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检索条件"主题词=Particle swarm Optimization Algorithm"

共 1430 条记录，以下是851-860 订阅

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Application of Hybrid Salp swarm optimization Method for Solving OPF Problem

Application of Hybrid Salp Swarm Optimization Method for Sol...

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International Conference on Advanced Electrical Engineering (ICAEE)

作者： Khelifi, Aboubakr Bentouati, Bachir Chettih, Saliha El Sehiemy, Ragab A. Amar Telidji Univ LMSF Lab Laghouat Algeria Univ Kafrelsheikh Dept Elect Engn Fac Engn Kafr Al Sheikh Egypt

ISBN: (纸本)9781728122205

In this paper, a new hybrid solution to the Optimal Power Flow (OPF) problem is proposed. In order to achieve this goal, a new hybrid Salp swarm algorithm (HSSA) is proposed to find the optimal frontier of OPF problem. The proposed hybrid algorithm combines the advantages of the salp swarm algorithm (SSA) and particle swarm optimization (PSO) algorithm. The proposed HSSA provides more efficient solutions even for conflict constraints. This method is applied on five objective functions called power generation cost, environmental pollution emissions, active power loss, voltage deviation and voltage stability. The tests and results of the proposed HSSA have been applied to IEEE 30 bus test system to demonstrate the high performance compared with other optimization methods in the literature. Single and bi-objectives studied cases are tested to prove the capability of the proposed HSSA compared with the original SSA and PSO as well as the existing methods in the literature.

关键词： Optimal power flow salp optimization algorithm particle swarm optimization algorithm HSSA multi-objective HSSA emission minimization enhancing voltage profile

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Reactive Power Management of MV Distribution Grid with Inverter-based PV Distributed Generations using PSO algorithm 45

Reactive Power Management of MV Distribution Grid with Inver...

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45th Annual Conference of the IEEE Industrial Electronics Society (IECON)

作者： Moondee, Wittaya Srirattanawichaikul, Watcharin Chiang Mai Univ Dept Elect Engn Fac Engn Chiang Mai Thailand Chiang Mai Univ Grad Sch Chiang Mai Thailand Prov Elect Author Bangkok Thailand

ISBN: (纸本)9781728148786

This paper presents the reactive power management approach for a medium voltage (MV) distribution grid with inverter-based photovoltaic (PV) distributed generations using a particle swarm optimization (PSO) algorithm. The objective of this research is to control the reactive power flow to support the distribution grid and voltage regulation. The control algorithm is based on centralized reactive power management at the MV distribution grid for allocating the optimal reactive power of each PV distributed generation. The system case consists of a PV system connected to the simple radial feeders in the distributed grid. Simulation studies of the proposed system are built through MATLAB and DIgSILENT PowerFactory software. The simulation results show that the proposed control algorithm is useful for mitigating voltage rise and reverse power flow in the MV distribution grid with the PV generation systems.

关键词： Reactive power management medium voltage distribution grid inverter-based photovoltaic distributed generation voltage regulation particle swarm optimization algorithm

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A Survey of Artificial Intelligence algorithm in Power System Applications 3

A Survey of Artificial Intelligence Algorithm in Power Syste...

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3rd IEEE International Electrical and Energy Conference (CIEEC)

作者： Cai, Hongwei Lu, Xiaodan Du, Ting Wang, Yixian Xia, Shiwei Zhang, Dongying State Grid Beijing Elect Power Co Beijing Peoples R China North China Elect Power Univ Sch Elect & Elect Engn Beijing Peoples R China

ISBN: (纸本)9781728116754

With the power network expansion and the grid-connection of intermittent renewable energy, more and more non-convex optimization problems emerge in power system, which cannot be effectively solved by the derivative based traditional methods. As a powerful branch of optimization techniques, artificial intelligence method can well address these non-convex problems, providing a promising solution for power system engineering. In this paper, five typical artificial intelligence algorithms including the particle swarm optimization algorithm, Tabu Search, Genetic algorithm, Simulated Annealing and Artificial Neural Network are investigated for their advantages and disadvantages, and the main application in power system for these artificial intelligence algorithms arc also discussed.

关键词： Power System Artificial Intelligent algorithms particle swarm optimization algorithm Tabu Search Genetic algorithm Simulated Annealing Artificial Neural Network

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Non-uniformly spaced linear antenna array design by means of PEEC approach applying Cheetah optimization algorithm

Non-uniformly spaced linear antenna array design by means of...

