HVAC Zoning Configuration Using Building Layout and Usage Data
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Solution Overview
Problem
Current HVAC systems lack an efficient method to dynamically configure and optimize their operations based on building structure and usage patterns, leading to suboptimal comfort and energy usage.
Innovation Solution
A system that includes a user interface and processing module to accept building information, determine suggested HVAC configurations, and display them to users, utilizing a cloud server with a communications block, memory, and controller to analyze and output configurations, allowing for remote user interaction and centralized control of HVAC components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If HVAC systems use traditional static configuration methods, then system simplicity is maintained, but comfort optimization and energy efficiency are compromised
Solution Approach 1:
The system performs preliminary analysis of building information (floor plans, HVAC component locations, thermal zones) before operation to pre-determine optimal HVAC configurations. This allows the system to adapt to different building layouts and usage patterns without requiring complex real-time calculations during HVAC operation, thus improving adaptability while managing complexity.
Solution Approach 2:
A cloud-based processing server acts as an intermediary between the user interface and HVAC control systems. This intermediary handles the complex computational tasks of analyzing building information and determining optimal configurations, allowing the local HVAC system to remain relatively simple while achieving advanced adaptability through the cloud-based processing layer.
2Productivity
If HVAC systems implement dynamic configuration based on building information, then comfort and energy efficiency are improved, but system complexity increases
Solution Approach 1:
The system automatically analyzes building information and determines optimal HVAC configurations without requiring manual intervention from HVAC specialists. The processing module self-services by taking building data as input and generating configuration recommendations, reducing the need for complex manual programming while improving energy efficiency through optimized configurations.
Solution Approach 2:
The system incorporates user feedback and operational data to continuously refine HVAC configurations. By monitoring comfort levels and energy consumption, the system adjusts configurations iteratively, improving productivity over time while the feedback loop manages complexity through learning from actual performance rather than requiring perfect initial configurations.
3Ease of operation
If HVAC configuration determination is centralized on cloud server, then remote user interaction is enabled, but system response time may increase
Solution Approach 1:
The cloud server performs preliminary processing of building information and pre-calculates optimal HVAC configurations during off-peak times or when changes are made to building data. This preliminary action reduces the response time required when users need configuration adjustments, as the system can quickly retrieve pre-computed recommendations rather than performing full analyses in real-time.
Solution Approach 2:
The system implements a two-level configuration approach: cloud-based comprehensive analysis for overall system optimization, and local controller-level adjustments for rapid response to immediate conditions. This partial centralization enables remote user interaction for strategic decisions while maintaining fast local response times for operational adjustments, balancing convenience and speed.
Data Source
AI summary
A system for developing HVAC system configurations for a building may develop suggested HVAC system configurations based, at least in part, on obtained building information. A user interface may accept building information that at least partially defines an interior or exterior of a building. The building information may include, among other information, current HVAC system configuration information for an HVAC system of the building including current locations of register vents within the building. A processing module in communication with the user interface may determine one or more suggested HVAC system configurations based, at least in part, on building information accepted at the user interface. The user interface may display the suggested one or more HVAC system configurations to a user.