Method and system for optimizing heating, ventilation and air conditioning system
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Solution Overview
Problem
Existing HVAC systems face challenges in optimizing control strategies due to subjective temperature and humidity targets, difficulty in measuring cooling capacity and power consumption, especially in third-party systems, and lack of comprehensive data on fan coil units and energy usage across floors and zones.
Innovation Solution
A controlling system comprising an HVAC information collector, a voting device, an occupancy collector, and a processor that collects and processes data to obtain optimal HVAC setpoint values using trained prediction models for zone temperature, comfort feedback, and occupancy, allowing for precise control of HVAC systems in each zone.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional BMS control methods are used with subjective temperature and humidity targets, then the control implementation is simplified, but the optimization effectiveness deteriorates due to lack of objective performance metrics
Solution Approach 1:
The patent introduces an intermediary measurement layer that indirectly infers cooling capacity and energy consumption through readily available sensor data (temperature, humidity, occupancy) and building models, rather than directly measuring these hard-to-obtain parameters. This mediator approach resolves the contradiction by providing objective performance metrics without requiring complex measurement infrastructure.
Solution Approach 2:
The patent replaces direct mechanical measurement systems (flow meters, power meters on individual fan coil units) with a computational model-based approach that uses electrical sensors and algorithms to infer performance metrics. This substitution eliminates the need for physical measurement infrastructure while providing objective optimization targets.
2Measurement precision
If comprehensive sensors and detailed system information are installed to measure cooling capacity and power consumption, then measurement precision improves, but device complexity and cost increase
Solution Approach 1:
The patent extracts only the essential measurement data that is already available in most BMS systems (temperature, humidity, occupancy, basic energy data) and uses these extracted inputs to infer the hard-to-measure parameters through computational models, rather than installing comprehensive sensor arrays.
Solution Approach 2:
The patent creates virtual copies of the physical system through digital twins and predictive models that replicate building thermal dynamics and HVAC performance. These virtual models allow measurement of cooling capacity and energy consumption through simulation rather than direct physical measurement, reducing hardware complexity.
3Adaptability or versatility
If third-party HVAC systems are controlled without detailed system information, then adaptability improves, but control precision deteriorates due to lack of system-specific data
Solution Approach 1:
The patent develops a universal control framework that works across different HVAC system types (fan coil units, VRF, chillers) and building configurations by using generic building physics models and standardized data interfaces. The system adapts to third-party systems through model-based inference rather than requiring system-specific programming, achieving both universality and precision.
Solution Approach 2:
The patent uses parameter-based modeling where building-specific thermal dynamics, HVAC performance characteristics, and environmental factors are represented as adjustable parameters in predictive models. These parameters can be calibrated with minimal site-specific data, allowing the system to adapt to different buildings and HVAC systems while maintaining control precision through model-based optimization.
Data Source
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AI summary
A method (800) for controlling a heating, ventilation and air conditioning (HVAC) system (10a) by a controlling system (100) for each HVAC zone (80) in a building, the controlling system (100) comprising a HVAC information collector (102), a voting device (122), an occupancy collector (132), a processor (110), and an HVAC controller (104), the method (800) comprising: a step (814) of collecting HVAC information (12) of the HVAC system (10a) by the HVAC information collector (102); a step (830) of collecting comfort feedback information (20) from each of occupants (22) by the voting device (122); a step (850) of collecting occupancy information (30) of the occupants (22) by the occupancy collector (132); and a step (880) of obtaining, by the processor (110), a set of optimal HVAC setpoint values (46) for time steps of control horizon based on a trained zone temperature prediction model (16), a trained comfort feedback prediction model (24), a trained occupancy prediction model, the collected HVAC information (12), collected outdoor environment information (14), the collected comfort feedback information (20), and the collected occupancy information (30).