Optimized energy usage in an air handling unit
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Solution Overview
Problem
HVAC systems face challenges in optimizing energy consumption due to complex modeling and time-consuming repetitive measurements, making it difficult to identify and utilize the operating state that minimizes energy use while satisfying other goals.
Innovation Solution
A control system that calculates the slope of energy usage as a function of temperature or humidity changes, adjusting the air supply temperature from the AHU based on this slope to balance energy usage between the AHU and terminal units, using a hill climbing technique without requiring complete calculation of a cost function.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex modeling or repetitive measuring is used to optimize energy consumption, then energy optimization accuracy is improved, but system complexity and time consumption increase
Solution Approach 1:
The patent extracts only the essential information needed for optimization - the slope of energy consumption - rather than using complete complex models. By taking out just the critical gradient information needed to determine optimization direction, the system achieves effective energy optimization without the burden of complete system modeling.
Solution Approach 2:
Instead of performing complete energy consumption calculations or exhaustive measurements, the patent uses partial information - specifically the slope or gradient of energy consumption with respect to operating parameters. This partial action approach provides sufficient guidance for optimization without requiring complete system analysis.
2Measurement precision
If complete cost function calculation is used to find optimal operating points, then optimization accuracy is improved, but computational time and complexity increase
Solution Approach 1:
The patent extracts only the slope or gradient of the cost function rather than calculating the complete cost function. This extracted gradient information is sufficient to determine the direction toward optimal operation, eliminating the need for time-consuming complete cost function evaluations while maintaining optimization effectiveness.
Solution Approach 2:
The system performs partial optimization by using only the gradient information needed to move toward the optimum, rather than calculating the complete cost function. This partial action approach provides the necessary directional guidance for optimization without the computational burden of complete function evaluation.
Data Source
AI summary
Rather than complex modeling or time consuming repetitive measuring for optimizing an HVAC system, a slope or change in energy use as a function of a change in a variable (e.g., temperature or humidity) is used to adjust the variable. In an HVAC system, the temperature or humidity of supplied air from the AHU is set based on the derived slope. The energy usage to heat and/or cool supplied air at the terminal units is balanced with the energy usage to heat and/or cool the air to be supplied by the AHU. The slope of the total energy usage may be indicated by a sum of flow rates.