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Dynamic Characteristic Analysis of a Toothed Electromagnetic Spring Based on the Improved Bouc-Wen Model

MATERIALS 2023年第13期16卷 4889页

作者： Zheng, Xiaoyuan Zhang, Cheng Lou, Yifang Xue, Guangming Bai, Hongbai Fuzhou Univ Coll Mech Engn & Automat Fuzhou 350116 Peoples R China Fuzhou Univ Met Rubber Engn Res Ctr Fuzhou 350116 Peoples R China

Electromagnetic spring active isolators have attracted extensive attention in recent years. The standard Bouc-Wen model is widely used to describe hysteretic behavior but cannot accurately describe asymmetric behavior. The standard Bouc-Wen model is improved to better describe the dynamic characteristic of a toothed electromagnetic spring. The hysteresis model of toothed electromagnetic spring is established by adding mass, damping, and asymmetric correction terms with direction. Subsequently, the particle swarm optimization algorithm is used to identify the parameters of the established model, and the results are compared with those obtained from the experiment. The results show that the current has a significant impact on the dynamic curve. When the current increases from 0.5 A to 2.0 A, the electromagnetic force sharply increases from 49 N to 534 N. Under different excitations and currents, the residual points predicted by the model proposed in this work fall basically in the horizontal band region of -20-20 N (for an applied current of 1.0 A) and -40-80 N (for an application of 4.5 mm/s). Furthermore, the maximum relative error of the model is 12.75%. The R-2 of the model is higher than 0.98 and the highest value is 0.9993, proving the accuracy of the established model.

关键词： electromagnetic spring dynamic characteristic Bouc-Wen model particle swarm algorithm experiment

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Analysis of OLED glass substrate heated by heating tube array based on multiple optimization algorithms

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THERMAL SCIENCE AND ENGINEERING PROGRESS 2024年 56卷

作者： Wang, Yiyi Xu, Chang Cai, Huikun Peking Univ Sch Engn Beijing 100871 Peoples R China Xiamen Univ Pen Tung Sah Inst Micronano Sci & Technol Xiamen 361102 Fujian Peoples R China

The temperature uniformity of OLED glass substrate during heat treatment is a key factor affecting the quality of its imaging display. This paper constructs the heating process model of OLED glass substrate based on heating tube array according to the actual scene, studies the thermal characteristics of OLED glass substrate, and then optimizes the temperature uniformity of glass substrate under isometric heating mode based on genetic algorithm, particle swarm optimization algorithm and simulated annealing algorithm. Compared with the initial solution of the algorithm, the optimization rates of the three algorithms respectively reach 75.5%, 86.4% and 98.3%, and the temperature differences are reduced to 3.82 degrees C, 1.44 degrees C and 0.30 degrees C. Finally, an experimental platform is built to verify the optimization results of different algorithms. The absolute errors are 0.58 degrees C, 1.46 degrees C, 1.30 degrees C respectively, all lower than 1.5 degrees C, which is within the allowable range of process requirements. It is proved that the proposed optimization algorithm control mode can reduce the heating temperature difference of glass substrate to the ideal level based on the heating device with low cost and simple structure. This scheme provides some reference for the formulation of temperature distribution solution in heat pipe heating technology.

关键词： OLED glass substrate Genetic algorithm particle swarm algorithm Simulated annealing algorithm Heating tube

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A Two-Stage Optimal Preventive Control Model Incorporating Transient Stability Constraints in the Presence of Multi-Resource Uncertainties

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PROCESSES 2023年第8期11卷

作者： Ni, Qiulong Sun, Jingliao Zha, Xianyu Zhou, Taibin Sun, Zelun Zhao, Ming State Grid Zhejiang Elect Power Co Ltd Hangzhou 310000 Peoples R China State Grid Wenzhou Elect Power Supply Co Wenzhou 325000 Peoples R China NARI Grp Corp State Grid Elect Power Res Inst Nanjing 210000 Peoples R China

The volatility and uncertainty introduced by increasingly integrated renewable energy pose challenges to the reliable and stable operation of the power system. To mitigate the operation risks, a two-stage optimal preventive control model that incorporates transient stability constraints and considers uncertainties from multiple resources is proposed. First, the uncertainties of different re-sources are modeled, with which the non-sequential Monte Carlo sampling method is used to correspondingly generate the scenarios. Thereafter, a two-stage control model that balances operational safety and economy and realizes preventive control and emergency control is built. The operation schedule from the preventive control stage aims to minimize the transient stability probability and operation costs. If any faults destabilize the system, the emergency control stage will be activated immediately to help the system recover stability with minimal control costs. To expedite the solving of the two-stage model, a multi-objective particle swarm algorithm based on entropy-TOPSIS is proposed. Finally, the effectiveness of the proposed model and solving algorithm are validated with the modified IEEE118 node system.

