This paper researches economic operation of wind-PV-ES hybrid micro-grid. Firstly, operational strategy of micro-grid and its energy system are proposed. Then the economic operation optimization model is built and par...
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ISBN:
(纸本)9781467356688
This paper researches economic operation of wind-PV-ES hybrid micro-grid. Firstly, operational strategy of micro-grid and its energy system are proposed. Then the economic operation optimization model is built and particle swarm optimization algorithm is simulated with MATLAB. Based on a practical wind-PV-ES hybrid micro-grid, the simulated results give the optimization cost according to the load and wind power/PV output prediction under kinds of typical weather condition. The results comparison shows that the proposed optimization method is useful to reduce operational cost.
Image registration based on mutual information is of high accuracy and ***,it has received much attention these ***,the mutual information function is generally not a smooth function but one containing many local maxi...
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Image registration based on mutual information is of high accuracy and ***,it has received much attention these ***,the mutual information function is generally not a smooth function but one containing many local maxima,which has a large influence on *** has fewer parameters to control and can find the best solution quickly and guarantee to be global *** paper proposes a registration method based on wavelet *** this method the mutual information is used as the similarity measure and a hybrid algorithm combined by PSO algorithm and a mutation the search *** method is applied to the 2D registration of *** results show that this registration method could efficiently restrain local maxima of mutual information function and not only it can improve accuracy and speed but also the subvoxel accuracy can be achieved.
This study used the complex dynamic characteristics of chaotic systems and Bluetooth to explore the topic of wireless chaotic communication secrecy and develop a communication security system. The PID controller for c...
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This study used the complex dynamic characteristics of chaotic systems and Bluetooth to explore the topic of wireless chaotic communication secrecy and develop a communication security system. The PID controller for chaos synchronization control was applied, and the optimum parameters of this PID controller were obtained using a particleswarmoptimization (PSO) algorithm. Bluetooth was used to realize wireless transmissions, and a chaotic wireless communication security system was developed in the design concept of a chaotic communication security system. The experimental results show that this scheme can be used successfully in image encryption.
Stocks diversity is the precondition for ensuring the convergence of PSO algorithm. The definition of stocks diversity is clear and the operand is small, moreover which was analyzed by particle evolution degree and ag...
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Stocks diversity is the precondition for ensuring the convergence of PSO algorithm. The definition of stocks diversity is clear and the operand is small, moreover which was analyzed by particle evolution degree and aggregation degree. A changed algorithm was proposed based on adjusting weight adaptively. The algorithm ensures population diversity and avoids premature convergence effectively. Simulation results indicate that this algorithm not only speeds up the population the evolution speed, but also strengthens the algorithm the overall situation astringency, and convergence of probability also increases from 15% to 100%.
A novel multi-agent particle swarm optimization algorithm (MAI'SO) is proposed for optimal reactive power dispatch and voltage control of power system. The method integrates multi-agent system (MAS) and particle s...
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ISBN:
(纸本)9780878492138
A novel multi-agent particle swarm optimization algorithm (MAI'SO) is proposed for optimal reactive power dispatch and voltage control of power system. The method integrates multi-agent system (MAS) and particle swarm optimization algorithm (PSO). An agent in *** represents a particle to PSO and a candidate solution to the optimization problem. All agents live in a lattice-like environment, with each agent fixed on a lattice-point. In order to decrease fitness value, quickly, agents compete and cooperate with their neighbors. and they can also use knowledge. Making use of these agent interactions and evolution mechanism of ***. MAPSO realizes the purpose of minimizing the value of objective function. MAPSO applied for optimal reactive power is evaluated on an IEEE 30-bus power system. It is shown that the proposed approach converges to better solutions much faster than the earlier reported approaches
particleswarmoptimization (PSO) algorithm is a well-known optimization approach to deal with discrete problems. There are two models proposed for the operators of PSO algorithm, one is based on value exchange and th...
