Heat supply system load prediction method, device and system based on building classification

A technology of load forecasting and heating system, applied in forecasting, instrument, character and pattern recognition, etc., can solve problems such as supply and demand mismatch, large energy waste, thermal inertia, etc., to improve user experience and reduce energy waste.

Inactive Publication Date: 2020-09-11
CHANGZHOU COLLEGE OF INFORMATION TECH
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The heating system is a complex dynamic system. The heat energy supply side has large fluctuations due to the diversification of heat sources and access to clean energy; the heat network side has the characteristics of large lag, strong coupling, and thermal inertia; the demand side uses energy and distributes it according to needs. Volatility brought about by formula energy supply
If the actual heating system adopts traditional feedback control, due to the large

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
  • Heat supply system load prediction method, device and system based on building classification
  • Heat supply system load prediction method, device and system based on building classification
  • Heat supply system load prediction method, device and system based on building classification

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0021] Example one

[0022] Such as figure 1 As shown, the present invention includes the following steps:

[0023] Step 1: Obtain historical measurement data of variables related to the heating system load. Obtain historical measurement data of various variables that may affect the load of the heating system, denoted as X r ={x 1 (k) r ,x 2 (k) r ,...,x n (k) r }, where x i (k) r (i=1, 2,...n) is the unprocessed historical measurement data sequence of the i-th variable at time k. The variables include system variables directly monitored by the heating system and disturbance variables from the outside. System variables monitored by the heating system, for example: primary water supply temperature T 1s , A return water temperature T 1r , An instantaneous flow M 1 , Heating power station heating load Q 1 Etc.; disturbance variable from outside: outdoor temperature T out .

[0024] Step 2: Preprocessing the collected historical data.

[0025] 1) Duplicate and missing values ​​are proc...

Example Embodiment

[0037] Example two

[0038] Based on the same inventive concept as the first embodiment, the present invention also provides a heating system load forecasting device, such as Figure 4 As shown, it includes: a data acquisition unit, used to obtain historical measurement data of variables that affect the load of the heating system; a preprocessing unit, used to preprocess the historical measurement data; an analysis unit, used to perform analysis on different building types The thermal power station is used for thermal analysis to determine the input factors of the thermal power station load prediction model; the model training unit uses the pre-processed historical data corresponding to the input factors to train the thermal power station load prediction model; the prediction unit uses the thermal power station The load forecasting model predicts the load of the corresponding thermal station.

Example Embodiment

[0039] Example three

[0040] Such as image 3 As shown, the present invention also provides a heating system load forecasting system based on building classification, including a database and a load forecasting unit, the database storing real-time measurement data of the heating system; the load forecasting unit from the database The data is extracted and processed according to the method in the first embodiment, so as to realize the prediction of the heating load of the corresponding building type thermal power station in the database.

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 provides a heat supply system load prediction method based on building classification, and the method is characterized in that the method comprises the following steps: obtaining historical measurement data of variables affecting the load of a heat supply system; preprocessing the historical measurement data; carrying out thermal characteristic analysis on thermal stations of different building types, and determining input factors of a thermal station load prediction model; training a heating station load prediction model by adopting the preprocessed historical data correspondingto the input factors; and predicting the load of the corresponding heating station by using the heating station load prediction model. According to the invention, the supply load of the target heating station can be predicted, so that the supply side load is matched with the demand side demand load.

Description

technical field [0001] The invention relates to a heating system load prediction method, device and system based on building classification, belonging to the field of intelligent heating system prediction control. Background technique [0002] With the acceleration of the urbanization process and the enhancement of the concept of environmental protection, energy conservation and emission reduction, it has become a hot spot in the heating industry to realize on-demand precise heating and reduce energy consumption under the premise of ensuring the quality of heating supply. The heating system is a complex dynamic system. The heat energy supply side has large fluctuations due to the diversification of heat sources and access to clean energy; the heat network side has the characteristics of large lag, strong coupling, and thermal inertia; the demand side uses energy and distributes it according to needs. The volatility brought about by formula energy supply. If the actual heati...

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): G06Q10/04G06Q50/06G06Q50/08G06K9/62
CPCG06Q10/04G06Q50/06G06Q50/08G06F18/2321G06F18/24
Inventor 王瑶朱川常兴治龙霄汉刘威
Owner CHANGZHOU COLLEGE OF INFORMATION TECH
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