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An advanced virtual synchronous generator control technique for frequency regulation of grid-connected PV system

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2021年 125卷 106440-106440页

作者： Rehman, Haseeb Ur Yan, Xiangwu Abdelbaky, Mohamed Abdelkarim Jan, Mishkat Ullah Iqbal, Sheeraz North China Elect Power Univ Sch Elect & Elect Engn Baoding 071003 Peoples R China North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewabl Beijing 102206 Peoples R China Cairo Univ Fac Engn Dept Elect Power & Machines Giza 12613 Egypt

The future power system is developing to an inverter-based system from a machine dominated power system due to a large integration of renewable energy sources (RESs). Lack of inertial part and intermittency of the RESs causes frequency instability in the power system. The virtual synchronous generator (VSG) development has been made to add inertial control to the power system for controlling the frequency deviation caused by the integration of the photovoltaic system. The VSG system comprised of power electronics components having a droop control mechanism like the conventional synchronous generator, which provides the necessary frequency stability to the power system. In this paper, three parallel VSG based photovoltaic systems integrated with battery storage systems are used to analyze the frequency response and its stability. Moreover, an advanced genetic algorithm optimization method is used to get the optimal values of parameters of the droop controller used in VSG. Furthermore, two different cases with respect to variation in supply and load power of the system are analyzed in detail. Additionally, an IEEE 14 bus system is utilized to validate the proposed system in MATLAB/Simulink. Evident improvements are observed in the simulation results presented through the suggested GA based VSG control technique.

关键词： Frequency regulation genetic algorithm optimization Multiple VSGs coordination PV grid integration Virtual synchronous generator

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Design of Minimal Quantity Lubrication System with Improved PID Control 3

Design of Minimal Quantity Lubrication System with Improved ...

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3rd World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM)

作者： Yuan, Jia Liu, Niancong Chengdu Univ Technol Coll Nucl Technol & Automat Engn Chengdu Peoples R China

ISBN: (纸本)9781665441094

To overcome the shortcomings of low automation, low test precision, and inaccurate control precision in the micro-lubrication device, a minimal quantity lubrication (MQL) system with high accuracy was designed. The system is composed of sensors (e.g. flow sensor, air pressure sensor), microcontroller unit (MCU), and control mechanism (e.g. peristaltic pump, air pressure valve), which can realize the functions of automatic detection, signal processing, and control in real-time. Concurrently, the improved PID control algorithm (GA_PID) based on genetic algorithm (GA) to optimize PID parameters makes the whole control system to achieve rapid response and accurate control. In this study, the MQL system with an improved PID control algorithm has high stability and has engineering application value due to its high efficiency of regulating parameter performance.

关键词： MQL system genetic algorithm optimization PID control

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AC Position Servo System Controller of Aircraft Simulator Based on genetic algorithm optimization

AC Position Servo System Controller of Aircraft Simulator Ba...

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International Conference on Advanced Materials Design and Mechanics (ICAMDM 2012)

作者： Liu, Baolong Zheng, Xiulin Li, Xiaoqi Aviat Univ AF Mil Simulat Technol Inst Changchun Jilin Peoples R China

ISBN: (纸本)9783037854808

This paper analyzes nonlinear and uncertainties factors caused by the friction and clearance of ac servo system. a Fuzzy-PI) controller based on genetic algorithm was designed. Adjust the three parameters of PID controller based on the error and error change rate;Adjust the various parameters of the fuzzy-PID controller using genetic algorithm optimization;This method has better control effect on the AC of Meter systems than traditional PID controller. And both dynamic and steady performances were improved evidently.

关键词： Aircraft Simulator AC Position Servo System Fuzzy PID Controller genetic algorithm optimization

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Boundary restricted genetic algorithm for multi-layer equivalent dielectric parameters retrieval of artificial gradient structure

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INTERNATIONAL JOURNAL OF MODERN PHYSICS C 2021年第1期32卷 2150004-2150004页

作者： Guo, Shaojun Shen, Tongsheng Zou, Chunrong Acad Mil Sci PLA Natl Inst Def Technol Innovat Beijing Peoples R China 169 Yongding Rd Beijing Peoples R China

With the equivalent dielectric parameters of an artificial gradient structure consisting of a kind of dielectric material as inputs of FDTD multi-layer equivalent simulation, there are big nonuniform differences between the S-curve of retrieval methods and the corresponding full structure. In order to decease these differences, here, a boundary restricted genetic algorithm is proposed. In our method, Smith S method is employed to find the rough values of dielectric parameters, and at the same time, the up and low limit cases are introduced to calculate the boundary parameter values for each layer of the artificial structure and form the searching areas for genetic algorithm to get high-precision inversion of S-curve. The FDTD S-curve of the retrieval parameters and full structure of cone gradient and moth eye were performed experimentally, the maximum deviation of inversion S21 curves corresponding to the cone and moth eye with full structure is limited within 0.0028 and 0.0024 in the X-band (8-12 GHz) range, respectively, which shows us the promising application of our method in dielectric parameter retrieval and may be helpful for electromagnetic field analysis.