关键词： preventive control transient stability constraints multi-resource uncertainties two-stage model particle swarm algorithm

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Modeling and control method of combined heat and power plant with integrated hot water storage tank

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APPLIED THERMAL ENGINEERING 2023年 226卷

作者： Wang, Di Han, Xinrui Li, Haoyu Li, Xiaoli Northeast Elect Power Univ Sch Automat Engn Jilin Peoples R China Northeast Elect Power Univ Sch Energy & Power Engn Jilin Peoples R China Shenzhen Machinery Inst Architectural Design Co Lt Shenzhen Peoples R China

To enhance the flexibility of conventional power plants, a dynamic mathematical model of a combined heat and power unit is developed and verified in this study using field data, and the maximum relative error is less than 5%. Subsequently, the dynamic characteristics of the coal-fired power plant with the hot water storage tank are studied, and the temperature distribution curve inside the hot water storage tank is obtained. Finally, a new coordinated control system with an integrated hot water storage tank is designed. The new coordinated control system reduces the fluctuation in the heating load caused by the unit in the process of changing the load. The integral of absolute value of the error criterion and integral of time multiplied by the squared error criterion results for unit loads at different variable load rates are at least 200 and 50,000 lower compared to conventional control methods. This study provides a new solution to the problem that the current conventional turbine and boiler coordinated control system cannot address the difficulty of renewable energy power consumption, which is important for the safe and stable power grid operation after the large-scale grid connection of renewable energy power.

关键词： Mechanism model Combined heat and power unit Hot water storage tank Flexibility particle swarm algorithm

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Multi-objective reactive power optimisation approach for the isolated grid of new energy clusters connected to VSC-HVDC

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The Journal of Engineering 2017年第13期2017卷 1024-1028页

作者： Shengli Yin Linlin Wu Wei Song Xiao Wang North China Electric Power University China Lianchi District Baoding 071003 People's Republic of China Research Institute State Grid Jibei Electric Power Co. Ltd Xicheng District Beijing 100045 People's Republic of China

It is known that reactive power optimisation is of great significance to improve the electrical power quality. How the security, reliability, and economy of the system can be effectively improved by reactive power optimisation has attracted the attention of scholars. In this study, according to the characteristics of an isolated grid of the new energy clusters connected to voltage source converter-based high-voltage direct current, the multi-objective reactive power optimisation model, which takes the network loss, and the reactive power margin of new energy clusters into consideration, is established. In particular, the maximisation of reactive power margin of new energy clusters is chosen as one goal, thus the response speed of voltage control can be effectively improved, and the preventive control of transient voltage stability of new energy clusters will be realised. Afterwards, using the weighted method the multi-objective optimisation model can be transformed into a single-objective optimisation model and the particle swarm algorithm is utilised to obtain the optimal solution. Finally, the simulation results show that the reactive power optimisation approach proposed can effectively reduce the network loss of the system, increase the reactive power margin of the new energy clusters, and improve the quality of the system voltage.

关键词： reactive power control HVDC power convertors voltage control power grids power supply quality particle swarm optimisation power system stability power system transients energy clusters multiobjective optimisation model single-objective optimisation model reactive power margin multiobjective reactive power optimisation approach isolated grid electrical power quality multiobjective reactive power optimisation model VSC-HVDC voltage control transient voltage stability particle swarm algorithm

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Wind Farm Layout Design Using Cuckoo Search algorithms

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Applied Artificial Intelligence 2018年第9-10期32卷 956页

作者： Rehman, S Ali, S S Khan, S A Research Institute King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Center of Intelligent Signal & Imaging Research Universiti Teknologi PETRONAS Bandar Seri Iskandar Tronoh Malaysia Computer Science Department University of Pretoria Pretoria South Africa

Wind energy has emerged as a strong alternative to fossil fuels for power generation. To generate this energy, wind turbines are placed in a wind farm. The extraction of maximum energy from these wind farms requires optimal placement of wind turbines. Due to complex nature of micrositing of wind turbines, the wind farm layout design problem is considered a complex optimization problem. In the recent past, various techniques and algorithms have been developed for optimization of energy output from wind farms. The present study proposes an optimization approach based on the cuckoo search (CS) algorithm, which is relatively a recent technique. A variant of CS is also proposed that incorporates a heuristic-based seed solution for better performance. The proposed CS algorithms are compared with genetic and particle swarm optimization algorithms which have been extensively applied to wind farm layout design. Empirical results indicate that the proposed CS algorithms outperformed the genetic and particle swarm optimization algorithms for the given test scenarios in terms of yearly power output and efficiency.

