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

A photovoltaic array fault diagnosis method based on an adaptive neural fuzzy inference system

A fuzzy inference system, photovoltaic array technology, applied in inference methods, photovoltaic power generation, character and pattern recognition, etc.

Active Publication Date: 2019-04-23
FUZHOU UNIV
View PDF3 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of this, the object of the present invention is to provide a photovoltaic array fault diagnosis method based on an adaptive neuro-fuzzy reasoning system, to overcome the defects of the existing related technologies, so as to more quickly and accurately realize fault detection and Classification

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
  • A photovoltaic array fault diagnosis method based on an adaptive neural fuzzy inference system
  • A photovoltaic array fault diagnosis method based on an adaptive neural fuzzy inference system
  • A photovoltaic array fault diagnosis method based on an adaptive neural fuzzy inference system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0056] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0057] Please refer to figure 1 , the present invention provides a photovoltaic array fault diagnosis method based on an adaptive neuro-fuzzy reasoning system, comprising the following steps:

[0058] Step S1: collect photovoltaic electrical characteristic data under various working conditions, and form original fault data through sampling and filtering; the photovoltaic electrical characteristic data includes the maximum power point voltage of the photovoltaic array, the maximum power point current of the photovoltaic string, The real-time photovoltaic panel temperature and real-time irradiance are shown in Table 1.

[0059] Table 1. Operating parameters of the photovoltaic array

[0060]

[0061]

[0062] Step S2: carry out data mapping operation respectively to the original fault data obtained, obtain overall fault feature data; Described ori...

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 relates to an intelligent photovoltaic array fault diagnosis method based on an adaptive neural network, and the method comprises the following steps of S1, collecting photovoltaic electrical characteristic data under various working conditions, and forming original fault data through the sampling and filtering processing; S2, performing data mapping operation on the original fault data to obtain overall fault feature data; S3, performing feature dimension reduction compression on the overall fault feature data to three dimensions by using an LDA algorithm to obtain new feature data; S4, dividing the new feature data into a test set and a training set by adopting K-fold cross inspection, and setting the number of membership functions and the types of the membership functions;S5, generating an initial fuzzy inference system; S6, constructing an adaptive neural network fuzzy inference system model; S7, judging whether the photovoltaic array system is in a fault state or not. The technology of the invention can effectively diagnose and classify the photovoltaic array in the fault, and compared with other machine learning algorithms, the classification precision is highand the result is accurate.

Description

technical field [0001] The invention relates to the field of photovoltaic array fault detection and classification, in particular to a photovoltaic array fault diagnosis method based on an adaptive neuro-fuzzy reasoning system. Background technique [0002] With the intensification of the global chemical energy crisis, clean energy has attracted widespread attention, and solar energy is a very important member of clean energy due to its unique advantages. According to the report of the National Bureau of Statistics, in 2017, the national power generation was 6.5 trillion kwh, an increase of 5.9% over the previous year. Among them, thermal power increased by 5.1%, hydropower increased by 0.5%, nuclear power increased by 16.3%, wind power increased by 24.4%, and solar power increased by 57.1%. The demand for solar energy is increasing, and the installed capacity of photovoltaic power plants is increasing. However, due to its outdoor environment, photovoltaic power plants are ...

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): G06K9/62G06N5/04
CPCG06N5/048G06F18/21322G06F18/21324G06F18/24G06F18/214Y02E10/50
Inventor 陈志聪甘雨涛吴丽君林培杰程树英
Owner FUZHOU UNIV
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