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Location effect on gold nano bi-domes based absorption coefficient

OPTICAL AND QUANTUM ELECTRONICS 2015年第7期47卷 1713-1719页

作者： Akhlaghi, Majid Emami, Farzin Nozhat, Najmeh Islamic Azad Univ Young Researchers & Elite Club Omidieh Branch Omidieh Iran Shiraz Univ Technol Electro Opt Dept Shiraz Iran

Binary particle swarm optimization (Bpso) algorithm was used to generate the binary gold nano bi-domes for getting higher absorption coefficient spectrum. The simulation results show that absorption coefficient strongly depends on the localized position of nano particles and non-periodic structures have more appropriate response in term of absorption coefficient. This approach can be useful in optical applications such as solar cell and plasmonic nano antenna.

关键词： Plasmonic nano particles Plasmonic nano antenna Optimization algorithm pso algorithm

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Optimal stochastic reactive power scheduling in a microgrid considering voltage droop scheme of DGs and uncertainty of wind farms

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ENERGY 2012年第1期45卷 994-1006页

作者： Khorramdel, Benyamin Raoofat, Mahdi Shiraz Univ Dept Power & Control Eng Sch Elect & Comp Eng Shiraz Iran

Distributed Generators (DGs) in a microgrid may operate in three different reactive power control strategies, including PV, PQ and voltage droop schemes. This paper proposes a new stochastic programming approach for reactive power scheduling of a microgrid, considering the uncertainty of wind farms. The proposed algorithm firstly finds the expected optimal operating point of each DG in V-Q plane while the wind speed is a probabilistic variable. A multi-objective function with goals of loss minimization, reactive power reserve maximization and voltage security margin maximization is optimized using a four-stage multi-objective nonlinear programming. Then, using Monte Carlo simulation enhanced by scenario reduction technique, the proposed algorithm simulates actual condition and finds optimal operating strategy of DGs. Also, if any DGs are scheduled to operate in voltage droop scheme, the optimum droop is determined. Also, in the second part of the research, to enhance the optimality of the results, pso algorithm is used for the multi-objective optimization problem. Numerical examples on IEEE 34-bus test system including two wind turbines are studied. The results show the benefits of voltage droop scheme for mitigating the impacts of the uncertainty of wind. Also, the results show preference of pso method in the proposed approach. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Stochastic reactive power scheduling Voltage droop characteristic Scenario reduction Expected reactive power reserve Expected voltage security margin pso algorithm

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Power control optimization of a new contactless piezoelectric harvester

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2017年第28期42卷 18134-18144页

作者： Zulueta, Ekaitz Kurt, Erol Uzun, Yunus Manuel Lopez-Guede, Jose Univ Basque Country UPV EHU Univ Coll Engn Vitoria Gasteiz Dept Syst Engn & Control Vitoria Spain Gazi Univ Technol Fac Dept Elect & Elect Engn TR-06500 Ankara Turkey Aksaray Univ Fac Engn Dept Elect & Elect Engn Aksaray Turkey

In this study, we propose an optimization scheme for the control of a piezoelectric wind energy harvester. The harvester is constructed by a blade in front and a magnet in the rear in order to sustain a magnetic repulsion by another magnet located on the stable harvester body in a contactless manner. For such a new harvester, the control scheme is missing in the literature in the sense that the harvester is new and an overall optimization study is required for such a device. In that context, the optimization has been realized by using a new current control law based on the harvester piezoelectric terminal voltage and the layer bending. The proposed control law can impose a second order linear dynamics although the magnetic effects can yield to nonlinear magnetic force relation. In order to improve the new control strategy, a Particle Swarm Optimization algorithm (pso) has been applied, since there is a nonlinear dependency among the control parameters, the collected energy and the bending force mean values. According to results, the captured electrical power has a high increasing trend with respect to the only-voltage-based (OVB) control as the current study proves. On the contrary, the artifact of the method'is that the obtained power is too low to increase the mean bending forces and it requires much complicated control system. (C) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Harvester Wind energy Piezoelectric Control optimization pso algorithm

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A Six-Dimensional Magnetic Localization algorithm for a Rectangular Magnet Objective Based on a Particle Swarm Optimizer

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IEEE TRANSACTIONS ON MAGNETICS 2009年第8期45卷 3092-3099页

作者： Yang, Wan'an Hu, Chao Meng, Max Q. -H. Song, Shuang Dai, Houde Chinese Univ Hong Kong Chinese Acad Sci Shenzhen Inst Adv Integrat Technol Shenzhen Inst Adv Technol Shenzhen 518067 Guangdong Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Inst Comp Technol Shenzhen 518067 Guangdong Peoples R China Chinese Acad Sci Grad Sch Shenzhen 518067 Guangdong Peoples R China Chinese Univ Hong Kong Dept Elect Engn Shatin Hong Kong Peoples R China

To build a wireless capsule endoscope with active external guidance for controllable and interactive diagnosis on the gastrointestinal tract, it is necessary to track the capsule's 3-D position and 3-D orientation. An approach to tracking is to enclose a small rectangular permanent magnet in the capsule. The magnetic field produced around the body by the rectangular magnet can be detected by magnetic sensors outside the patient's body. With these detected magnetic sensor data, the 3-D localization and 3-D orientation parameters can be computed by an appropriate algorithm based on the mathematical model of the rectangular magnet's magnetic field. We tried several nonlinear optimization algorithms, and simulation experiments show that the particle swarm optimization algorithm can work effectively with good accuracy when the magnet moves within a predetermined range.

