy dispatching centre must optimize operation plans through coordinating the interests of all parties. Considering the randomness of renewable energy output, this paper describes the uncertainty by chance-constrained programming. This paper established a two-level hierarchical optimization scheduling framework for the MAMG system. The upper level is an optimization scheduling model for the active distribution network (ADN) dispatching centre, and the lower level is an optimization scheduling model for each microgrid. Then, a new collaborative optimization method called the analytical target cascading (ATC) method is adopted to realize the independent optimization after decoupling the upper and lower models. Numerical examples show that the hierarchical distributed optimization algorithm based on ATC features rapidity and good convergence. © 2023 IEEE.

关键词： active distribution network analytical target cascading economic optimal dispatch multi-agent microgrids

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An efficient model for capturing gas transients in the energy flow of integrated electricity-gas systems

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ENERGY REPORTS 2023年 9卷 127-136页

作者： Du, Hui Lin, Tao Li, Qingyan Fu, Xiyue Xu, Xialing Wuhan Univ Sch Elect Engn & Automat Hubei Engn & Technol Res Ctr AC DC Intelligent Distribut Network 8 Donghu South Rd Wuhan 430072 Peoples R China Cent China Branch State Grid Cooperat China 225 Xudong Rd Wuhan 430077 Peoples R China

Gas-fired units provide great flexibility to accommodate the intermittent nature of renewable energy sources and are also considered to be an ideal substitute for retiring coal-fired generations. However, the increasing deployment of gas-fired units deepens interdependency between electric power and natural gas, calling for efficient modeling of the heterogeneous energy flow in the integrated electricity-gas systems (IEGS). Plenty of research works show the necessity of considering gas flow transients in the IEGS, which can be described by a set of partial differential equations (PDEs). To ensure a tractable optimization, the PDEs are often discretized using the finite/infinite difference method, which may result in a large computational scale for achieving good precision. To this end, this paper proposes an efficient model for capturing gas flow transients in the IEGS, which can be taken as the operational constraints in the optimal energy flow model for IEGS coordinated planning, scheduling, and control. For improving the computational efficiency, the PDE-based transient gas flow model is discretized using a space-time orthogonal collocation (OC) method, which provides high-quality results using fewer spatial-temporal discrete points than differential methods. Further, aiming at the difficulty in the determination of the number of space-time collocation points, an adaptive strategy is proposed and embedded in the proposed model utilizing the local fitting errors of state variables related to pipelines. Case studies show the superiority in computational accuracy and efficiency of the proposed model over the existing models based on Wendorff difference and global OC. And an illustrative case based on the modified IEGS benchmark system composed of the IEEE 118-bus power system and the Belgian 20-node gas network exhibits the application value of the proposed model in the optimization and control of the IEGS. (c) 2023 The Author(s). Published by Elsevier Ltd.

关键词： Energy internet Integrated electricity-gas system (IEGS) Transient gas pipe flow Space-time orthogonal collocation (OC) Partial differential equation (PDE)

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Multi-Time Scale Reactive Power and Voltage optimization control Based on Second-Order Cone Programming 3

Multi-Time Scale Reactive Power and Voltage Optimization Con...

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3rd International conference on Mechatronics and Automation Technology, ICMAT 2024

作者： Wang, Huanyou Xie, Guangqi School of Mechanical and Electrical Engineering Guangdong University of Science and Technology Dongguan523668 China Academy of Electronic Information and Electrical Engineering Xiangnan University Chenzhou423000 China Academy of Electronic Information and Electrical Engineering Xiangnan University China

ISBN: (纸本)9781643685649

With the large-scale integration of distributed generations (DGs) such as photovoltaics (PVs) and wind turbines (WTs) into the distribution network (DN), problems such as increased network loss, increased voltage offset, and voltage exceeding limit have arisen. This article establishes a dynamic reactive power optimization multi-objective model for active and reactive power coordination in DN, which includes various active management devices such as energy storage system, DGs, capacitor banks (CBs), and static var generations (SVGs). Through linearization and convex relaxation processing, transforming the original non convex nonlinear optimization model into an effectively solvable second-order cone programming (SOCP) model. The IEEE33 node system was used for numerical analysis to verify the optimization stability and computational efficiency of the proposed method. © 2024 The Authors.

关键词： Second-order cone programming

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Performance Evaluation of First Hop Redundancy Protocols in IPv4 and IPv6 networks 3

Performance Evaluation of First Hop Redundancy Protocols in ...

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3rd IEEE International Maghreb Meeting of the conference on Sciences and Techniques of Automatic control and Computer Engineering, MI-STA 2023

作者： Saud, Najia Ben Mansour, Mahmud University of Tripoli Department of Network Tripoli Libya

ISBN: (纸本)9798350319897

To enhance IP network availability, First Hop Redundancy Protocol (FHRP) is a necessary tool that used to achieve this goal. FHRPs are group of protocols that used to manage and maintain network first hop router (i.e. default router) failure. This work compares and evaluates different FHRPs which are Hot Standby Router Protocol (HSRP), Virtual Router Redundancy Protocol (VRRP), and Gateway Load Balancing (GLBP), in both IPv4 and IPv6 networks. The comparison among the three mentioned protocol was accomplished based on convergence time, packet loss and CPU utilization, after implementation, testing and optimization. GNS3 emulation tool was used. The comparison results highlights which protocol performed the best in each scenario and which protocol can be considered as the best among the three FHRPs. © 2023 IEEE.

