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Design and measurement of three-dimensional uniform-field coils based on swarm intelligence algorithms under ferromagnetic boundaries

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MEASUREMENT 2024年 233卷

作者： Wang, Kun Ma, Danyue Gao, Yanan Dou, Yao Li, Siran Wang, Jing Sun, Jinji Beihang Univ Inst Large Scale Sci Facil Ctr Zero Magnet Field Sci Beijing 100191 Peoples R China Natl Inst Extremely Weak Magnet Field Infrastruct Hangzhou 310000 Peoples R China Hefei Natl Lab Hefei 230088 Peoples R China China Acad Space Technol Beijing 100094 Peoples R China Beijing Inst Elect Syst Engn Beijing 100074 Peoples R China

Combination systems of high permeability magnetic shields and coils are widely used in fields such as the magnetic field standard metrology and the zero magnetic room construction. To solve the problem that the magnetic field of uniform -field coils under the ferromagnetic boundary of magnetic shields is difficult to design precisely and the uniformity is difficult to improve, three-dimensional uniform field coils are designed based on the magnetic field model of coils under the ferromagnetic boundary using the target -field method (TFM), and the weight coefficient vectors determining the coils ' structure are optimized using intelligent optimization algorithms, which improves the uniformity of the magnetic field in the target region by 2 orders of magnitude through whale optimization algorithm (WOA). Then, the radial WOA-TFMUFY coil and the axial WOA-TFMUFZ coil are designed considering sidewall optical holes, and their magnetic field distribution is analyzed and verified under different permeabilities and axial opening sizes of the shield. Compared to the traditional saddle coil and Lee -whiting coil, the maximum magnetic field non -uniformity in the target uniform field region is reduced by 82.2 % and 92.8 % for the WOA-TFMUFY coil and WOA-TFMUFZ coil. The maximum relative errors between the measured magnetic field generated by the designed coils and the finite element method (FEM) simulation results are no higher than 2.2%. This novel method can provide more precise and uniform magnetic field metrology standard elements.

关键词： Target field method Ferromagnetic boundaries Uniform-field coil optimization algorithm Magnetic field measurement

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A condition fitting method of temperature field for tunnel structure based on test measurements

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TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY 2024年 144卷

作者： Wang, Linxi Shen, Yi Yan, Zhiguo Tongji Univ State Key Lab Disaster Reduct Civil Engn 1239 Siping Rd Shanghai 200092 Peoples R China Tongji Univ Dept Geotech Engn 1239 Siping Rd Shanghai 200092 Peoples R China

Accurate temperature distribution of the tunnel lining under a fire scenario is crucial for conducting reliable thermal-mechanical investigations, as it directly impacts thermal stress and property degradation. In this regard, achieving consistency between simulation and actual response is imperative. However, the precision of most simulated temperature fields is hindered by a phenomenon known as the 'temperature platform', which occurs around the vaporization point of water. To this end, a Condition Fitting Method (CFM) is proposed in this paper. In CFM, optimal parameters are adjusted based on local historical measurements, enabling the acquisition of a detailed temperature field for the entire tunnel structure in real-time or even forward time step. Based on a preliminary segment fire test, the implementation of CFM successfully captures the temporal characteristics of the temperature platform on certain survey points. The results of both the current and forward time steps obtained from CFM demonstrate close agreement with the reference measurements obtained from the fire test, indicating consistency throughout the entire process. The maximum average error of the calculation result on survey points is 50.4 degrees C while the value for prediction result is 65.3 degrees C. For further investigation, a parametric study is conducted to identify the most crucial parameters. Additionally, numerical verification is performed to assess the feasibility of the proposed method and to compare the efficiency of different optimal algorithms. The results indicate that the proposed method has overcome the drawback of conventional simulation method that the temperature deviate from actual values at early stage. This achievement ensures that the proposed method provides a reliable temperature field for further investigations.

