检索结果-内蒙古大学图书馆

Multilevel DC-link converter photovoltaic system with modified PSO based on maximum power point tracking

SOLAR ENERGY 2017年第Sep.期153卷 329-342页

作者： Mao, Mingxuan Zhang, Li Duan, Qichang Chong, Benjamin Chongqing Univ Automat Coll Chongqing 400044 Peoples R China Univ Leeds Sch Elect & Elect Engn Leeds LS2 9JT W Yorkshire England

The paper presents a modified particle swarm optimization (MPSO) control strategy for the maximum power point tracking applied to a multilevel DC-link PV power generation system. This system consists of a chain of PV modules with individual DC-DC converters and has a DC-AC converter at its terminals for generating AC voltage. The proposed MPSO control method can predict all PV voltages at their maximum power point on the basis of respective light level and temperature. A PWM with permutation of DC converter switching is applied to balance switch utilisation. The method is applied to a system of five-voltage levels with two PV-converter units under different light intensities and the results are compared with the perturb and observe (P&O) method and the traditional PSO method under the same operating conditions. The paper shows that the new method gives more rapid convergence, increased power output, and lower total harmonic distortion. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Multilevel DC-link converters modified particle swarm optimization (MPSO) Maximum power point tracking (MPPT) Photovoltaic (PV) system

来源：评论

学校读者我要写书评

暂无评论

Beam reconfiguration of linear array of parallel dipole antennas through switching with real excitation voltage distribution

引用

ANNALS OF TELECOMMUNICATIONS 2012年第5-6期67卷 285-293页

作者： Basu, Banani Mahanti, G. K. Natl Inst Technol Dept Elect & Commun Engn Durgapur India

In this paper, authors propose a method based on the modified particle swarm optimization (PSO) for beam reconfiguration of linear array of mutually coupled parallel half-wavelength dipole antennas with real excitation voltage amplitude distribution. Two different beam pairs are generated, one pencil/pencil beam pair and another pencil/flat-top beam pair in the horizontal plane. One beam is changed to another through switching while sharing a common amplitude distribution. Two examples are presented, one without ground plane and another in presence of ground plane. Dipoles are connected to its feed network through a switch, so that it can be turned on or off, depending on the switch position. Beam reconfiguration is achieved by suitably turning the array elements on or off using same voltage excitation distribution. modified PSO is used to compute the excitation voltages as well as the switching configuration for each pattern having a prefixed side lobe level. The current in the driven and parasitic elements is determined via induced EMF method considering the current distribution on each dipole to be sinusoidal. Proposed method efficiently synthesizes dual-beam switching the power pattern from pencil to pencil and pencil to flat-top having same or different side lobe levels using common excitation voltages. It calculates the maximum variation of the active impedance of driven elements and the power losses when the radiation patterns switch from one beam to another. The paper calculates the array directivity as the distances between antenna array and the ground pane varies. Three other state-of-the-art metaheuristics like differential evolution, gravitational search algorithm, artificial bee colony algorithm are also employed for achieving a comparative evaluation.

关键词： modified particle swarm optimization Switching Beam reconfiguration Linear array Dipole antennas Mutual coupling

来源：评论

学校读者我要写书评

暂无评论

Distribution network expansion considering distributed generation and storage units using modified PSO algorithm

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2013年第1期52卷 221-230页

作者： Sedghi, M. Aliakbar-Golkar, M. Haghifam, M. -R. KN Toosi Univ Technol Tehran Iran Tarbiat Modares Univ Tehran Iran

Multistage distribution network expansion because of load growth is a complex problem in distribution planning. The problem includes minimizing cost of objective function subject to technical constraints. The objective function consists of investment, operation and reliability costs. In this paper, HV/MV substations, main and reserve MV feeders, dispatchable DG sources and storage units are considered as possible solutions for multistage distribution expansion planning. A three-load level is used for variable load and some strategies are proposed for DG and storage units operation. A modified PSO algorithm is applied to solve the complex optimization problem. Numerical results of the case studies show the ability of the modification. Moreover, the proposed strategies improve the distribution network from both economical and reliability points of view compared with the other methods. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Distribution network planning Distributed generation Storage Reliability modified particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

Joint Waveform Control and Resource optimization for Maneuvering Targets Tracking in Netted Colocated MIMO Radar Systems

引用

IEEE SYSTEMS JOURNAL 2022年第3期16卷 3960-3971页

作者： Su, Yang Cheng, Ting He, Zishu Li, Xi Univ Elect Sci & Technol China Sch Informat & Commun Engn Chengdu 611731 Peoples R China