关键词： Redundancy

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Resonant wireless charging scheme

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ENERGY REPORTS 2023年 9卷 612-621页

作者： Guo, Xing Qi, Yongsheng Liu, Liqiang Jia, Shunyu Mi, Lijun Inner Mongolia Key Lab Elect & Mech Control Hohhot 010051 Peoples R China Inner Mongolia EHV Power Supply Co Hohhot 010080 Peoples R China Inner Mongolia Univ Technol Inst Elect Power Hohhot 010080 Peoples R China

In order to reduce the number of switching devices and passive components in the hybrid topology charging system based on resonant power transmission technology, and simplify the control strategy of primary and secondary sides, a hybrid self switching resonant topology based on LCL-LCL/S is proposed. The structure does not need primary and secondary side communication and adds any passive components, and only changes the topology network through the self switching operation of LCL structure can be realized constant current and constant voltage switching of wireless charging system. Then, according to the characteristics of battery charging curve, resonant current threshold and voltage jump threshold, a parameter optimization design method for hybrid resonant topology network is proposed, which can avoid the parameter uncertainty caused by the limitation of empirical selection of resonant network parameters, and provide theoretical basis for parameter selection. In the constant current and constant voltage mode, the input impedance is pure resistance, and the zero phase angle(ZPA) is between the input current and the voltage. The experimental results show that the hybrid self switching wireless charging system with optimized resonant network parameters has better constant current and constant voltage output characteristics. The system realizes ZPA and constant frequency soft switching characteristics, which meets the requirements of constant current and constant voltage charging. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Magnetically coupled resonant wireless power transfer(MCR-WPT) Hybrid topology Parameter design ZPA

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A Multi-Scenario optimization Scheduling Strategy of Active Distribution networks Considering Source-Load-Storage Coordination 3

A Multi-Scenario Optimization Scheduling Strategy of Active ...

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3rd International conference on New Energy and Power Engineering, ICNEPE 2023

作者： Li, Chaoran Cui, Jia Yan, Zhenhong Chu, Tianfeng Wang, Shunjiang Zhang, Ximing Li, Yuanzhong Shenyang University of Technology School of Electrical Engineering Liaoning Shenyang China Electric Power Research Institute of State Grid Liaoning Electric Power Co Liaoning Shenyang China

ISBN: (纸本)9798350393224

The use of new energy power reduces the operating cost of the power grid. The optimal dispatching of active distribution network is proposed considering source-load uncertainty and source-load-storage coordination. Firstly, a multi-scenario optimal scheduling model of active distribution network considering source-charge-storage coordination is established in this paper. Secondly, fully considering the source load storage coordination reduces the operating cost of the distribution network and the fluctuation degree of the output of adjustable resources. Thirdly, the multi-scenario optimization is considered as the two-sided uncertainty of the source load. Finally, numerical examples show that the proposed algorithm outperforms existing algorithms in source-load-storage coordination. © 2023 IEEE.

关键词： active distribution network demand side response distributed power generation parallel genetic membrane algorithm

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Research on Battery Energy control Strategy Based on Neural network 3

Research on Battery Energy Control Strategy Based on Neural ...

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3rd IEEE International conference on Mobile networks and Wireless Communications, ICMNWC 2023

作者： Liu, Xianghao Li, Jinsong Wang, Yi Hainan University Hainan Haikou China China Automotive Engineering Research Institute Chongqing China

ISBN: (纸本)9798350317022

With the development of science and technology, battery energy plays an increasingly important role in modern society. The role of battery energy includes but is not limited to providing power for mobile devices and powering cars. It is also the main energy source for new energy vehicles. Energy storage systems provide energy storage. It provides power for aerospace and can also be used as a backup power supply for households and industries to deal with sudden power outages and other situations. Neural networks are also widely used in battery energy. For example, neural networks can be used to predict the remaining service life of lithium-ion batteries. This paper takes the commonly used 18650 power lithium battery as the main research object, and proposes a neural network battery state of charge (SOC) estimation method based on the LEVY flight step-based group search optimization algorithm (LEVY-GSO-BP). The group search optimization algorithm after Levy flight step optimization is used to optimize the design of the established SOC neural network model to improve the accuracy of the neural network's estimation of SOC related parameters. BP neural network is a powerful optimization algorithm that can solve unimodal function and multimodal function optimization problems of high-dimensional data. It has the advantages of simplicity, efficiency and accuracy, so it is widely used in various problems. However, the calculation of BP neural network is more difficult, takes a long time, and the convergence speed drops significantly at the end of the calculation, and may even stagnate. In order to solve these problems, we propose an algorithm improvement method based on Levy flight step size. Levy flight is an optimization algorithm with excellent global search capabilities that can find the optimal solution in a short time. It uses a combination of short-distance frequent search and occasional jumping long-distance search to improve local search capabilities and global sear

关键词： Battery SOC BP Neural network Group Search optimization Algorithm Lithium-Ion Battery

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A Novel Approach on Parkinson Detection with Deep Ensemble network 3

A Novel Approach on Parkinson Detection with Deep Ensemble N...