关键词： Tunnel structure Temperature distribution Fire test Numerical validation optimization algorithm

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Intra City Transport On-demand

Intra City Transport On-demand

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IFAC Workshop on Control for Smart Cities (CSC)

作者： Netov, Nikolay Spassov, Kamen Sofia Univ St Kliment Ohridski Sofia 1113 Bulgaria

An algorithm to calculate optimal trajectories of e-buses to fulfil on-demand requests for transportation in a smart city environment is presented. Instead of solving the transportation problem once when all transportation requests are registered, we solve the transportation problem at any virtual or public station during the taxi. This approach enables gathering transportation requests dynamically and also consider changes in the environment (e.g. weather conditions, roadblocks, traffic jams, etc) during the transportation. The algorithm is tested with real data. Some results of the simulation are presented. Copyright (C) 2022 The Authors.

关键词： Transport on demand Optimal route Transportation problem optimization algorithm Model Simulation Green city Smart city Optimal control

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A Flexible Control Strategy Model for Energy Storage System 4

A Flexible Control Strategy Model for Energy Storage System

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4th Asia Energy and Electrical Engineering Symposium (AEEES)

作者： Zhang, Shaohua Zhang, Rong Wei, Xin Wang, Yunshan Cai, Zhi Kang, Rong China EPPEI Smart Energy Co Ltd Beijing Peoples R China Xian FPA Energy Technol Co Ltd Xian Peoples R China China Elect Power Res Inst Beijing Peoples R China

ISBN: (纸本)9781665479141

As the share of wind power participating in the electricity market grows, it is becoming increasingly important to control energy storage systems in order to increase the profitability of wind farms. This paper presents a flexible control model of energy storage system that may be utilized to assist wind farms in controlling energy storage system efficiently in real time, hence improving wind farm controllability and economic benefits. Based on the rolling forecast of ultra-short-term power and real-time electricity prices, the model in this paper can adjust the control strategy of the energy storage system in real time according to actual application scenarios, so as to help wind farms avoid deviation recovery losses and obtain excess profits as much as possible. To begin, a constrained optimization model of an energy storage system is established with the maximization of income generated by energy storage system as the objective function. Then, the CPLEX solver is used to solve the constrained optimization problem. Finally, data from a wind farm in Shanxi Province is used to verify the model proposed in this paper, and the result indicates the reliability and effectiveness of the model.

关键词： energy storage system flexible control strategy optimization algorithm wind power

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Review on optimization algorithms for plug in hybrid electric vehicle 19

Review on optimization algorithms for plug in hybrid electri...

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19th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)

作者： Ben Ali, Marwa Elloumi, Mariem Boukettaya, Ghada Univ Sfax Natl Sch Engn Dept Elect Engn Sfax 3038 Tunisia

ISBN: (纸本)9781728112923

In this study, Vehicle to grid (V2G) application is considered as an important solution to minimize the CO2 emission, as well as its ability to involve the utilization of renewable energy and recovers the limitation of fossil energy. In this context, the plug in hybrid electric vehicle (PHEV) have attracted the attention of researchers and industries due to its various advantages especially it's utilization as a good interface on the V2G application all over the world. This paper includes an introduction of various vehicle architecture and the formulation of total cost of ownership (TCO) presented during the owning period of the vehicle. We are also interested on the different approaches and algorithms used for optimal design of PHEV in literature to optimize the TCO.

关键词： V2G application Plug in hybrid electric vehicle optimization algorithm Total cost of ownership

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A review of hierarchical energy management system in networked microgrids for optimal inter-microgrid power exchange

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ELECTRIC POWER SYSTEMS RESEARCH 2024年 231卷

作者： Yassim, Halyani Mohd Abdullah, Mohd Noor Gan, Chin Kim Ahmed, Asif Univ Teknikal Malaysia Melaka Fac Elect Engn Durian Tunggal 76100 Melaka Malaysia Univ Tun Hussein Onn Malaysia Fac Elect & Elect Engn Green & Sustainable Energy GSEnergy Focus Grp Batu Pahat 86400 Johor Malaysia

