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Based on Improved Particle Swarm Optimization with power grid planning

Author: GuoJuXin
Tutor: LiYanQing
School: North China Electric Power University
Course: Proceedings of the
Keywords: Improved PSO Distribution network Grid optimization Network Reconfiguration
CLC: TM715
Type: Master's thesis
Year: 2011
Downloads: 116
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Abstract


Modern power distribution network is an important part of the system , one of its tasks is to get from the power supply or the power grid directly assigned to different voltage levels of the user. Distribution network structure planning distribution network planning optimization is the focus of this work for good , can greatly improve the efficiency of investment distribution network for flexible and reliable operation of the distribution network and lay a good foundation. This article first distribution network structure models were studied, a non- deterministic model . Then PSO algorithm is studied through improved strategic analysis , an improved particle swarm optimization. Then, using the improved particle swarm algorithm for distribution network structure conducted in-depth research , and the distribution network reconfiguration , distribution network fault isolation recovery were studied . Finally, specific examples of projects to verify the feasibility of the algorithm . The main research results and the specific contents are as follows : ( a ) Consider the distribution network planning uncertainty , we propose a change of uncertainty based on load distribution network structure optimization model that enables Distribution Network more realistic engineering optimization model for distribution network structure optimization program selected has laid a good foundation. ( 2 ) In this paper, the flatness of the fitness function information on the particle swarm algorithm for dynamic inertia factor was improved. The improved algorithm makes full use of objective functions, so that the search direction inspired enhancements . In order to improve the diversity of particle , immune algorithm is introduced by the concentration of selection mechanism , PSO has been improved. Through simulation experiments found that this improved algorithm effectively enhances the diversity of particle , convergence speed, avoid the particle swarm algorithm easy to fall into local optimal solution shortcomings. ( 3 ) the improved PSO successfully applied to the actual distribution of power grid planning and optimization . Through analysis of the results of the planning , found that the algorithm converges fast, high precision and overcome the iterative optimization process of \( 4 ) In this paper, based on improved particle swarm optimization Distribution Network Reconfiguration , fault isolation, recovery conducted a preliminary study by the actual numerical results verify the feasibility .

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CLC: > Industrial Technology > Electrotechnical > Transmission and distribution engineering, power network and power system > Theory and Analysis > Power system planning
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