Unlock instant, AI-driven research and patent intelligence for your innovation.

Photovoltaic power combination prediction method and system based on multi-source data fusion

A technology of power combination and multi-source data, applied in forecasting, data processing applications, resources, etc., can solve problems such as hard to find, and achieve the effect of improving accuracy, universality and strong portability

Pending Publication Date: 2021-07-16
CHINA SOUTHERN POWER GRID COMPANY +2
View PDF2 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, affected by changes in weather conditions, the ultra-short-term fluctuation characteristics of irradiance and power data are various, and each prediction algorithm also has its own limitations. It is still difficult to find an algorithm theory that is applicable to any weather condition.

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
  • Photovoltaic power combination prediction method and system based on multi-source data fusion
  • Photovoltaic power combination prediction method and system based on multi-source data fusion
  • Photovoltaic power combination prediction method and system based on multi-source data fusion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0039] According to an embodiment of the present invention, a photovoltaic power combination prediction method based on multi-source data fusion is disclosed, referring to figure 1 , including the following steps:

[0040] (1) Acquire historical power generation power series data and external meteorological data on the day to be predicted;

[0041] (2) The data are respectively input into the trained convolutional neural network sub-prediction model, the long short-term memory network sub-prediction model and the extreme gradient enhanced tree sub-prediction model for photovoltaic power prediction;

[0042] (3) Carry out the classification of weather type according to the cloud amount index of the day to be predicted, and then determine the prediction weight of each sub-forecast model;

[0043] (4) Fusing the prediction results of the sub-prediction models above based on the weights to obtain a final photovoltaic power prediction result.

[0044] This embodiment fully consid...

Embodiment 2

[0104] According to an embodiment of the present invention, a photovoltaic power combination prediction system based on multi-source data fusion is disclosed, including:

[0105] The data acquisition module is used to acquire historical power generation sequence data and external meteorological data on the day to be predicted;

[0106] The power prediction module is used to input the data into the trained convolutional neural network sub-prediction model, the long short-term memory network sub-prediction model and the extreme gradient enhanced tree sub-prediction model to perform photovoltaic power prediction;

[0107] The prediction weight module is used to classify the weather type according to the cloud index of the day to be predicted, and then determine the prediction weight of each sub-forecast model;

[0108] A data fusion module, configured to fuse the prediction results of the above sub-prediction models based on the weights to obtain a final photovoltaic power predic...

Embodiment 3

[0111] According to an embodiment of the present invention, an embodiment of a terminal device is disclosed, which includes a processor and a memory, the processor is used to implement instructions; the memory is used to store multiple instructions, and the instructions are suitable for being loaded and executed by the processor The photovoltaic power combination prediction method based on multi-source data fusion described in the first embodiment.

[0112] In other embodiments, a computer-readable storage medium is disclosed, in which a plurality of instructions are stored, and the instructions are suitable for being loaded by the processor of the terminal device and executing the multi-source data fusion method described in Embodiment 1. Photovoltaic power combination forecasting method.

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 photovoltaic power combination prediction method and system based on multi-source data fusion. The method comprises the following steps: acquiring historical generated power sequence data and external meteorological data of a day to be predicted; respectively inputting the data into a trained convolutional neural network sub-prediction model, a long and short-term memory network sub-prediction model and an extreme gradient enhancement tree sub-prediction model for photovoltaic power prediction; classifying weather types according to the cloud cover index of the day to be predicted, and determining the prediction weight of each sub-prediction model; and fusing the prediction results of the sub-prediction models based on the weights to obtain a final photovoltaic power prediction result. According to the method, data information of various different architectures is integrated, the characteristics of historical power data, meteorological data and satellite cloud picture data are fully analyzed, and then unified information which is better and richer than single data is fused.

Description

technical field [0001] The present invention relates to the technical field of photovoltaic power combination prediction, in particular to a photovoltaic power combination prediction method and system based on multi-source data fusion. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] With the increasing contradiction between global warming and energy crisis, sustainable clean energy has developed rapidly in the past few years. Solar energy is an inexhaustible source of energy and is considered to be the most popular alternative to traditional energy sources. Therefore, the proportion of photovoltaic power generation connected to the grid has been increasing in recent years. According to statistics, the total installed capacity of photovoltaics has exceeded 400GW. However, the intermittent and fluctuating characteristics of solar energy h...

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): G06Q10/04G06Q10/06G06Q50/06G06N3/04
CPCG06Q10/04G06Q10/067G06Q50/06G06N3/044G06N3/045Y04S10/50G05B2219/2639G06N3/0442G06N3/0464G06N5/01G06N20/20G06N3/086G06N3/126G05B19/042
Inventor 杨明司志远王皓怀于一潇和识之邓韦斯车建峰王勃
Owner CHINA SOUTHERN POWER GRID COMPANY