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

Intelligent operation and maintenance method based on ensemble learning photovoltaic forecasting

An integrated learning and photovoltaic technology, applied in forecasting, instrumentation, data processing applications, etc., can solve problems such as untimely maintenance, impact on power station revenue and power generation efficiency, and difficulty in determining where problems have occurred in the power station, so as to achieve the effect of reducing investment

Inactive Publication Date: 2019-01-15
SHANGHAI ANYO ENERGY SAVING TECH
View PDF7 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The components of a photovoltaic power station are provided by many manufacturers. Without professional knowledge, it is difficult to determine where there is a problem in the power station. The corresponding manufacturer cannot be found, and maintenance is not timely, which will affect the revenue and power generation efficiency of the power station.
In addition, some power stations are scattered and distributed in remote areas. Once a failure occurs, it is difficult to carry out operation and maintenance.

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
  • Intelligent operation and maintenance method based on ensemble learning photovoltaic forecasting
  • Intelligent operation and maintenance method based on ensemble learning photovoltaic forecasting
  • Intelligent operation and maintenance method based on ensemble learning photovoltaic forecasting

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0023] figure 1 It is a flow chart of the intelligent operation and maintenance method based on ensemble learning photovoltaic prediction in the present invention.

[0024] See figure 1 , the intelligent operation and maintenance method based on integrated learning photovoltaic prediction provided by the present invention includes the following steps: S1: preprocessing the historical photovoltaic data of the power station collected by the photovoltaic monitoring cloud platform; S2: performing feature correlation on the data processed in step S1 Analyze and determine the strong correlation factors that affect the output power of power generation; S3: use the integrated learning boosting algorithm to build a photovoltaic prediction model, and fit the data; compare and analyze the model performance of different algorithms; S4: train the photovoltaic predi...

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 an intelligent operation and maintenance method based on integrated learning photovoltaic prediction, comprising the following steps: S1, preprocessing the historical photovoltaic data of a power station collected by a photovoltaic monitoring cloud platform; S2, pre-processing the historical photovoltaic data of the photovoltaic monitoring cloud platform; S2, analyzing thecharacteristic correlation of the pre-processed data to determine the strong correlation factors affecting the output power of the power generation quantity; 3, establishing a photovoltaic predictionmodel and fitting data; S4, training the photovoltaic prediction model and optimizing the model; 5, embedding a photovoltaic prediction model into a photovoltaic monitoring platform, inputting data inreal time to obtain a prediction value, comparing the prediction value with the actual value, and setting a deviation interval; S6: guiding the operation and maintenance of the power station according to the interval where the deviation value in step S5 is located. The intelligent operation and maintenance method based on the integrated learning photovoltaic prediction provided by the invention predicts the photovoltaic power through the integrated learning algorithm and embeds the photovoltaic prediction model into the photovoltaic monitoring cloud platform, thereby improving the construction quality of the power station, reducing the later operation and maintenance cost of the power station and reducing the artificial input.

Description

technical field [0001] The invention relates to an intelligent operation and maintenance method for photovoltaic prediction, in particular to an intelligent operation and maintenance method for photovoltaic prediction based on integrated learning. Background technique [0002] In recent years, due to its clean, pollution-free and renewable characteristics, solar energy has attracted more and more public attention. At the same time, photovoltaic power generation has become a research hotspot in the field of renewable energy in the world today. However, due to the uncertainty and intermittent characteristics of photovoltaic power, large-scale photovoltaic grid-connected operation will increase the difficulty of grid dispatching and affect the safe, stable and economical operation of the power system. Accurate prediction of photovoltaic power is the premise to effectively mitigate the adverse impact of large-scale photovoltaic grid-connected on the power grid, and it has impor...

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 Applications(China)
IPC IPC(8): G06Q10/04G06Q10/00G06Q10/06G06Q50/06
CPCG06Q10/04G06Q10/0631G06Q10/20G06Q50/06Y04S10/50
Inventor 宋晓菲洪本浩万源
Owner SHANGHAI ANYO ENERGY SAVING 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