Supercharge Your Innovation With Domain-Expert AI Agents!

Design method for topological structure of power transmission network based on multi-agent genetic algorithm

A technology of network topology and genetic algorithm, applied in the direction of genetic law, design optimization/simulation, calculation, etc., can solve the problems of weak deep search ability and poor robustness, and achieve the improvement of local search ability, robustness, search ability and so on. powerful effect

Active Publication Date: 2017-08-18
广州元生信息技术有限公司
View PDF10 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the deficiencies in the prior art above, and propose a method for designing a topology structure of an electric power transportation network based on a multi-agent genetic algorithm, which is used to solve the problem of deep search existing in the method for designing a topology structure of an existing electric power transportation network Weak ability and easy to fall into local optimal solution, leading to technical problems of poor robustness of power transportation network against attacks or disturbances

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Design method for topological structure of power transmission network based on multi-agent genetic algorithm
  • Design method for topological structure of power transmission network based on multi-agent genetic algorithm
  • Design method for topological structure of power transmission network based on multi-agent genetic algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0045] refer to figure 1 , a method for designing a topology structure of an electric power transportation network based on a multi-agent genetic algorithm, including the following steps:

[0046] Step 1. Set the parameters of the multi-agent genetic algorithm, and use the population obtained by the multi-agent genetic algorithm as the topology structure of the power transportation network to be designed. The set parameters include the population size Ω of the multi-agent genetic algorithm equal to 9, and domain contention probability P 0 Equal to 0.5, neighborhood intersection probability P c Equal to 0.5, mutation probability P m Equal to 0.6, local search probability P l is equal to 0.8 and the maximum number of iterations N is equal to 30000.

[0047] Step 2, initialize the population of the multi-agent genetic algorithm, obt...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a design method for a topological structure of a power transmission network based on a multi-agent genetic algorithm and aims at solving the technical problem of poor robustness when the power transmission network resists attack or disturbance due to weak deep search capability and easiness in falling into the local optimum in an existing design method for the topological structure of the power transmission network. The design method comprises the following realization steps: setting parameters of the multi-agent genetic algorithm; initializing a population of the multi-agent genetic algorithm; carrying out neighborhood competition on the initialized population; carrying out neighborhood intersection on the neighborhood competition; mutating neighborhood intersection species; carrying out population local search on a mutated population to generate a local search population serving as a topological structure output of the power transmission network. According to the design method provided by the invention, in the design process of the topological structure of the power transmission network, a multi-agent genetic algorithm framework is adopted, a neighborhood competition operator, a neighborhood intersection operator, a mutation operator and a local search operator are designed, and the topological structure with high robustness of the power transmission network is designed out.

Description

technical field [0001] The invention belongs to the field of physical technology, and relates to a method for designing a topology structure of an electric power transportation network, in particular to a method for designing a topology structure of an electric power transportation network based on a multi-agent genetic algorithm. When attacked or disturbed, the function of the power transportation network can be kept intact to the greatest extent, and at the same time, it can effectively resist the attacked or disturbed. Background technique [0002] In the power transportation system, power stations, substations, etc. can be abstracted into complex network nodes, and transmission lines can be regarded as connection edges, then the power transportation system can be abstracted into a complex network model, called the power transportation network. The topology design of the power transportation network is to adjust the topology of the power transportation network while keepi...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F17/50G06N3/12
CPCG06F30/18G06F30/20G06N3/126
Inventor 刘静焦李成安柏慧
Owner 广州元生信息技术有限公司
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More