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15th Biennial International Workshop on optimization and Inverse Problems in Electromagnetism (OIPE)

作者： Moreno, Sinvaldo R. Klein, Carlos E. Mariani, Viviana C. Coelho, Leandro dos S. Alotto, Piergiorgio Torchio, Riccardo Bauernfeind, Thomas Baumgartner, Paul Univ Fed Parana Dept Elect Engn Curitiba Parana Brazil Pontificia Univ Catolica Parana Ind Syst Engn Grad Program Curitiba Parana Brazil Pontificia Univ Catolica Parana Dept Mech Engn Curitiba Parana Brazil Univ Padua Dipartimento Ingn Ind Padua Italy Graz Univ Technol Inst Fundamentals & Theory Elect Engn Graz Austria

This paper presents the application of the Partial Element Equivalent Circuit (PEEC) approach, which is a full wave electromagnetic modelling technique for conductors embedded in arbitrary dielectrics based on equivalent circuits, to the optimal design of antennas with non-uniform spacing between the array elements. The design optimization problem is solved by means of the new nature-inspired Cheetah metaheuristic. The main aim of this paper is to introduce the Cheetah optimization algorithm to the electromagnetics and antenna community. The results are compared to two well-known optimization algorithms and to show the effectiveness of the proposed algorithm on a realistic benchmark problem.

关键词： Antenna array Cheetah optimization algorithm genetic algorithm partial element equivalent circuit particle swarm optimization algorithm

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Short Term Load Forecasting and Early Warning of Charging Station Based on PSO-SVM

Short Term Load Forecasting and Early Warning of Charging St...

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International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS)

作者： Liao Xiaoqun Kang Xiaofan Ma Li Cao Nanlan Xian Univ Sci & Technol Xian 710054 Shaanxi Peoples R China

ISBN: (纸本)9781728113074

In this paper, a short-term load forecasting model and a load early warning model for charging station based on PSO-SVM are proposed. particle swarm optimization (PSO) is used to optimize the parameters of support vector machine (SVM) model, and the PSO-SVM load forecasting model for the optimal nuclear parameters of charging station is established according to the normalized root mean square error (NRMS). On the basis of it, a load warning model of charging station is established and verified by an example. Experiments show that the short-term load forecasting model based on PSO-SVM and the load forecasting model of charging station meet the requirements of forecasting and forecasting accuracy.

关键词： Load Forecasting Optimal Kernel Parameters Support Vector Machine particle swarm optimization algorithm Load Early Warning

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The Study of Characteristics of the Hybrid particle swarm algorithm in Solution of the Global optimization Problem 5

The Study of Characteristics of the Hybrid Particle Swarm Al...

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5th Mediterranean Conference on Embedded Computing (MECO)

作者： Demidova, Liliya Klyueva, Irina Pylkin, Alexander Ryazan State Radio Engn Univ Ryazan Russia

ISBN: (纸本)9781509022212

The present paper considers convergence characteristics of the particle swarm algorithm and its modification - the hybrid PSO-GS algorithm obtained under combination of the PSO algorithm and Grid Search algorithm. Comparison of quality indices of the particle swarm algorithm and the steepest descent algorithm has been carried out for evaluation of advantages of the PSO algorithm in comparison with classical optimization algorithms.

关键词： particle swarm optimization algorithm grid search algorithm hybridization solution of problems of the global unconstrained optimization

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Research on the temperature field model of plate hot rolling process based on CUDA 3

Research on the temperature field model of plate hot rolling...

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3rd International Conference on Fluid Mechanics and Industrial Applications (FMIA)

作者： Liu, Wenhong Guo, Siying Zhang, Siyu Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China

The current temperature field model of plate rolling process is generally based on CPU programming, due to the influence of computer performance, the accuracy and speed of the model can not be improved at the same time. To solve this problem, this paper studies the temperature field model with particle swarm optimization to modify the heat transfer coefficients, and the parallel program of this model is written under CUDA architecture, on premise of ensuring the accuracy of the model, the computation speed of the model is improved. To get the best acceleration, this paper analyzes the factors affecting GPU performance, the accuracy and speed of the temperature field model before and after modification are compared under the best acceleration configuration. Final temperature field model calculation error reduced to an average of 15.57., better than the model based on the empirical formula, the computing speed is also improved, which is 1.78 times that of CPU.

