Distributed set point configuration in heating, ventilation, and air-conditioning systems
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Solution Overview
Problem
Existing HVAC systems face inefficiencies and challenges in managing complex building structures due to the lack of effective methods for generating optimal supply stream temperature set-points, particularly in hierarchically structured systems.
Innovation Solution
A computer-implemented method utilizing distributed reinforcement learning to generate supply stream temperature set-points by identifying hierarchical positions and potential set point configuration actions, determining overall cost measures, and optimizing set-points based on upstream and downstream costs within HVAC systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed reinforcement learning techniques are implemented to generate optimal supply stream temperature set-points, then system efficiency and scalability are improved, but computational complexity and processing requirements increase
Solution Approach 1:
The HVAC system is divided into multiple distribution channel elements organized in a hierarchical architecture, where each element can independently determine set-points based on local conditions and hierarchical position, reducing centralized computational complexity while maintaining system-wide efficiency
Solution Approach 2:
A hierarchical dimension is introduced to the control architecture, organizing distribution channel elements into levels based on their position in the system. This hierarchical structure enables distributed decision-making by allowing elements to consider upstream and downstream costs at different hierarchical levels, improving scalability without proportionally increasing computational burden
2Adaptability or versatility
If hierarchical control methods are implemented across complex building structures, then scalability is improved, but system complexity and control difficulty increase
Solution Approach 1:
The system segments the building's HVAC distribution network into hierarchical levels based on physical location and functional dependencies. Each segment (distribution channel element) operates semi-independently, determining set-points based on its hierarchical position, which enables the system to scale to complex buildings without proportionally increasing control difficulty
Solution Approach 2:
Each distribution channel element is赋予 different control authorities and decision-making capabilities based on its hierarchical position. Elements at different levels apply different cost considerations (upstream and downstream costs vary by position), allowing the system to adapt to local conditions while maintaining overall scalability
Data Source
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AI summary
Method, apparatus and computer program product for generating a supply stream temperature set-point for a particular distribution channel element associated with a heating, ventilation, and air-conditioning (HVAC) system. In one example, a method includes identifying a hierarchical position of the particular distribution channel element; identifying potential set point configuration actions associated with the particular distribution channel element, wherein each potential set point configuration action is expected to cause transition of the particular distribution channel element from a current state to a future state; determining an overall cost measure for each potential set point configuration action based at least in part on the hierarchical position of the particular distribution channel element, and generating the supply stream temperature set-point based on each overall cost measure associated with a potential set point configuration action.