关键词： Equivalent dielectric parameter retrieval S-curve inversion boundary restricted genetic algorithm optimization

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On Neural Networks Based Electrothermal Modeling of GaN Devices

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IEEE ACCESS 2019年 7卷 94205-94214页

作者： Jarndal, Anwar Univ Sharjah Elect & Comp Engn Dept Sharjah 27272 U Arab Emirates

This paper presents an effcient artificial neural network (ANN) electrothermal modeling approach applied to GaN devices. The proposed method is based on decomposing the device nonlinearity into intrinsic trapping-induced and thermal-induced nonlinearities that can be simulated by low-order ANN models. The ANN models are then interconnected in the physics-relevant equivalent circuit to accurately simulate the transistor. genetic algorithm (GA)-based training procedure has been implemented to find optimal values for the weights of the ANN models. The modeling approach is used to develop a large-signal model for a 1-mm gate-width GaN high-electron mobility transistor (HMET). The model has been implemented in the advanced design system (ADS) and it has been validated by pulsed and continues small- and large-signal measurements. The model simulations showed a very good agreement with the measurements and verify the validity of the developed technique for dynamic electrothermal modeling of active devices.

关键词： GaN HEMT electrothermal modeling neural networks genetic algorithm optimization

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New method for power allocation of multi-power sources considering speed-up transient vibration of planetary power-split HEVs driveline system

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2019年 128卷 1-18页

作者： Wang, Feng Zhang, Jian Xu, Xing Cai, Yingfeng Zhou, Zhiguang Sun, Xiaoqiang Jiangsu Univ Automot Engn Res Inst Zhenjiang 212013 Jiangsu Peoples R China Chongqing Univ Technol Minist Educ Key Lab Adv Manufacture Technol Automobile Parts Chongqing 400054 Peoples R China Chery Automobile Co Ltd Powertrain Technol Ctr New Energy Dev Dept Wuhu 241009 Peoples R China

One of the major issues for hybrid electric vehicles (HEVs) powertrain is the torsional vibration in the process of speed-up condition, which is unavoidable. The broader goal of this article is to re-examine the classical gear transmission machinery transient vibration problem in the context of a 4 + N degree of freedom nonlinear torsional system that essentially describes a planetary coupling transmission system (PCTS) of HEVs example, and further provide a new method for power allocation of multi-power sources considering speed-up transient vibration of planetary power-split HEVs driveline system. In particular, resonant amplifications during acceleration, as excited by angular displacement-based meshing stiffness of gear teeth, are investigated using a nonlinear torsional model, and the transient vibration predictions are successfully compared with test bench results. Then a quasi-linear model during acceleration process is proposed and numerically solved to obtain the transient vibration acceleration as well as its envelope curve. Dynamic response results of PCTS are also successfully compared and analyzed under different speed-allocation rules. Finally, an improved genetic algorithm method is applied to construct optimal relationship between the motor speeds and vehicle speeds, and the influences of vibration character and energy consumption are successfully considered in multi-optimized function. Experimental results under the speed-up condition show that transient vibration acceleration of the optimized powertrain is decreased within the safe range, thus new power-allocation solutions provide more insight to the enhancement of planetary power-split HEVs quality. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Transient vibration-induced power allocation Angular displacement-based meshing stiffness Planetary coupling transmission system Multi-power source machinery genetic algorithm optimization

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Optimal planning and design of run-of-river hydroelectric power projects

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RENEWABLE ENERGY 2019年 141卷 858-873页

作者： Ibrahim, Mohamed Imam, Yehya Ghanem, Ashraf Cairo Univ Fac Engn Dept Irrigat & Hydraul Giza Egypt Univ Sci & Technol Zewail City Sci & Technol Environm Engn Program Giza Egypt

An optimal planning and preliminary-design (OPD) model was developed to maximize the annual net benefit of run-of-river (RoR) hydropower projects along a stream. The OPD model identifies optimal, non-overlapping RoR projects along the given stream. For each project, the OPD model determines intake location;penstock diameter and length;and type, number, and discharge of turbines. The OPD model applies genetic algorithm in two stages. The first stage optimizes design of individual potentially overlapping projects densely spaced at uniform intervals along the stream and the second stage determines the set of non-overlapping projects that maximizes the net hydropower benefit. Results of the OPD model compared favorably to results of previous models for a hypothetical case study. Further application of the OPD model to idealized case studies with different stream elevation profiles and with tributary flows indicated that the model gives reliable results. The OPD model was used to identify optimal RoR projects for the Guder River, Ethiopia. The OPD model identified 22 optimal RoR projects covering similar to 49 km of the 127-km-long Guder River. The total annual generated energy from the identified projects is similar to 540 GWh and the installed capacity for individual projects ranges between similar to 1 MW and 21 MW. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Hydropower Run-of-river genetic algorithm optimization Guder river