A networked microgrid (NMG) is a novel cyber-physical system that provides power to urban and rural communities. The benefits of NMG that coupled with hierarchical energy management system (EMS) include increased renewable energy utilization, reliability, system efficiency, and flexibility in inter-microgrid (MG) power exchange (PX). Nevertheless, achieving secure and optimal NMG operation would require hierarchical EMS strategies that can manage uncertainties such as renewable generation fluctuations, load variation, energy prices, and flexible bidirectional PX. This paper outlines the NMG concept and various power balance methods. Subsequently, a comprehensive review of hierarchical EMS designs for NMG is presented. Four NMG models are introduced, and a comparison of various EMS strategies based on objectives, constraints, and optimization methods is also elaborated. Additionally, this paper addresses flexible bidirectional power flow between multiple MGs and the utility grid (UG) within three PX scenarios (MG -to -MG, MG-to-UG, and UG-to-MG). The advantages and challenges of hierarchical EMS for NMG with bidirectional power flow are also discussed considering grid stability, economic viability, and environmental impact. Finally, future research directions for enhancing the NMG model for optimal inter-MG PX are established. It highlights the efficient hierarchical EMS strategies and optimization algorithms for more reliable, affordable, and sustainable NMG operation.

关键词： Distributed energy resources Energy management system Networked microgrid operation optimization algorithm Power exchange

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Parametric study and optimization of the cryo-magnetic system for EU DEMO at the pre-conceptual design phase

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CRYOGENICS 2022年 124卷 1页

作者： Hoa, Christine Latella, Thomas Bonne, Francois Lacroix, Benoit Le Coz, Quentin Zani, Louis Lewandowska, Monika Sedlak, Kamil Corato, Valentina Univ Grenoble Alpes CEA IRIG SBT F-38000 Grenoble France CEA IRFM F-13018 St Paul Les Durance France West Pomeranian Univ Technol Fac Mech Engn & Mechatron Szczecin Poland Ecole Polytech Fed Lausanne Swiss Plasma Ctr SPC Forschungsstr 111 CH-5232 Villigen Switzerland ENEA ENEA CR Frascati I-00044 Frascati Rome Italy

The pre-conceptual design phase of the EU DEMO magnet system relies on mechanical, electromagnetic and thermal-hydraulic analyses of different conductor designs for the Toroidal Field (TF) coils, the Poloidal Field (PF) coils and the Central Solenoid (CS) magnet. The cryo-magnetic system includes the superconducting magnets cooled by forced flow of supercritical helium at about 4.5 K, the cryo-distribution lines and valve boxes, and the cryogenic system with several cold boxes. The present analysis focuses on the cooling requirement of the TF coils with three winding pack options for the cable in conduit conductors based on 2015 DEMO baseline, featuring pancake or layer winding approaches. This analysis methodology would be further developed with the latest conductor designs and more complete heat load assumptions for the future conductor design studies and the specification of the cooling requirements. Parametric studies on the cold source temperature and on the supercritical helium mass flow rate have been performed on the three conductor designs in order to identify for each one the impact of the cooling conditions onto the temperature margin with respect to the current sharing temperature. In this study, the heat load contribution have been limited to the estimation of the neutron heating and some joint resistance heat loads when available. In addition, Simcryogenics, a dynamic modelling tool developed by CEA, is used to model supercritical helium loops for cooling different conductor designs. An algorithm has been developed to optimize both the cold source temperature and the supercritical helium mass flow, in order to minimize refrigeration power for each conductor design. optimization studies are analyzed and compared in order to estimate for each TF winding pack design, the impact on refrigeration power. The interest of such quick cross-check analyses is to identify design improvements for the conductors and the cryodistribution, keeping acceptable temperatu

关键词： Fusion EU DEMO Cryo-magnetic system Dynamic modelling optimization algorithm

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Mechanical Behavior Monitoring and Load Inversion Analysis of Large-Diameter Underwater Shield Tunnel during Construction

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SENSORS 2024年第4期24卷 1310页

作者： Ma, Si-Yuan Ye, Xiao-Wei Liu, Zhi-Xiong Ding, Yang Zhang, Di Sun, Feng Zhejiang Univ Dept Civil Engn Hangzhou 310058 Peoples R China Hangzhou City Univ Dept Civil Engn Hangzhou 310015 Peoples R China China Railway Siyuan Survey & Design Grp Co Ltd Wuhan 430063 Peoples R China

