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Improved particle swarm algorithm-based distributed power locating and sizing optimization method and system

A technology of distributed power supply and improved particle swarm, applied in system integration technology, information technology support system, computing and other directions, can solve the problems of trapping in local optimum, trapping in local optimum, low convergence accuracy, etc., to improve convergence , the effect of improving the convergence performance and reducing the amount of calculation

Inactive Publication Date: 2018-10-12
STATE GRID SHANDONG ELECTRIC POWER
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Problems solved by technology

However, the algorithm also has problems such as low convergence accuracy and easy to fall into local optimum. Although some optimization algorithm researchers have improved the traditional particle swarm optimization algorithm, the convergence performance of the improved algorithm has been significantly improved, but there is still the problem of falling into local optimum. possible

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  • Improved particle swarm algorithm-based distributed power locating and sizing optimization method and system
  • Improved particle swarm algorithm-based distributed power locating and sizing optimization method and system
  • Improved particle swarm algorithm-based distributed power locating and sizing optimization method and system

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Embodiment Construction

[0049] The present invention will be further described below in conjunction with accompanying drawing.

[0050] The meaning of each symbol in the text is defined as follows:

[0051] w begin and w end are the initial and final values ​​of the inertia weight w, respectively, is the velocity of each particle in the next iteration, is the velocity of each particle in the current iteration, k+1 is the next iteration number, k is the current iteration number, and is a random number between [0,1] in the current iteration, is the position of each particle in the current iteration, x pi is the position of the current individual optimal solution.

[0052]It should be noted that the following detailed description is exemplary and intended to provide further explanation of the present invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belo...

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Abstract

The invention discloses an improved particle swarm algorithm-based distributed power locating and sizing optimization method and system. The method comprises the steps of building an OpenDSS-based distributed power model and a power distribution network simulation model comprising distributed power; obtaining power flow distribution of a power distribution network connected with the distributed power; building an optimized objective function of network connection of the distributed power, and determining a constraint condition; and generating an initial population by taking position and capacity information of the distributed power as position information of individuals, and optimizing the position and capacity of the distributed power by adopting an improved particle swarm algorithm. Theinstallation position and capacity of the distributed power during connection with the power distribution network are optimized by adopting the improved particle swarm algorithm to reduce the situations of increased system network loss and reduced voltage stability caused by unreasonable installation position and capacity of the distributed power, thereby guaranteeing safe production and stable operation of the power distribution network comprising the distributed power.

Description

technical field [0001] The invention relates to a method and system for optimizing the location and capacity of distributed power sources based on the improved particle swarm algorithm. Background technique [0002] At present, the commonly used distributed power generation site selection and capacity optimization methods include classical genetic algorithm, particle swarm optimization algorithm, ant colony algorithm and Tabu search algorithm, etc. Among them, particle swarm optimization algorithm is a more classic and widely used optimization method. Particle swarm algorithm is a parallel algorithm, which was proposed by Dr. Eberhart and Dr. Kennedy when they studied the behavior of bird predation. It is suitable for solving nonlinear and non-differentiable complex optimization problems. Because the algorithm is simple, easy to implement and needs to be adjusted. Not much, it is used in many disciplines and fields of engineering. However, the algorithm also has problems su...

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Application Information

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IPC IPC(8): G06Q10/04G06N3/00G06N3/12G06Q50/06
CPCG06N3/006G06N3/126G06Q10/04G06Q50/06Y02E40/70Y04S10/50
Inventor 聂萌徐珂马松王洋刘文哲李强荆树志程金田运涛
Owner STATE GRID SHANDONG ELECTRIC POWER
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