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

Building heating ventilation air conditioning load optimization control method based on partial linear model

A load optimization control and HVAC technology, applied in mechanical equipment and other directions, can solve the problems that simple models cannot be applied to real scenarios, optimal control, and complex data-driven models, so as to reduce energy consumption costs, improve efficiency, and reduce electricity consumption. effect of cost

Active Publication Date: 2021-08-03
TSINGHUA UNIV
View PDF13 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] To sum up, the existing simple model of HVAC load cannot be applied to real scenarios; the data-driven model is too complex, and it is difficult to optimize the control on this basis

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
  • Building heating ventilation air conditioning load optimization control method based on partial linear model
  • Building heating ventilation air conditioning load optimization control method based on partial linear model
  • Building heating ventilation air conditioning load optimization control method based on partial linear model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0055] The optimal control method for building HVAC loads based on a partial linear model proposed by the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments; it should be understood that the specific embodiments described here can be used to explain the present invention, but not limit the invention;

[0056] The building HVAC load optimization control method based on the partial linear model proposed by the present invention first establishes the thermal inertia model and the HVAC system model of the building respectively, and converts the two models to obtain a linear part and a data-driven model. Part of the HVAC load forecasting model, using historical data fitting to obtain the parameters of the HVAC load forecasting model; then according to the HVAC load forecasting model, an optimization model for building indoor temperature is established, and the optimized model is solved to calculate The ...

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 building heating ventilation air conditioning load optimization control method based on a partial linear model, and belongs to the technical field of power demand response. The method comprises the following steps: firstly, respectively establishing a thermal inertia model and a heating ventilation air conditioning system model of a building, converting the two models to obtain a heating ventilation air conditioning load prediction model comprising a linear part and a data driving part, and carrying out fitting by utilizing historical data to obtain parameters of the load prediction model; and then according to the load prediction model, establishing an optimization model of the indoor temperature of the building, solving the optimization model, obtaining the optimal indoor temperature of the building at the next time point through calculation, and realizing optimization control over the heating ventilation air conditioning load of the building. According to the method, a physical model and a data driving model are combined, so that the heating ventilation air conditioning prediction model has interpretability and high prediction precision at the same time, the indoor temperature can be optimized according to the model under the real-time electricity price, and the energy consumption cost of the building is reduced on the premise that the indoor temperature is kept within a certain comfortable range.

Description

technical field [0001] The invention belongs to the field of power demand response, and in particular proposes a building HVAC load optimization control method based on a partial linear model. Background technique [0002] With the acceleration of the global urbanization process, the construction industry consumes more and more energy, causing nearly 40% of the global greenhouse gas emissions. HVAC systems account for nearly 50% of a building's energy consumption. Due to the thermal inertia of buildings, HVAC is a typical electrothermal coupled load that can adjust electricity demand in a short period of time with little impact on user comfort, and has the potential to provide flexibility to the grid. Proper demand-side management can greatly improve the economics of grid operation, which requires modeling and optimal control of HVAC loads. [0003] Many literatures have confirmed the application of HVAC systems in demand response, such as implementing optimal control of i...

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): F24F11/46F24F11/63
CPCF24F11/46F24F11/63
Inventor 钟海旺何一鎏谭振飞夏清康重庆
Owner TSINGHUA UNIV
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