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particleswarmoptimization (PSO) algorithm is a well-known optimization approach to deal with discrete problems. There are two models proposed for the operators of PSO algorithm, one is based on value exchange and the other on order exchange, accordingly two versions of PSO algorithms are formed. A new version of PSO algorithm based on order exchange has been presented in our studies, which is capable of converging on the global optimization solution, with the method of generating the stop evolution particle over again. In this paper, we propose another version of PSO algorithm based on value exchange with the same method. There exist, thus, totally four versions of PSO algorithms, which is given a brief introduction individually and the performance of which are compared in solving sequence optimization problems through fifty runs. The performance comparison show that the PSO algorithm with global convergence characteristics based on order exchange outperforms the other versions of PSO in solving sequence optimization problem. (C) 2011 Elsevier Ltd. All rights reserved.
In this paper, a nonlinear model predictive controller is presented for idle speed control (ISC) problem of spark ignition (SI) engine. The objective is to maintain the engine speed at a prescribed set-point through a...
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In this paper, a nonlinear model predictive controller is presented for idle speed control (ISC) problem of spark ignition (SI) engine. The objective is to maintain the engine speed at a prescribed set-point through actuating a electronic throttle, and minimize the effects of load torque disturbances and model uncertainties. The nonlinear programming (NLP) problem formed by nonlinear model predictive control (NMPC) is solved by using particleswarmoptimization (PSO) algorithm. Simulation results show that the designed nonlinear model predictive controller can achieve satisfactory performance for ISC.
The deformation of seamless steel pipe rolling process is complex due to material and geometrical nonlinearity, so it's hard to design pass and optimize rolling schedule. With the analysis of rolling for PQF, a me...
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ISBN:
(纸本)9781479900305
The deformation of seamless steel pipe rolling process is complex due to material and geometrical nonlinearity, so it's hard to design pass and optimize rolling schedule. With the analysis of rolling for PQF, a method of pass design and optimization method based on the finite element modeling is presented. On the basis of pass design, the finite element simulation model is established. Considering the checking condition of pass design and rack load balanced allocation, the paper establishes an appraisal model based on the finite element modeling to evaluate pass design. Finally, as the evaluation function serves as the objective function, the paper uses particle swarm optimization algorithm to optimize specific elongation. These not only develop new products but also enhance the state rolling process characteristics (dimensional accuracy and internal and external surface quality).
The direct-drive permanent magnet synchronous generator (DDPMSG) for wind power system uses a back-to-back double PWM converter. PI controller based on decoupling control strategies is used to control generator side c...
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ISBN:
(纸本)9781467363204
The direct-drive permanent magnet synchronous generator (DDPMSG) for wind power system uses a back-to-back double PWM converter. PI controller based on decoupling control strategies is used to control generator side converter and grid side converter. But the parameters of the PI controller are difficult to obtain correctly. Though manual tuning method is applied to regulate the parameters, the method would waste a lot of time and greatly depend on the experience. The paper analyses the mathematical model of direct-drive permanent magnet synchronous wind power generation system. It presents a particleswarmoptimization (PSO) method for determining the parameters of PI controller for PMSG to improve the control ability. PSO is powerful stochastic evolutionary algorithm that is used to find the global optimum solution in search space. Under the condition of wind speed mutation, the simulation results of PMSG system after PI parameter optimization show that the PI control with PSO algorithm can fit the real value. The PSO controller has fast convergence rate, strong adaptability and good dynamic performance.
Time to time, many researchers have suggested modifications to the standard particleswarmoptimization to find good solutions faster than the evolutionary algorithms, but they could be possibly stuck in poor region o...
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Time to time, many researchers have suggested modifications to the standard particleswarmoptimization to find good solutions faster than the evolutionary algorithms, but they could be possibly stuck in poor region or diverge to unstable situations. For overcoming such problems, this paper proposes new Fast Convergence particleswarmoptimization (FCPSO) approach based on balancing the diversity of location of individual particle by introducing a new parameter, particle mean dimension (Pmd) of all particles to improve the performance of PSO. The FCPSO method is tested with five benchmark functions by variable dimensions and fixed size population and compared with PSO & Constriction factor approach of PSO (CPSO). Finally, search performances of these methods on the benchmark functions are tested.
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