Remote intelligent diagnosis method of photovoltaic module dust deposition degree

A technology of intelligent diagnosis and photovoltaic modules, applied in the direction of instruments, biological neural network models, data processing applications, etc., can solve the problems of lack of cleaning strategies, unconsidered cleaning costs, loss of power generation, etc., and achieve the effect of saving cleaning costs

Active Publication Date: 2018-03-20
CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
View PDF6 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Most of these documents involve the design of high-efficiency dust removal devices and the selection methods of various cleaning methods, without considering the cost of cleaning, loss of power generation and other indicators
There is no online diagnosis method for

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
  • Remote intelligent diagnosis method of photovoltaic module dust deposition degree
  • Remote intelligent diagnosis method of photovoltaic module dust deposition degree
  • Remote intelligent diagnosis method of photovoltaic module dust deposition degree

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0046] The technical solutions of the present invention will be further described in detail below in conjunction with specific embodiments.

[0047] The actual data of two different time periods (case 1 and case 2) of a photovoltaic power station in Gansu will be used as a specific example to describe it in detail below. figure 1 .

[0048] Step 1: For historical samples of different weather types in different seasons, respectively establish a photovoltaic output prediction model based on a fuzzy neural network in a clean state, and calculate the theoretical output value of a photovoltaic panel in a clean state according to the model. Depend on figure 2 As shown, the historical data of the clean power generation of photovoltaic power plants and the solar irradiance, atmospheric temperature, and relative humidity provided by the weather station are divided into sunny days, cloudy days, and rainy days in different seasons to establish a training sample database. The neural ne...

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 present invention discloses a remote intelligent diagnosis method of a photovoltaic module dust deposition degree, belonging to the field of photovoltaic optimization operation technology. The method comprises the steps of: respectively establishing photovoltaic output prediction models based on a fuzzy neural network in a cleaning state for different weather type history samples, and calculating a theoretical output value in the photovoltaic cleaning state according to the models; comparing a cleaning state prediction value Pst with a real-time collected photovoltaic actual output value Pout; determining whether a dust deposition loss electric quantity reaches a cleaning cost E or not, if the dust deposition loss electric quantity reaches the cleaning cost E, defining time from the last cleaning to a current moment is T1, and fitting a daily generating capacity decay function F(x); calculating cost of reaching n-times dust deposition starting from the T1 moment according to the daily generating capacity decay function F(x), wherein this period of time is marked as T2; and determining whether a rainfall capacity in the T2 moment satisfies a dust deposition washing threshold ornot, if the rainfall capacity in the T2 moment satisfies the dust deposition washing threshold, giving up this cleaning and waiting for rainfall to remove dust, or else, immediately organizing cleaning work. The remote intelligent diagnosis method of a photovoltaic module dust deposition degree saves the cleaning cost at the greatest extent.

Description

technical field [0001] The invention belongs to the technical field of photovoltaic optimization operation, and relates to a remote intelligent diagnosis method for the dust accumulation degree of photovoltaic modules. Background technique [0002] The cost of photovoltaic operation and maintenance accounts for about 1% of the cost of the power station. If the cost of a photovoltaic power station is 7 yuan / W, the cost of operation and maintenance is about 0.07 yuan / W. At the end of 2016, the total installed photovoltaic capacity in the country was 77.42GW, and the photovoltaic operation and maintenance market exceeded 5 billion yuan. According to the "Thirteenth Five-Year Plan", the target of photovoltaic installed capacity in China in 2020 will be more than 105GW, and according to the recent installation plans proposed by local governments in China, the total installed photovoltaic capacity in 2020 is expected to exceed 147GW. The scale will reach 7 billion to 10 billion y...

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): G06Q10/06G06Q10/04G06Q10/00G06Q50/06G06N3/04
CPCG06Q10/04G06Q10/0637G06Q10/20G06Q50/06G06N3/045
Inventor 姜飞吴震宇涂春鸣李印宜李浩刘振磊王大朔
Owner CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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