In netted colocated multiple-input multiple-output (MIMO) radar system (NCMRS), constrained to the limited resource, one must decide when to run the NCMRS, which nodes are to be activated, how much energy should be consumed, and which waveform type as well as parameter should be transmitted by each activated node. To this end, in this article, we consider the problem of joint waveform control and space-time resource management for maneuvering targets tracking in NCMRS. First, the joint waveform type as well as parameter selection and space-time resource management optimization model is proposed, where both the network system resource consumption and the overall tracking performance of maneuvering targets are considered and employed as the network comprehensive cost. Then, to solve the established optimization problem efficiently, a modified particle swarm optimization (MPSO)-based joint waveform control and space-time resource optimization (JWCSTRO) algorithm is put forward. In the MPSO-based JWCSTRO algorithm, the system sampling period, the activated nodes, the node-target assignment, and the subarray number, transmit energy and transmit waveform type, as well as parameter of each activated node can be adjusted jointly and adaptively, where the former five implement the space-time resource optimization and the last one achieves the waveform control in NCMRS. Finally, numerical simulation results demonstrate the effectiveness of the proposed MPSO-based JWCSTRO algorithm. Furthermore, compared with the five other benchmark algorithms, the maximum and minimum improvement ratios of the network comprehensive cost of the proposed MPSO-based JWCSTRO algorithm are 44.89% and 21.68%, respectively.

关键词： optimization Target tracking Resource management Radar tracking Radar Signal to noise ratio Numerical models Maneuvering targets tracking modified particle swarm optimization netted colocated MIMO radar systems subarray division waveform control and space-time resource optimization

来源：评论

学校读者我要写书评

暂无评论

A new approach to smooth global path planning of mobile robots with kinematic constraints

引用

INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2019年第1期10卷 107-119页

作者： Song, Baoye Wang, Zidong Zou, Lei Xu, Lin Alsaadi, Fuad E. Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH Middx England King Abdulaziz Univ Dept Elect & Comp Engn Fac Engn Jeddah 21589 Saudi Arabia

This paper is concerned with the planning problem of smooth global path for mobile robots with kinematic constraints. A new approach is proposed that is based on a modified particle swarm optimization (MPSO) combined with the (3)-splines. Some preliminaries on (3)-splines are first introduced to interpolate an arbitrary sequence of points with assigned kinematic parameters associated with the motion and control of mobile robots. Then, the MPSO algorithm with adaptive random fluctuations (ARFs) is proposed to deal with the frequently encountered local convergence issue in the planning of the global smooth path. In the MPSO algorithm, the evolutionary state is classified averagely at each iteration according to the evaluated evolutionary factor, where the velocity updating dynamics switches among various modes according to the evolutionary state and the ARFs are enforced on the global/local best particles in each mode of the current iteration. The proposed MPSO is verified to outperform five other well-known PSO algorithms via comprehensive simulation experiments on a collection of benchmark functions. Finally, the new approach by combining the MPSO algorithm with the (3)-splines is exploited to handle a double-layer smooth global path planning problem with several kinematic constraints.

关键词： Smooth path planning Mobile robots modified particle swarm optimization Adaptive random fluctuations (3)-splines

来源：评论

学校读者我要写书评

暂无评论

Model predictive control strategy for energy optimization of series-parallel hybrid electric vehicle

引用

JOURNAL OF CLEANER PRODUCTION 2018年 199卷 348-358页

作者： Wang, Yafei Wang, Xiangyu Sun, Yong You, Sixiong Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China Tsinghua Univ State Key Lab Automot Safety & Energy Beijing 100084 Peoples R China Ocean Univ China Coll Informat Sci & Engn Qingdao 266100 Peoples R China

Series-parallel hybrid electric vehicle (SPHEV) is a compact and effective configuration of HEV, which has great potential to save fuel consumption. Because of multi power sources (one engine and two electric motors) and various driving conditions, it is difficult to design an optimal energy management strategy (EMS). To obtain better fuel economy, a novel particle swarm optimization based (PSO-based) nonlinear model predictive control (NMPC) strategy is proposed for EMS of SPHEV. First, a nonlinear model predictive control framework is designed. Then, a modified particle swarm optimization is used for receding horizon optimization. Next, in order to realize fast computing, a two-steps optimization method is adopted. Finally, the proposed strategy are verified by simulations based on the data of a real bus and a driving cycle. The results show that the fuel consumption of SPHEV is greatly decreased by more than 10% compared to that with CD-CS strategies. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Series-parallel hybrid electric vehicle Model predictive control modified particle swarm optimization Energy optimization

来源：评论

学校读者我要写书评

暂无评论

3D brain tumor segmentation in MRI images based on a modified PSO technique

引用

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY 2019年第4期29卷 501-509页

作者： Gtifa, Wafa Hamdaoui, Faycal Sakly, Anis Univ Monastir Dept Elect Engn Natl Sch Engineers ENIM Automat Elect Syst & Envi Monastir Tunisia Univ Monastir Lab EE Monastir Fac Sci FSM Monastir Tunisia

Three-dimensional (3D) brain tumor segmentation is a clinical requirement for brain tumor diagnosis and radiotherapy planning. This is a challenging task due to variation in type, size, location, and shape of tumors. Several methods such as particle swarm optimization (PSO) algorithm formed a topological relationship for the slices that converts 2D images into 3D magnetic resonance imaging (MRI) images which does not provide accurate results and they depend on the number of input sections, positions, and the shape of the MRI images. In this article, we propose an efficient 3D brain tumor segmentation technique called modified particle swarm optimization. Also, segmentation results are compared with Darwinian particle swarm optimization (DPSO) and fractional-order Darwinian particle swarm optimization (FODPSO) approaches. The experimental results show that our method succeeded 3D segmentation with 97.6% of accuracy rate more efficient if compared with the DPSO and FODPSO methods with 78.1% and 70.21% for the case of T1-C modality.