关键词： Wireless endoscope 6D localization and orientation rectangular magnet pso algorithm

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ADOPTION OF COMPUTER PARTICLE SWARM OPTIMIZATION algorithm UNDER THERMODYNAMIC MOTION MECHANISM

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THERMAL SCIENCE 2020年第5期24卷 2707-2715页

作者： Li, Qizhong Yue, Yizheng Wang, Zhongqi North China Inst Sci & Technol Beijing Peoples R China Inst Disaster Prevent Beijing Peoples R China Beijing Inst Technol Beijing Peoples R China

In order to improve the stability and sensitivity of particle swarm optimization (pso) algorithm and to solve the problem of premature convergence, in this research, a computer pso algorithm based on thermodynamic motion mechanism is proposed based on the principle of thermodynamic motion mechanism. Firstly, the thermodynamic motion phenomenon, the diffusion law in kinematics and the standard pso algorithm are introduced. Then, according to the basic idea of thermodynamic motion mechanism, the standardized pso algorithm is optimized and its optimization process is introduced. Finally, the experimental results are analysed by setting the test function. The results show that among the five test functions, the computer pso algorithm based on thermodynamic motion mechanism has a higher probability of jumping out of the local optimal solution. Its robustness and stability are much better than standard pso algorithms. The evolution ability of the computer pso algorithm based on thermodynamic motion mechanism is better than that of the standard pso algorithm. The standard pso algorithm is superior because it is based on thermodynamic motion mechanism. The research in this paper can provide good guidance for improving the performance of pso algorithm.

关键词： thermodynamic motion mechanism convergence pso algorithm test functions

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A novel, reduced-order optimization method for nonlinear model correction of turboshaft engines

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2024年第4期38卷 2103-2122页

作者： Han, Xinhao Huang, Jinquan Zhou, Xin Zou, Zelong Lu, Feng Zhou, Wenxiang Nanjing Univ Aeronaut & Astronaut Coll Energy & Power Engn Nanjing 210016 Peoples R China

Turboshaft engines are different from each other due to manufacturing and installation tolerances. Hence, it is difficult to draw out the physical model from the average component maps and design points to represent the performance of the individual engine. The available test-bed data is usually less than the number of correction coefficients to update the maps, and it is the underdetermined state optimization issue. In this paper, we propose a novel reduced-order optimization, namely pso-EKF algorithm, combined with prior state estimation for non-linear model correction of the turboshaft engine. This method combines the advantages of pso and extended Kalman filter (EKF). pso-EKF method converts partial parameters optimized by pso into parameters directly solved by EKF. The order of optimization space is reduced. Using the correction coefficient function, a stability improvement strategy is designed to ensure the stability of the optimization process. Compared with the GA and pso algorithms, experimental verification shows that the method has a faster convergence speed and smaller model error than the general pso. After the performance map is updated by this method, the error of outputs of the individual model is within 1.4 %.

关键词： Turboshaft engine Component-level model pso algorithm EKF Model correction

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Parameter identification and optimization algorithm in microbial continuous culture

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APPLIED MATHEMATICAL MODELLING 2012年第2期36卷 585-595页

作者： Shen, Bangyu Liu, Chongyang Ye, Jianxiong Feng, Enmin Xiu, Zhilong Dalian Univ Technol Sch Math Sci Dalian 116024 Liaoning Peoples R China Huaiyin Normal Univ Sch Math Sci Huaian 223300 Jiangsu Peoples R China Shandong Inst Business & Technol Sch Math & Informat Sci Yantai 264005 Shandong Peoples R China Dalian Univ Technol Sch Environm & Biol Sci Dalian 116024 Liaoning Peoples R China

In this study, a novelty mathematical model is established to formulate the continuous culture of glycerol to 1,3-Propanediol (1,3-PD) by Klebsiella pneumoniae, in which the inhibition of 3-hydroxypropionaldehyde (3-HPA) to cells growth and activity of some enzymes (such as glycerol dehydratase (GDHt) and 1,3-PD oxidoreductase (PDOR)), and the passive diffusion and active transport of glycerol and 1,3-PD across cell membrane are all taken into consideration. Taking the mean relative error between the experimental data and calculated values as the performance index, a parameter identification model involving multiple nonlinear dynamic systems is presented. The identifiability of the parameter identification model is also proved. Finally, an improved particle swarm optimization (pso) algorithm is constructed to find the optimal parameters for the systems under substrate limitation and excess conditions, respectively. Numerical results not only show that the established model can be used to describe the continuous fermentation reasonably, but also the improved pso algorithm is valid. (C) 2011 Elsevier Inc. All rights reserved.