关键词： Wind Energy Conversion Systems Wind algorithms maximum energy SEARCHING algorithm Energy output Wind farms particle swarm algorithm layout design Cuculidae Fossil Fuels

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Power system reactive power optimization based on MIPSO

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Energy Procedia 2012年 14卷 788-793页

作者： Li DingPing Shen GuoLiang Guo WenDong Zhang ZHi Hu BaoNing Gao Wei Wuzhong Electric Power Bureau Ningxia Electric Power CompanyWuzhong 751100China

In order to improve power quality and reduce network losses, this paper proposes a modified immune particle swarm algorithm for power system reactive power optimization. To overcome the disadvantages in the traditional PSO algorithm about low accuracy and easy to fall into local optimal, MIPSO adopts sinusoidal changing inertia weight strategy to make particles explore the local and global optimization more efficiently. Introduce convergence acceleration factor to improve the convergence rate. Modified immune principle enhances the search capability to avoid premature convergence. Finally, compare the reactive power optimization results of Wuzhong of Ningxia system by MIPSO with other classical PSO algorithms. The experimental results show that the MIPSO algorithm is an efficient and feasible approach for reactive power optimization.

关键词： reactive power optimization particle swarm algorithm sinusoidal changing inertia weight convergence acceleration factor modified immune

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A New algorithm for the Identification of CNC Geometric Errors

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Procedia CIRP 2016年 56卷 293-298页

作者： Min Wan Yang Liu Weihong Zhang School of Mechanical Engineering Northwestern Polytechnical University Xi’an Shaanxi 710072 China

This paper proposes a geometric error model for the three-axis machine tool using the homogeneous transformation matrix. An error-prediction model for the three-axis CNC machine tools is presented. This model takes the geometric errors into consideration, using the homogeneous coordinate transformation matrix(HTM) to analyze the geometric error model, which can change the tool's complex position and orientation changes in space into matrix calculations to make the model simpler and more intuitive. A simple method using the cubic polynomial functions to fit the geometric error components is proposed. Using this method, the high-order, non-linear spatial geometric problem can be transformed into algebraic equation. To large extent, the difficulty of calculation is reduced. The QC20 ball-bar is used to measure, analyze and separate all the geometric error components. A new kind of particle swarm algorithm based on the genetic algorithm is developed to solve the algebra equation.

关键词： HTM geometric error QC20 particle swarm algorithm

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Improved Metaheuristic Optimization algorithm Applied to Hydrogen Fuel Cell and Photovoltaic Cell Parameter Extraction

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ENERGIES 2021年第3期14卷

作者： Liu, En-Jui Hung, Yi-Hsuan Hong, Che-Wun Natl Tsing Hua Univ Dept Power Mech Engn Hsinchu 30013 Taiwan Natl Taiwan Normal Univ Undergrad Program Vehicle & Energy Engn Taipei 106 Taiwan

As carriers of green energy, proton exchange membrane fuel cells (PEMFCs) and photovoltaic (PV) cells are complex and nonlinear multivariate systems. For simulation analysis, optimization control, efficacy prediction, and fault diagnosis, it is crucial to rapidly and accurately establish reliability modules and extract parameters from the system modules. This study employed three types of particle swarm optimization (PSO) algorithms to find the optimal parameters of two energy models by minimizing the sum squared errors (SSE) and roots mean squared errors (RMSE). The three algorithms are inertia weight PSO, constriction PSO, and momentum PSO. The obtained calculation results of these three algorithms were compared with those obtained using algorithms from other relevant studies. This study revealed that the use of momentum PSO enables rapid convergence (under 30 convergence times) and the most accurate modeling and yields the most stable parameter extraction (SSE of PEMFC is 2.0656, RMSE of PV cells is 8.839 center dot 10(-4)). In summary, momentum PSO is the algorithm that is most suitable for system parameter identification with multiple dimensions and complex modules.

关键词： metaheuristic optimization algorithm particle swarm algorithm photovoltaic cell proton exchange membrane fuel cell

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Blockchain-Based Educational Management and Secure Software-Defined Networking in Smart Communities

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INTERNATIONAL JOURNAL OF INFORMATION SECURITY AND PRIVACY 2022年第2期16卷

作者： Fang, Bin Nanjing Vocat Univ Ind Technol Nanjing Peoples R China

As network multimedia technology has advanced rapidly, video communication has made enormous strides and has been used in many educational industries. The use of educational video communication is a simple, effective, and convenient method of communication. A fast and energy-efficient blockchain clustering algorithm is proposed to pick the desired cluster head in software-defined networking (SDN). This research suggests using an adaptive resource allocation method and secure communication networks to improve the quality of instructional video transmission. To better educational management resources (EMR), this research suggests using a particle swarm algorithm (PSA). Using the PSA-EMR, an extended particle swarm optimization model suggests a low-complexity solution for adaptive central and distributed resource allocation in communication networks. The method improves the productivity and accuracy of the teaching team. Finally, a cost-effective digital framework for collecting and transmitting high-quality instructional content was developed to conclude the research.

关键词： Adaptive Resource Allocation Method Blockchain Educational Management Resources particle swarm algorithm Smart Cities Software Defined Networking Student Video Communication Technologies

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