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genetic and hybrid algorithms for optimization of non-singular 3PRR planar parallel kinematics mechanism for machining application

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ROBOTICA 2018年第6期36卷 839-864页

作者： Rosyid, Abdur El-Khasawneh, Bashar Alazzam, Anas Khalifa Univ Sci & Technol Mech Engn Dept POB 127788 Abu Dhabi U Arab Emirates

This paper proposes a special non-symmetric topology of a 3PRR planar parallel kinematics mechanism, which naturally avoids singularity within the workspace and can be utilized for hybrid kinematics machine tools. Subsequently, single-objective and multi-objective optimizations are conducted to improve the performance. The workspace area and minimum eigenvalue, as well as the condition number of the homogenized Cartesian stiffness matrix across the workspace, have been chosen as the objectives in the optimization based on their relevance to the machining application. The single-objective optimization is conducted by using a single-objective genetic algorithm and a hybrid algorithm, whereas the multi-objective optimization is conducted by using a multi-objective genetic algorithm, a weighted sum single-objective genetic algorithm, and a weighted sum hybrid algorithm. It is shown that the single-objective optimization gives superior value in the optimized objective, while sacrificing the other objectives, whereas the multi-objective optimization compromises the improvement of all objectives by providing non-dominated values. In terms of the algorithms, it is shown that a hybrid algorithm can either verify or refine the optimal value obtained by a genetic algorithm.

关键词： genetic algorithm optimization Hybrid optimization Multi-objective optimization Parallel manipulators Manufacturing

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Development of sensor placement optimization tool and application to large-span cable-stayed bridge

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JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING 2019年第1期9卷 77-90页

作者： Wu, Zheng Yi Zhou, Kai Shenton, Harry W., III Chajes, Michael J. Bentley Syst Inc Watertown CT 06795 USA Univ Delaware Dept Civil & Environm Engn Newark DE USA

Structural health monitoring (SHM) is essential for engineers to effectively evaluate structural performance. The accelerometers and strain gauges are commonly used for monitoring and testing structural performance. Placing both types of sensors is the key step for SHM and structural testing. This paper presents the development and application of the sensor placement optimization methods, which have been integrated and implemented in a versatile software tool for maximizing the sensor coverage capacity for structural performance assessment. The sensor placement solutions are optimized using a parallel optimization framework based on the competent genetic algorithm, leading to a number of features that enrich the application flexibility. The developed methods and software tool provide a generic approach for multi-type sensor placement. The integrated tool has been applied to the Indian River Inlet Bridge a large-span cable-stayed bridge to demonstrate and validate the effectiveness of the proposed solution methods for facilitating real world SHM practice.

关键词： Strain gauge placement Accelerometer placement Structural health monitoring genetic algorithm optimization

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Composite material structure optimization design and aeroelastic analysis on forward swept wing

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING 2019年第13期233卷 4679-4695页

作者： Xue Rongrong Ye Zhengyin Ye Kun Wang Gang Northwestern Polytech Univ Sch Aeronaut Youyi West Rd 127 Xian 710072 Shaanxi Peoples R China

The static aeroelastic torsion divergence problem is the main obstacle to bring forward swept wing into massive applications. The aeroelastic tailoring technique-based radial basis function neural networks (RBFNNs) and genetic algorithm (GA) optimization in MATLAB considering the material orientation, thickness, and lay-up are elucidated in the present work. RBFNNs are used to build a surrogate model between the composite parameters and structure displacement, which is proved robust and accurate. Then an optimal structure is obtained by GA global search based on RBFNNs model with the weight constrain. The displacements of the forward swept wing caused by an approximate aerodynamic load are decreased 32.5% through finite element method (FEM) static structural analysis. The modal analysis illustrates that the first mode frequency increases by 33.0% and the second mode increases by 37.9%. A computational aeroelasticity approach is developed by in-house Hybrid Unstructured Reynolds-Averaged Navier-Stokes solver associating an open source FEM code - Calculix. The results of coupling calculations show effectiveness of aeroelastic tailoring optimization of composite forward swept wing without weight penalty. The results obtained demonstrate that for the forward swept wing, the most violent situation appears around Mach Number 1.0 where the aeroelastic tailoring optimization could decrease the torsion angle by nearly 70.0%. The torsion of forward swept wing will increase at subsonic and decrease at supersonic with the increase of velocity.

关键词： Composite material forward swept wing aeroelastic tailoring radial basis function neural networks genetic algorithm optimization

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