HVAC Control Framework Using Asset Allocation for Auto Commissioning
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Solution Overview
Problem
HVAC systems require frequent manual updates to optimize energy efficiency and operation, which is time-consuming and inefficient, especially in complex building setups with varying energy loads.
Innovation Solution
A cloud computing system automatically commissions and operates HVAC systems by querying site information, constructing an asset allocator model, and generating control variables to optimize equipment operation, allowing for automated updates and energy load management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual updates are performed on each device within the HVAC system, then system operation can be optimized, but time consumption and operational efficiency deteriorate
Solution Approach 1:
The system enables automated self-updating of HVAC devices through cloud-based asset allocator models. The cloud computing system automatically generates control variable values and pushes updates to physical equipment without requiring manual intervention at each device, allowing the system to serve and update itself autonomously
Solution Approach 2:
A cloud computing system acts as an intermediary between operators and HVAC devices. The asset allocator model in the cloud receives site information, processes optimization algorithms, and automatically distributes control commands to multiple devices simultaneously, eliminating the need for manual updates at each individual device while maintaining system-wide optimization
2Productivity
If automated commissioning and operation is implemented using cloud computing systems, then operational efficiency and energy management improve, but system complexity increases
Solution Approach 1:
The cloud computing system serves as an intermediary layer that manages the complexity of automated commissioning and operation. By centralizing the asset allocator model and control logic in the cloud, the system achieves automated optimization without requiring complex local infrastructure at each building site, maintaining productivity gains while managing system complexity through cloud-based abstraction
Data Source
AI summary
A method for automatically commissioning and operating an HVAC system to serve energy loads of a building site is shown. The method includes querying site information describing the building site to identify physical equipment and relationships between the physical equipment. The method further includes constructing an asset allocator model, the asset allocator model indicating connections between the physical equipment and resources produced or consumed by the physical equipment. The method further includes generating a mapping between points of the physical equipment at the building site and corresponding variables of the asset allocator model. The method further includes using the asset allocator model to generate values of one or more control variables of the asset allocator model. The method further includes adjusting an operation of the physical equipment by triggering software elements to automatically push updated values of the control variables to corresponding points of the physical equipment.