Wind power system reactive power planning method based on golden section cloud particle swarm optimization algorithm

A golden section and cloud particle swarm technology, applied in the field of power information, can solve problems such as excessive voltage fluctuations and unsatisfactory voltage quality

Inactive Publication Date: 2013-10-09
SHANGHAI JIAO TONG UNIV +2
View PDF1 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a wind power system reactive power planning method based on the cloud particle swarm optimization algorithm of the go

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
  • Wind power system reactive power planning method based on golden section cloud particle swarm optimization algorithm
  • Wind power system reactive power planning method based on golden section cloud particle swarm optimization algorithm
  • Wind power system reactive power planning method based on golden section cloud particle swarm optimization algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0048] The invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0049] The above-mentioned disclosure is only a specific embodiment of the present invention, which is only used to illustrate the present invention more clearly, but not to limit the present invention. Any changes that those skilled in the art can think of should fall within the scope of protection Inside.

[0050] Such as figure 1 As shown, the present invention provides a wind power system reactive power planning method based on the cloud particle swarm optimization algorithm of the golden section, comprising the following steps:

[0051] S1: Establish a mathematical model of wind turbines in a power grid containing wind turbines: the change of output power of the wind farm comes from the fluctuation of wind speed and wind direction. From the relationship between the wind turbine and the wind speed V, the power generated by the wind turbine is:

[0...

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 wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm. The wind power system reactive power planning method comprises the steps that a reactive power planning mathematic model is built, and a target function is determined; original data of a wind power system is input, and therefore an initial population is formed; all particles are generated randomly, a golden section judging criterion is used for dividing a particle swarm into three parts according to the self-fitness value of the particle swarm, and different inertia weight is set for each part of particles; new positions and speeds of the particles are obtained through the particle swarm optimization algorithm, the particles are divided into three parts and iterated repeatedly according to the method before an the end condition is met, an optimal solution is searched, and therefore reactive power planning of the wind power system is achieved. According to the wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm, the node voltage level of the wind power system is effectively improved, network loss of a power network is reduced, the diversity of the particles is kept according to the algorithm, the prematurity phenomenon which easily occurs during optimization searching is avoided, and convergence rate in the optimization searching process is improved. In addition, the wind power system reactive power planning method based on the golden section cloud particle swarm optimization algorithm is small in calculated amount, and higher in operability.

Description

technical field [0001] The invention relates to the field of electric power information technology, in particular to a reactive power planning method of a wind power system based on a cloud particle swarm optimization algorithm of the golden section. Background technique [0002] Wind energy is a cheap renewable energy, and wind-based power generation technology has attracted more and more people's attention. Due to the randomness, intermittent and uncontrollable nature of wind, when large-scale wind power is connected to the grid, the wind turbine needs to absorb a large amount of reactive power, which will cause a sharp increase in network loss, and the voltage fluctuation problem caused by it is becoming more and more prominent. In severe cases, it will cause grid voltage flicker and voltage collapse. [0003] Optimizing operation is an important task in the construction of smart grid, and the access of wind power provides a new means of adjustment for the optimization o...

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): H02J3/18G06N3/00
CPCY02E10/76Y02E40/30
Inventor 王昕郑益慧李立学王希王太金许宇辉王新宇
Owner SHANGHAI JIAO TONG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap