This paper deals with the problem of network reconfiguration of distribution networks with high proportional Distributed Generation(DG). Firstly, this paper studies the types of Distributed Generation and their charac...
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ISBN:
(纸本)9781538685495
This paper deals with the problem of network reconfiguration of distribution networks with high proportional Distributed Generation(DG). Firstly, this paper studies the types of Distributed Generation and their characteristics, discusses the influence of distributed power supply to distribution network, and studies their computing model. Secondly, the forward and backward substitution method is introduced to calculate the load flow. Then, the reconfiguration model of distribution network is established, and the objective function of Pareto multi-objective optimization is to minimize the loss of the net and voltage deviation and to maximize reliability. This paper uses the Prim's algorithm to generate the radiation network and uses the binary particle swarm optimization algorithm to achieve network reconfiguration. At the same time, the strategy of randomly initializing velocity vectors is adopted to prevent the local optimal. At last, the optimization analysis of the 33-node of the distribution network is carried out, and good results are obtained, which verifies the validity and convergence of the algorithm.
To reduce the influence of wind power output uncertainty on power system stable operation, demand response (DRPs) and energy storage system (ESSs) are introduced while solving scheduling optimization problems of syste...
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To reduce the influence of wind power output uncertainty on power system stable operation, demand response (DRPs) and energy storage system (ESSs) are introduced while solving scheduling optimization problems of system with wind power. To simulate wind power scenarios, this paper used interval method to generate the initial scenario set, and construct scenario reduction strategy based on Kantorovich distance. Then, DRPs and ESSs are respectively introduced in the demand-side and generation side, taking wind power day-ahead forecasting and ultra-short-term forecasting as a random variable and its implementation, a two-stage scheduling optimization model for wind energy storage systems is construct combined with two stage optimization theory. To solve the proposed model, the ergodic of chaos search is applied to improve the inadequate that binaryparticleswarmalgorithm may fall into local optimum, chaotic binary particle swarm optimization algorithm is proposed. Finally, example simulation is made in the IEEE36 node 10 machine systems to analyze the influence of energy storage system and demand response on system's wind power consumptive capacity. The result shows chaotic binaryparticleswarmalgorithm can get a global optimal solution, applicable to solve wind power energy storage systems two-stage model. The synergies of DRPs and ESSs can be used to suppress wind power uncertainty, improve the utilization efficiency of wind power, and reduce coal consumption level with significantly overall efficiency. (C) 2014 Elsevier Ltd. All rights reserved.
A new global path planning approach based on binary particle swarm optimization algorithm (BPSO) for a mobile robot is presented. The detailed realization of the approach is illustrated. The obstacles in the robot'...
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ISBN:
(纸本)9781424416752
A new global path planning approach based on binary particle swarm optimization algorithm (BPSO) for a mobile robot is presented. The detailed realization of the approach is illustrated. The obstacles in the robot's environment are described as polygons and the vertexes of obstacles are numbered from 1 to n. binaryparticleswarmoptimization is used to plan the path. The length of the particle is the number of the vertexes. Every bit in the particle may be 1 or 0 which represents whether the vertex is in the path or not. To avoid converging too fast (the algorithm stops when the optimal path is not found), the algorithm is improved and the mutation operation is used. Simulation results are provided to verify the effectiveness and practicability of this approach.
In this paper the hot lots problem on semiconductor wafer fabrication is studied. Corresponding mathematical model whose object is to minimize the total cost of produce and transport is made. The method based on Binar...
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ISBN:
(纸本)9781424436705
In this paper the hot lots problem on semiconductor wafer fabrication is studied. Corresponding mathematical model whose object is to minimize the total cost of produce and transport is made. The method based on binary particle swarm optimization algorithm is proposed to solve this problem. The detailed realization of the method is illustrated, and an example is presented, the simulation results compared to solved by lingo software proves that the BPSO method is effective and stable.
This paper shows the performance of the binary PSO algorithm as a classification system. These systems are classified in two different perspectives: the Pittsburgh and the Michigan approaches. In order to implement th...
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ISBN:
(纸本)0780393635
This paper shows the performance of the binary PSO algorithm as a classification system. These systems are classified in two different perspectives: the Pittsburgh and the Michigan approaches. In order to implement the Michigan Approach binary PSO algorithm, the standard PSO dynamic equations are modified, introducing a repulsive force to favor particle competition. A dynamic neighborhood, adapted to classification problems, is also defined. Both classifiers are tested using a reference set of problems, where both classifiers achieve better performance than many classification techniques. The Michigan PSO classifier shows clear advantages over the Pittsburgh one both in terms of success rate and speed. The Michigan PSO can also be generalized to the continuous version of the PSO.
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