The construction of large-diameter shield tunnels underwater involves complex variations in water and earth load outside the tunnel segment, as well as intricate mechanical responses. This study analyzes the variation laws of external loads, axial forces, and bending moments acting on the segment ring during the shield assembly and removal from the shield tail. It accomplishes this through the establishment of an on-site monitoring system based on the Internet of Things (IoT) and proposes a Bayesian-genetic algorithm model to estimate the water and earth pressure. The fluctuation section exhibits a peak load twice as high as that in the stable section. These variations are influenced by Jack thrust, shield shell force, and grouting pressure. The peak load observed in the fluctuation section is twice as high as the load observed in the stable section. During the shield tail removal process, the internal forces undergo significant fluctuations due to changes in both load and boundary conditions, and the peak value of the axial force during the fluctuation section is eight times higher than that during the stable section, while the peak value of the bending moment during the fluctuation section is five times higher than that during the stable section. The earth and water pressure calculated using the inversion analysis method, which relies on the measured internal forces, closely matches the actual measured values. The results demonstrate that the accuracy of the water and earth pressure obtained through inversion analysis is twice as high as that obtained using the full coverage pressure method. These results can serve as a valuable reference for similar projects.

关键词： Structural Health Monitoring shield tunnel Fiber Bragg grating inversion analysis Parameter estimation optimization algorithm

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A novel reinforcement learning based Heap-based optimizer

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KNOWLEDGE-BASED SYSTEMS 2024年 296卷

作者： Ma, Xuesen Zhong, Zhineng Li, Yangyu Li, Dacheng Qiao, Yan Hefei Univ Technol Sch Comp Sci & Informat Engn Hefei Peoples R China Intelligent Mfg Inst HFUT Hefei Peoples R China Chinese Acad Sci Hefei Inst Phys Sci Hefei Peoples R China

The Heap-Based optimization (HBO), a novel meta-heuristic algorithm, constructs a hierarchical heap resembling a company structure to facilitate interaction among search agents. This enables the search agent to learn various levels of information from the population to obtain improved solutions, but it has drawbacks such as limited search capability and slow convergence speed when tackling complex optimization problems. To address these challenges, we propose an enhanced heap optimizer based on reinforcement learning(RLHBO), which demonstrates robust stability, rapid convergence, and high solution accuracy. Firstly, fixed operators are replaced with a reinforcement learning dynamic control search strategy in RLHBO to regulate the search range of agents. This prevents agents from being restricted in their search when encountering local or global optima, thus enhancing their search capability. Additionally, RLHBO introduces a dimensional selflearning strategy and a convergence strategy based on search direction similarity to address issues such as invalid and discrete solutions, accelerating convergence. Furthermore, an initialization strategy based on quasi-oppositional learning is employed to increase the diversity of the algorithm-generated population, surpassing the limitations of random initialization and further boosting convergence speed. Extensive testing on various complex functions from CEC2017 and CEC2022 demonstrates that RLHBO, as presented in this paper, outperforms HBO and numerous other advanced MAs in terms of search capability and convergence speed.

关键词： Meta-heuristic algorithm optimization algorithm Heap-based optimizer Reinforcement learning

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End-to-end inverse modeling and optimization for filters based on artificial neural network

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INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING 2022年第11期32卷 e23365-e23365页

作者： Huang, Hao Liang, Xiuye Guan, Fang Zi, Jian Fudan Univ Inst Nanoelect Devices & Quantum Comp State Key Lab Surface Phys Shanghai 200433 Peoples R China Fudan Univ Dept Phys State Key Lab Surface Phys Shanghai Peoples R China Fudan Univ Zhangjiang Fudan Int Innovat Ctr Shanghai Peoples R China

In this letter, we propose an end-to-end inverse modeling and optimization method for microwave filter designs based on the data-augmentation learning strategy. Because of the non-uniqueness of solutions, it is difficult to achieve good convergence with artificial neural networks for inverse designs when the parameter space is very large. We prove that the accuracy of inverse predictions can be significantly improved using the network's self-generated data and the optimization can be greatly accelerated with the help of the inverse network. The predicted structural parameters can be used as initial values for optimization, which reduces the number of iterations and avoids falling into local optima. This method is applied to designs of fourth-order interdigital cavity filters. The measurement and simulation agree well.

关键词： artificial neural network microwave filter optimization algorithm

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