Heat supply energy saving control method and system based on neural network prediction

An energy-saving control system and neural network technology, applied in the field of heating energy-saving research, can solve the problems of the temperature not reaching the set value, the system cannot be adjusted, and the time setting is too large, so as to reduce energy consumption, reduce carbon emissions, boosting effect

Active Publication Date: 2016-07-27
CHANGZHOU ENGIPOWER TECH
View PDF6 Cites 37 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The existing heating system control unit cannot automatically adjust the time required for the system to start in advance according to the heating system control unit and the indoor and outdoor temperature of the building. If the time setting is too large, the system will run at high speed prematurely, wasting energy; time setting is too small, the indoor temperature cannot reach the set value within the specified time

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 energy saving control method and system based on neural network prediction
  • Heat supply energy saving control method and system based on neural network prediction
  • Heat supply energy saving control method and system based on neural network prediction

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0034] Such as figure 1 As shown, the present invention provides a heating energy-saving control method, comprising the following steps:

[0035] Step S1, establishing a neural network prediction model;

[0036] Step S2, control the heating system control unit through the neural network predictive model to make the building reach the desired room temperature at the set time.

[0037] Preferably, the method for establishing a neural network prediction model in the step S1 includes the following steps:

[0038] Step S11, collecting sample data required to establish a neural network prediction model;

[0039] Required sample data include: flow rate of heating hot water inlet, hot water temperature (heating hot water inlet temperature), initial indoor temperature, outdoor temperature;

[0040] Step S12, according to the sample data and the start-up time of the heating system control unit and the set time data corresponding to the room temperature reaching the set temperature, a...

Embodiment 2

[0082] On the basis of Embodiment 1, the present invention also provides a heating energy-saving control system.

[0083] Such as Figure 4 and Figure 5 As shown, the heating energy-saving control system includes: a data acquisition unit, which collects the sample data required to establish a neural network prediction model; a neural network modeling and prediction unit connected to the data acquisition unit, which is suitable for combining the heating system with the sample data A neural network predictive model is established based on the set time data corresponding to the starting time of the control unit and the room temperature reaching the set temperature, and the control unit of the heating system is controlled through the neural network predictive model to make the building reach the desired room temperature at the set time.

[0084] The heating energy-saving control system also includes: a remote communication unit, which is located at the client end, and is used to...

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 relates to a heat supply energy saving control method and system based on neural network prediction. The heat supply energy saving control method comprises the following steps that (S1) a neural network prediction model is built; and (S2) a heat supply system control unit is controlled through the neural network prediction model to enable a building to reach an anticipant room temperature at set time. Through a remote communication unit and a task control unit, users can set the temperature demands of the building locally or through remote equipment, that is, the indoor temperature reaches the set temperature at the appointed time. The control method and system, provided by the invention, can predict optimal advance starting time of a heat supply system according to the operation history data of the heat supply system and the hot water flow, the hot water temperature, the indoor temperature and the outdoor temperature at the present time, finishes the starting of the heat supply system through a heat supply system control unit to realize reduction of the energy consumption under the precondition of satisfying the heat supply demands, and is excellent in economic benefit and social benefit.

Description

technical field [0001] The invention relates to a heating energy-saving control method and system based on neural network prediction, which can realize the prediction of the time required for a building from the start of heating to the indoor temperature heating to a set value during the heating process, and through the heating The control of a system control unit realizes model predictive control of building heating, and belongs to the technical field of heating energy saving research. Background technique [0002] With the improvement of people's living environment requirements, heating system control units are used in a large number of buildings in cold winter cities. For commercial office buildings, government office buildings, schools and other buildings, the heating time and heat load vary greatly with time, and the continuous operation of the heating system consumes a lot of energy. Therefore, intermittent heating is required for different buildings. Optimize control...

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): F24D19/10
CPCF24D19/1009
Inventor 陈孝武于春娣董朝艳郝静麒
Owner CHANGZHOU ENGIPOWER 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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap