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

A Method of Forecasting Thermal Load of Thermal Power Station Using Pattern Recognition Technology

A pattern recognition and heat load technology, applied in forecasting, data processing applications, instruments, etc., can solve the problems of secondary heating pipeline complexity and process parameters that are difficult to measure, measure data, and cannot be calculated, so as to reduce personnel Labor load, improved prediction accuracy, and reasonable effect of response speed

Active Publication Date: 2021-09-07
BEIJING HUAYUAN HEAT SUPPLY PIPE NETWORK CO LTD
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The reasons are mainly due to the differences in heat dissipation conditions of buildings for heating users in different thermal stations, the complexity of the influence of outdoor air temperature, wind force, illumination and other climatic conditions on the indoor temperature of heating users, the complexity of the secondary heating pipelines of thermal stations and It is difficult to measure process parameters with measurement data; the delay time of heat supply from thermal station to user heat supply cannot be calculated due to the influence of the above complex factors

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 Method of Forecasting Thermal Load of Thermal Power Station Using Pattern Recognition Technology
  • A Method of Forecasting Thermal Load of Thermal Power Station Using Pattern Recognition Technology
  • A Method of Forecasting Thermal Load of Thermal Power Station Using Pattern Recognition Technology

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0034] Embodiment 1, the present invention provides a kind of method utilizing pattern recognition technology to predict the thermal load of thermal power station, it comprises the following steps:

[0035] S1: Install the existing indoor environment temperature monitoring equipment in the user's home, and set the user's indoor environment temperature value in four periods according to the monitored indoor temperature data; wherein, the four periods are respectively morning, afternoon, night and early morning, The specific time of early morning, morning, afternoon and evening is:

[0036] 0-6 am;

[0037] 6-12 am;

[0038] 12-18 pm;

[0039] 18-24 in the evening;

[0040] In this embodiment, the set values ​​of the user's indoor ambient temperature for the four periods are 22°C, 20°C, 22°C and 18°C ​​respectively;

[0041] S2: the next day's weather forecast data (outdoor ambient temperature, wind, etc.) are divided into four periods (morning, afternoon, night and early mo...

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 method for predicting the thermal load of a thermal station by using pattern recognition technology, comprising: S1: installing temperature monitoring equipment, and setting the indoor environment temperature value; S2: dividing the next day's weather forecast into the same time period as S1 , and calculate the average value; S3: Calculate and sort the historical chronological data set through the Euclidean distance algorithm for the data obtained by S1 and S2, and obtain the historical chronological data in ascending order; S4: Obtain the minimum Euclidean distance according to several forecast periods According to the historical record corresponding to the distance, a number of relevant parameters of the original corresponding thermal station are obtained; S5: the secondary delivery water temperature or instantaneous heat load of the thermal station corresponding to the minimum Euclidean distance in the historical moment is the dependent variable, and the corresponding indoor related factors of the user are self- variable, get the time delay; S6:1 minus the maximum correlation coefficient, get the correction coefficient value, calculate the predicted heat load of the next day; calculate and analyze the predicted heat load value of the heat source plant, and finally realize the joint adjustment of the source, network and station .

Description

technical field [0001] The invention relates to a method for predicting heat load, in particular to a method for predicting heat load of a heat station by using pattern recognition technology. Background technique [0002] At present, in the heating industry around the world, there is no industry-recognized calculation model and algorithm for heat load forecasting based on thermal stations. The reasons are mainly due to the differences in heat dissipation conditions of buildings for heating users in different thermal stations, the complexity of the influence of outdoor air temperature, wind force, illumination and other climatic conditions on the indoor temperature of heating users, the complexity of the secondary heating pipelines of thermal stations and Process parameters are difficult to measure with measurement data; the delay time from heat station to user heat supply cannot be calculated due to the influence of the above complex factors. Contents of the invention ...

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 Patents(China)
IPC IPC(8): G06Q10/04G06Q50/06
Inventor 李海滨于治国梅德芳张海增程天才吴佳滨关向东于悦
Owner BEIJING HUAYUAN HEAT SUPPLY PIPE NETWORK CO LTD
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com