Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Microgrid Capacity Optimal Location Method Based on Improved Ant Colony Algorithm

A technology of ant colony algorithm and capacity optimization, which is applied in calculation, calculation model, biological model, etc., to achieve the effect of optimizing search range, strong search ability and good robustness

Active Publication Date: 2017-06-23
ZHEJIANG UNIV OF TECH
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, at present, the research on the micro-grid capacity optimization location method based on the improved ant colony algorithm has not yet appeared, and the present invention studies this method

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
  • Microgrid Capacity Optimal Location Method Based on Improved Ant Colony Algorithm
  • Microgrid Capacity Optimal Location Method Based on Improved Ant Colony Algorithm
  • Microgrid Capacity Optimal Location Method Based on Improved Ant Colony Algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] 1. Project implementation method

[0042] The microgrid capacity optimization location method based on the improved ant colony algorithm includes the following steps:

[0043] 1) Build a wind and solar power generation island microgrid model with battery stations as a simulation model for studying the microgrid capacity optimization location method based on the improved ant colony algorithm;

[0044] The micro-source model constructed by the micro-grid system is as follows:

[0045] 1-1) Use the Weibull distribution to process the wind speed and establish the mathematical model of the fan;

[0046] 1-2) Use the Beta distribution to process the light and establish the mathematical model of the photovoltaic panel;

[0047] 1-3), use the state of charge (SOC) parameters to establish a mathematical model for battery charge and discharge, and combine relevant parameters to evaluate the efficiency of battery charge and discharge;

[0048]2) Construct a multi-objective mode...

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 discloses a micro-grid capacity address optimizing and distributing method based on an improved ant colony algorithm. The method includes the following steps that a wind and light power generation island micro-grid model including a storage battery station is built up and serves as a simulation model for studying the micro-grid capacity optimizing and address distributing method based on the improved ant colony algorithm; a multi-target model for micro-grid capacity optimizing and address distributing is constructed, a micro-grid comprehensive operation target function is determined, the improved ant colony algorithm is designed to solve the multi-target model.

Description

technical field [0001] The project of the present invention relates to a micro-grid capacity optimization addressing method, especially a micro-grid capacity optimization addressing method based on an improved ant colony algorithm. Background technique [0002] At present, the capacity optimization of the microgrid has always been a major problem in the construction of the microgrid. The unreasonable distribution of micro-sources in the micro-grid will have a certain impact on the power consumption of lines or users, and the external environment will also affect the power generation performance of micro-sources. At present, some intelligent optimization algorithms have been applied to solve this problem, such as particle swarm algorithm, genetic algorithm and differential evolution algorithm. However, the particle swarm optimization algorithm is prone to fall into local optimal solutions when dealing with discrete problems such as micro-source placement; the genetic algorit...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/00H02J3/00
Inventor 王雪锋王肖杰张颖陈骏宇龚余峰王晶骆旭伟
Owner ZHEJIANG UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products