Toolchain for HVAC system design configuration
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Solution Overview
Problem
HVAC system design, installation, and retrofitting in buildings often rely on expert knowledge, which can be limited by the complexity of configuration variations, environmental considerations, and control options, leading to suboptimal performance in energy efficiency and comfort.
Innovation Solution
A system that uses an energy conservation measures database to determine base load profiles, modify them based on building envelope parameters, and simulate HVAC configuration options to select optimal control configurations, enhancing performance indicators such as energy consumption and comfort level through automated design configuration generation and evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If expert knowledge is used for HVAC system design and configuration, then the design process can be completed with existing methods, but the performance in energy efficiency and comfort is suboptimal due to limited or incomplete expert knowledge
Solution Approach 1:
The patent creates a digital twin or virtual model of the HVAC system that replicates the complex configuration variations and performance characteristics. This virtual model allows comprehensive evaluation of energy efficiency and comfort across multiple configurations without requiring physical prototypes or extensive manual analysis, thereby resolving the contradiction between achieving optimal performance and managing configuration complexity.
Solution Approach 2:
The system systematically varies key parameters such as equipment selection, control strategies, building envelope properties, and operational schedules to evaluate their impact on energy efficiency and comfort. By automating parameter variation and performance assessment, the system can explore a broader design space than expert knowledge alone, improving reliability while managing complexity through structured parameter exploration.
2Reliability
If comprehensive HVAC configuration options are evaluated to improve performance, then energy efficiency and comfort can be optimized, but computational resources and time are consumed
Solution Approach 1:
The patent performs preliminary filtering and pre-assessment of HVAC configurations before conducting full simulations. By evaluating basic criteria and eliminating clearly suboptimal options in advance, the system reduces the number of configurations requiring detailed simulation analysis, thereby maintaining comfort level optimization while significantly reducing computational time and resource consumption.
Solution Approach 2:
The system employs a multi-level evaluation approach where not all configurations receive full computational analysis. Instead, configurations are assessed at different depths based on preliminary screening results, applying partial analysis to most options and excessive (full) analysis only to promising candidates. This stratified approach maintains optimization quality while reducing overall computational burden.
3Measurement precision
If detailed simulation models are used to accurately assess HVAC performance, then precise performance indicators can be obtained, but computational complexity and resource consumption increase
Solution Approach 1:
The patent employs adaptive modeling where the simulation model complexity dynamically adjusts based on the evaluation stage and configuration characteristics. For preliminary screening, simplified models are used to quickly assess performance trends. For final optimization of promising configurations, more detailed models provide precise performance indicators. This dynamic approach maintains measurement precision where needed while reducing computational complexity during intermediate stages.
Data Source
AI summary
A system is provided that includes one or more processing resources operable to execute instructions to determine one or more base load profiles associated with one or more buildings and modify the one or more base load profiles based on a new set of building envelope parameter options that vary at least one building envelope feature. The one or more base load profiles are matched with a plurality of heating, ventilation, and air conditioning (HVAC) equipment profiles to define HVAC configuration options. Control configurations are determined for the HVAC configuration options. A simulation of the control configurations is executed on models of the HVAC configuration options to determine one or more performance indicators. An assessment is output of the one or more performance indicators associated with the control configurations and the HVAC configuration options for the one or more buildings.