Longitudinal photovoltaic power prediction method based on historical data mining

A technology of historical data and forecasting methods, applied in the field of solar energy utilization research, can solve problems that cannot meet practical needs and have poor results

Inactive Publication Date: 2017-09-22
BEIJING INFORMATION SCI & TECH UNIV +3
View PDF5 Cites 17 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The above two methods have been applied in photovoltaic power prediction, but there are some limitations in the method. For example, for data information with strong regularity and periodicity, these two prediction m...

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
  • Longitudinal photovoltaic power prediction method based on historical data mining
  • Longitudinal photovoltaic power prediction method based on historical data mining
  • Longitudinal photovoltaic power prediction method based on historical data mining

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0067] The present invention proposes a photovoltaic power longitudinal prediction method based on historical data mining. The embodiments will be described in detail below in conjunction with the accompanying drawings.

[0068] figure 1 It is a flow chart of longitudinal prediction of photovoltaic power based on similar cloud fusion, as shown in the figure:

[0069] Step 1. Collect the output power data of the photovoltaic power station, and the sampling time interval is 15 minutes. Select the D-day historical photovoltaic power data in a certain season in the previous year for statistical analysis, and obtain six statistical indicators such as the mean value, standard deviation, coefficient of variation, kurtosis, skewness, and output sum in the corresponding season, and perform normalization processing . The calculation and normalization methods of statistical features are as follows:

[0070] (1) Average output P mean : The average value of output describes the relativ...

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 belongs to the field of research of solar energy utilization, and in particular relates to a longitudinal photovoltaic power prediction method based on historical data mining. The longitudinal photovoltaic power prediction method comprises the steps of: performing statistical analysis for historical photovoltaic power data in different seasons at first, so that six statistical indexes of photovoltaic power in corresponding seasons are obtained; clustering the statistical indexes by utilizing the Euclidean distance, so that similar day matrixes under different weather conditions in different seasons, and forming similar day typical curves and distribution intervals through a one-dimensional forward cloud generator; realizing longitudinal photovoltaic power prediction at the corresponding times in 24 hours in the future by utilizing the Markov Chain theory, and fusing the prediction value with the similar day typical curves and distribution intervals, so that a new prediction value is formed; and finally, performing weighted fusion of the new prediction value and the prediction value obtained through a continuous prediction method through a one-dimensional reverse cloud generator. Thereby, longitudinal photovoltaic power prediction based on historical data similar cloud fusion is realized; and thus, the photovoltaic power prediction precision is further increased.

Description

technical field [0001] The invention belongs to the field of solar energy utilization research, and in particular relates to a longitudinal prediction method of photovoltaic power based on historical data mining. Background technique [0002] Compared with water energy, wind energy, geothermal energy, biomass energy, etc., solar energy has become the focus of people's attention because of its outstanding and unique advantages. Abundant solar radiation energy is inexhaustible and inexhaustible, and photovoltaic power generation devices are noiseless, pollution-free, cheap, flexible in scale, and easy for human beings to freely and widely use. According to statistics, the energy of solar energy reaching the ground every second is as high as 800,000 kilowatts. If 0.1% of the solar energy on the earth's surface is converted into electrical energy, and the conversion rate is 5%, the annual power generation can reach 5.6×1012 kWh, which is equivalent to 40 times the world's total...

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): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y04S10/50
Inventor 杨秀媛徐铭璐徐寿臣王春玲韩晓娟
Owner BEIJING INFORMATION SCI & TECH 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