关键词： 2D images 3D brain tumor segmentation modified particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

Modeling and optimization of coal blending and coking costs using coal petrography

引用

INFORMATION SCIENCES 2020年 522卷 49-68页

作者： Yuan, Yan Qu, Qilin Chen, Luefeng Wu, Min China Univ Geosci Sch Automat Wuhan 430074 Peoples R China Hubei Key Lab Adv Control & Intelligent Automat C Wuhan 430074 Peoples R China

Coke is an important raw material in the steel industry, and its quality directly influences the smelting of iron and steel. To improve coal quality and reduce coal blending costs, we need to predict the coke quality and optimize the coal blending scheme. In this paper, we propose a modeling and optimization method based on the characteristics of the coal blending and coking process. First, we establish a model for predicting coke quality from coking petrography data, based on Gaussian functions and Xgboost-SVR. The model has two components. In the first part, we analyze the key characteristics of the coal blending and coke process, and extract features of the vitrinite reflectance distribution with Gaussian functions. In the second part, we use Xgboost to select a representative feature subset, and then use support vector regression (SVR) to create a model for predicting coal quality. Next, we formulate a multi-constraint optimization problem to describe the coal blending costs, and solve it using a modified particle swarm optimization. Finally, we demonstrate the effectiveness of our modeling and optimization method by applying it to actual process data. This shows that our proposed method can improve prediction performance and reduce the coal blending costs. (C) 2020 Elsevier Inc. All rights reserved.

关键词： Coal blending and coking process Gaussian functions Xgboost-SVR Coal petrography Costs optimization modified particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

Intelligent approach to maximum power point tracking control strategy for variable-speed wind turbine generation system

引用

ENERGY 2010年第6期35卷 2440-2447页

作者： Lin, Whei-Min Hong, Chih-Ming Natl Sun Yat Sen Univ Dept Elect Engn Kaohsiung 80424 Taiwan

To achieve maximum power point tracking (MPPT) for wind power generation systems, the rotational speed of wind turbines should be adjusted in real time according to wind speed. In this paper, a Wilcoxon radial basis function network (WRBFN) with hill-climb searching (HCS) MPPT strategy is proposed for a permanent magnet synchronous generator (PMSG) with a variable-speed wind turbine. A high-performance online training WRBFN using a back-propagation learning algorithm with modified particle swarm optimization (MPSO) regulating controller is designed for a PMSG. The MPSO is adopted in this study to adapt to the learning rates in the back-propagation process of the WRBFN to improve the learning capability. The MPPT strategy locates the system operation points along the maximum power curves based on the dc-link voltage of the inverter, thus avoiding the generator speed detection. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Wilcoxon radial basis function network modified particle swarm optimization Permanent magnet synchronous generator Maximum power point tracking Hill-climb searching

来源：评论

学校读者我要写书评

暂无评论

Adequate Topology for Efficient Energy Resources Utilization of Active Distribution Networks Equipped With Soft Open Points

引用

IEEE ACCESS 2019年 7卷 99003-99016页

作者： Shafik, M. B. Chen, Hongkun Rashed, Ghamgeen, I El-Sehiemy, R. A. Elkadeem, M. R. Wang, Shaorong Wuhan Univ Sch Elect Engn & Automat Wuhan 430072 Hubei Peoples R China Kafrelsheikh Univ Fac Engn Elect Power Syst & Machines Dept Kafrelsheikh 33516 Egypt Ecole Cent Nantes F-44300 Nantes France Huazhong Univ Sci & Technol Sch Elect & Elect Engn Wuhan 430074 Hubei Peoples R China

Active distribution networks concerned with providing efficient control technologies for large-scale integration of distributed generation (DG) units into the distribution systems. This research proposes a methodology for distribution networks reconfiguration by controlling number, sharing, size, and location of DG units. Also, the soft-open points (SOPs) are added instead of the tie line switches. The SOPs are benefited with its high capability in controlling active/reactive power flow to enhance transmission system performance. The main target of this work is to increase the efficiency of energy utilization through minimizing the power system losses and improving system voltage profile while preserving all system constraints within permissible limits with reliable and flexible networks in normal and abnormal conditions with a suitable penetration level of DG. A modified particle swarm optimizer is developed to find the best system configuration, size, and placement of DG units as well as the size and allocation of SOPs. Research methodology is tested on two standards: the IEEE 33-node and 69-node distribution networks under different operating cases. This paper compares the obtained results with those in the literature to prove the capabilities of the proposed work. Finally, the suggested work pursues the optimal number of DG units with their appropriate penetration levels and selects the most convenient location of SOPs for adequate network reconfiguration.

关键词： Efficiency of energy utilization active distribution networks distributed generation soft-open points modified particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：