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3rd IEEE International conference on Intelligent Techniques in control, optimization and Signal Processing, INCOS 2024

作者： Sivaprakasam, Anantha Senthil Pandi, S. Varsha, S.P. Vishnu, M. Sharath, J. Rajalakshmi Engineering College Department of Cse Chennai India

ISBN: (纸本)9798350361186

Parkinson Disease (PD) is one of the serious and life- threatening disease treated by doctors with various progressive diagnosis. Magnetic resonance imaging (MRI) plays a significant role in treating the disease in the early stages. Although various screening techniques are utilized for PD, MRI technique provides accurate extraction of Parkinson features impacting the disease. The emerging growth of artificial intelligence frameworks in recent days create a strong foundation in medical image processing and critical disease inference. The presented system formulated with such framework using an ensemble approach. The MARI images are collected from UCI repository. The involvement of image processing technology and deep learning, deep ensemble network (DEN) is developed here. The primary goal of the system is to detect the presence of Parkinson disease in the early stages. The proposed approach is created with deep ensemble process with Convolutional Neural network (CNN) and Long-Short Term Memory model (LSTM) with ADAM optimizer. The performance of the system is evaluated using accuracy, precision, recall and F1score. Through DEN model, accuracy of 98% is achieved. The quantitative parameters are compared with the existing state of art approaches. © 2024 IEEE.

关键词： Magnetic resonance imaging

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The flexible resource optimization scheduling considering the substation of the distribution network and the classification characteristics of electric vehicles 3

The flexible resource optimization scheduling considering th...

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3rd International conference on Energy, Power and Electrical Technology, ICEPET 2024

作者： Luo, Busheng Lin, Zhichao Zhou, Haohan Guangdong Power Grid Co. Ltd. Huizhou Power Supply Bureau Guangdong Province Huizhou516000 China Beijing Kedong Electric Power Control System Co. Ltd Haidian District Beijing100089 China

ISBN: (纸本)9798350352658

Aiming at the deepening differentiation of distribution network areas and the flexible changes of electric vehicle resources, a flexible resource scheduling model considering the functional partitioning of active distribution networks and the classification characteristics of EVs is proposed. Firstly, an EV classification initialization model is established, categorizing charging periods and durations for private cars, taxis, and buses as examples. The EV charging and discharging are guided by congestion and willingness indices, and a regional controllable load model is built. Secondly, a spatiotemporal hierarchical scheduling model for the distribution network is constructed to minimize user costs and integrate renewable energy sources while scheduling flexible resources. At the lower level, an economic dispatch of EV charging and discharging locations and controllable loads in different areas is conducted. Finally, using the IEEE 33-node system as an example, simulations demonstrate that the proposed method can optimize the charging and discharging modes of various types of electric vehicles, thereby validating the effectiveness and rationality of the proposed approach. © 2024 IEEE.

关键词： Power distribution networks

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Model optimization Methods for Real-time 2D Human Pose Estimation Applied to Robots: A Survey 3

Model Optimization Methods for Real-time 2D Human Pose Estim...

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3rd International conference on Robotics, Automation and Intelligent control, ICRAIC 2023

作者： He, Weiting Zeng, Bi Liu, Jianqi Ye, Xiaoying Zhou, Fuken Neusoft Institute Guangdong School of Computers Foshan China Guangdong University of Technology School of Computers Guangzhou China Guangdong University of Technology School of Automation Guangzhou China

ISBN: (纸本)9798350360813

With the development of technology, there are more and more robots around us. These robots need to recognize human pose to monitor people or interact with people, so the human pose estimation model is required to be deployed on robots to achieve these functions. Human pose estimation involves the processing of more than a dozen joints, so the human pose estimation model usually has a relatively large amount of calculation resulting in a relatively slow detection speed. Transferring these large amounts of image data to cloud servers for human pose estimation detection will consume a lot of network resources and detection time will be delayed. And the robot's local computing power is limited. So it is difficult to deploy both human pose estimation algorithm models and other complex algorithm models locally on robots. This requires various algorithms running locally on the robot to consume as little computing resources and real-time as possible. This paper studies the optimization methods of real-time 2D human pose estimation models studies in recent years, which are divided into three aspects: the optimization of the feature extraction network, the optimization of the joint point detection and the optimization of the joint point connection. And summarized the advantages and disadvantages of these optimization methods, attempting to apply them to robots. © 2023 IEEE.

关键词： Robots

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