关键词： Temperature field model Parallel computing CUDA architecture particle swarm optimization algorithm

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Dynamic Responses of PI^λ, PD^δ, and PI^λD^δ Controllers for Prosthetic Hand Model Using PSO algorithm 19

Dynamic Responses of PI<SUP>λ</SUP>, PD<SUP>δ</SUP>, and P...

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19th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Batiba, Iqbal M. El-Khazali, Reyad Momani, Shaker Univ Jordan Fac Sci Dept Math Amman 11942 Jordan Khalifa Univ ECCE Dept Abu Dhabi 127788 U Arab Emirates Ajman Univ Coll Humanities & Sci Dept Math & Sci Ajman U Arab Emirates

ISBN: (纸本)9781728153414

Prosthetic hand is a device designed to help those with full or partial hand loss retain the function and appearance of a regular hand. It has been shown that such device needs to be enhanced in the control capabilities and functional devising. Thus, a robust design is required to enhance the performance of prosthetic hand model, and also improve existing capabilities to the optimum level. The objective of this paper is to design and analyze the Fractional-order Proportional Integral (PI lambda), Fractional-order Proportional Derivative (PD delta), and Fractional-order Proportional Integral Derivative ((PID delta)-D-lambda) controllers for the model under consideration, in order to realize accurate control with high performance. The effect of each controller on the dynamics of a closed-loop system has been discussed and analyzed. Tuning parameters for each controller has been done using particle swarm optimization (PSO) algorithm via El-Khazali's approach. Different simulated comparisons reveal that the performance of (PID delta)-D-lambda-controller is outperform than other controllers in terms of rise time, settling time and overshoot.

关键词： prosthetic hand model (PID delta)-D-lambda-controller particle swarm optimization algorithm Laplacian operator El-Khazali's approach

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Thermal Chips Layout Method in MCM Based on an Improved particle swarm algorithm 31

Thermal Chips Layout Method in MCM Based on an Improved Part...

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31st Chinese Control And Decision Conference (CCDC)

作者： Ning, Ye Jie, Yang Ye, Tao Northeastern Univ Sch Informat Sci & Engn Shenyang 110819 Peoples R China

ISBN: (纸本)9781728101057

The emergence of Multichip Module(MCM) means that the development of component technology is greatly improved in number, speed and performance. Research on thermal layout optimization methods for MCM can promote its reliability, this paper established a numerical relationship model between junction temperature and coordinates of each chip. and uses ANSYS to simulate and analyze the temperature profile of the optimization results. This paper compares several typical optimization schemes based on (W) and presents the improved particle swarm algorithm. Experimental results show that improved particle swarm algorithm can improve inertia weight and maximum speed effectively, and also can achieve lower chip junction temperature in chip layout.

关键词： Multi-chip Module(MCM) particle swarm optimization algorithm Thermal Layout optimization Inertia Weight

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Multi-objective reactive power optimization in power system based on improved PSO-OSA algorithm 14

Multi-objective reactive power optimization in power system ...

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14th IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Song Bo Cao Yujie Zhang Xiang Wang Yelin Li Ning Xian Univ Technol Inst Water Resources & Hydroelect Engn Xian Shaanxi Peoples R China Xian Univ Technol Sch Automat & Informat Engn Xian Shaanxi Peoples R China China Ship Dev & Design Ctr Wuhan 430064 Hubei Peoples R China Xian Kenuo Network & Informat Secur Technol Inst Xian Shaanxi Peoples R China

ISBN: (纸本)9781538694909

With the rapid development of Chinese economy, the power industry is playing a more and more important role in the development of Chinese economy. The optimal reactive power in the power system plays an important role in the voltage stability of the power system and reducing the loss of active power. The calculation results of particle swarm optimization algorithm, oriented search algorithm and PSO - OSA hybrid algorithm in reactive power optimization of power system is compared, and the performance of the proposed method has been tested on the IEEE 30-bus systems in this paper. The simulation results show that the proposed method is able to produce well distributed Pareto optimal solutions for the optimal reactive power problem.

关键词： Optimal reactive power Multi-objective probelem particle swarm optimization algorithm Oriented search algorithm

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