HVAC Automatic Control Architecture for Partial-Load Energy Savings
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing HVAC energy management systems rely heavily on human intervention and lack comprehensive automatic control logic, leading to inefficient energy consumption in buildings.
Innovation Solution
A system comprising a data intake module, data storage module, process module, and control module that collects data from sensors and manual inputs, processes it, and automatically controls HVAC equipment such as fans, pumps, dampers, and valves to optimize energy usage and maintain design conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If HVAC energy management systems rely on human intervention for control, then operational flexibility is maintained, but energy consumption efficiency deteriorates due to lack of automatic optimization
Solution Approach 1:
The control system is segmented into four distinct modules: data intake module (800) for collecting operational parameters, data storage module (810) for storing building information and operational data, process module (820) for executing control logic, and control module (830) for implementing actual control actions. This segmentation allows automatic control functionality to be added without creating a monolithic complex system, as each module has a specific function and can be independently configured and maintained.
Solution Approach 2:
The system performs preliminary actions by pre-storing building information, HVAC system specifications, design conditions, and operational parameters in the data storage module before actual control operations begin. The process module also pre-establishes control sequences and logic based on these stored parameters, enabling automatic optimization to occur without real-time human intervention while maintaining system flexibility through pre-configurable parameters.
2Productivity
If monitoring systems are used without automatic control logic, then system simplicity is maintained, but energy management effectiveness deteriorates
Solution Approach 1:
The control module receives real-time operational data from sensors through the data intake module and compares actual system performance against stored design conditions and optimal parameters. Based on this feedback, the process module automatically adjusts control sequences to optimize energy consumption while maintaining comfort conditions. This closed-loop feedback mechanism enables effective energy management without requiring complex manual monitoring and adjustment procedures.
Solution Approach 2:
The HVAC system performs self-service through automatic control where the process module autonomously determines optimal operating parameters and the control module automatically implements control actions based on real-time conditions. The system uses stored building information and operational data to self-adjust without human intervention, significantly improving energy management effectiveness while the modular architecture prevents excessive complexity by limiting the scope of automatic control to specific functions.
Data Source
AI summary
The present invention relates to a system and method of HVAC (Heating, Ventilating, Air Conditioning) energy management system. More specially, the present invention provides a system and method that can provide automatic optimized control mechanism for HVAC system to save energy.