关键词： Parameter identification pso algorithm 1,3-Propanediol Continuous culture Nonlinear dynamic system

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Modified CORPS beamforming network with null-steering capability

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IET MICROWAVES ANTENNAS & PROPAGATION 2019年第8期13卷 1208-1213页

作者： Saliani, Nima Bemani, Mohammad Kazemi, Hossein Univ Tabriz Elect & Comp Engn Tabriz Iran Amirkabir Univ Technol Elect Engn Tehran Iran

This article proposes CORPS beamforming network (BFNs) with both beam and null steering capability. All simulation results are presented for scannable mono-beam configuration but it can be extended to the multi-beam system. Complex inputs are optimised by means of the pso algorithm to get the array factor with the desired characteristics that are side lobe level (SLL), directivity (D), and null depth. All sub-blocks of the BFN are designed in the centre frequency of 2.4 GHz.

关键词： antenna radiation patterns particle swarm optimisation beam steering linear antenna arrays array signal processing antenna arrays simulation results scannable mono-beam configuration multibeam system complex inputs pso algorithm null depth modified CORPS beamforming network null-steering capability BFNs null steering capability frequency 2 4 GHz

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An Enhanced Lithium-Ion Battery Model for Estimating the State of Charge and Degraded Capacity Using an Optimized Extended Kalman Filter

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IEEE ACCESS 2020年 8卷 208322-208336页

作者： Imran, Rasool M. Li, Qiang Flaih, Firas M. F. Wuchang Univ Technol Sch Artificial Intelligence Wuhan 430223 Peoples R China Minist Elect State Co North Distribut Elect Baghdad 10013 Iraq

Lithium-ion batteries have become the most appropriate batteries to use in modern electric vehicles due to their high-power density, long lifecycle, and low self-discharge rate. The precise estimation of the state of charge (SOC) in lithium-ion batteries is essential to assure their safe use, increase the battery lifespan, and achieve better management. Various methods of SOC estimation for lithium-ion batteries have been used. Among these methods, the model-based estimation method is the most practical and reliable. The accuracy of the utilized model is a crucial factor in realizing better SOC estimation in the model-based method. In this paper, an enhanced battery model is proposed to estimate the SOC precisely via an optimized extended Kalman filter. The model considers the most influencing factors on the estimation accuracy, such as temperature, aging, and self-discharge. The parameterization of the model has defined the dependency of sensitive parameters on state estimation. As a fundamental step before estimating the SOC, the capacity degradation is evaluated using a straightforward approach. Later, a particle swarm optimization algorithm is utilized to optimize the vector of process noise covariance to enhance the state estimation. The performance of the proposed method is compared to recent techniques in the literature. The results indicate the effectiveness of the proposed approach in terms of both accuracy and computational simplicity.

关键词： Lithium-ion batteries Temperature Computational modeling Aging State of charge Kalman filters State estimation Lithium-ion battery state of charge capacity estimation extended Kalman filter pso algorithm

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Reliability evaluation of power systems in the presence of energy storage system as demand management resource

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2019年 110卷 1-10页

作者： Yang, Hejun Zhang, Yeyu Ma, Yinghao Zhou, Ming Yang, Xi Hefei Univ Technol Sch Elect Engn & Automat Hefei 230009 Anhui Peoples R China North China Elect Power Univ State Key Lab Alternate Elect Power Syst Renewabl Beijing 102206 Peoples R China

The energy storage system as a demand management resource can be incorporated into a power system for economizing the cost and improving the reliability. Therefore, this paper investigates the participation of energy storage system in demand management and its application to the reliability evaluation. Firstly, an optimal period partitioning model is proposed for dividing load series into the on-peak period, the mid-peak period, and the off-peak period, and a pso based optimization algorithm is explored to optimize the unconstrained period partitioning problem which is transformed from the constrained optimization problem. Secondly, a demand management model with the participation of energy storage system is developed, and a peak shaving and valley filling factor is presented for describing the degree of demand management in this paper. Thirdly, a pseudo-analytical sampling method is presented for evaluating the reliability of the power system in the presence of energy storage system as a demand management resource, and some indices which can be used to describe the influence of demand management are defined. Finally, the Roy Billinton Test System and the Reliability Test System are conducted for verifying the correctness and validity of the proposed method.

关键词： Energy storage system Demand management Power system planning pso algorithm Reliability evaluation

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