Thermal management of buildings using intelligent and autonomous set-point adjustments
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Solution Overview
Problem
Existing thermal management systems in buildings often face inefficiencies due to manually chosen set-point temperatures, leading to energy inefficiency and comfort issues, as they do not dynamically adjust based on real-time occupancy and ambient conditions.
Innovation Solution
An intelligent and autonomous system that captures user-selected settings for energy usage and thermal comfort, utilizing real-time occupancy and ambient data to dynamically determine and adjust set-point temperatures, minimizing HVAC energy consumption while ensuring occupant comfort through rule-based and data-driven analytics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manually chosen set-point temperatures are used, then ease of operation is improved, but energy efficiency deteriorates
Solution Approach 1:
The system enables itself to automatically determine and adjust set-point temperatures based on real-time occupancy and ambient data, eliminating the need for continuous manual intervention while optimizing energy consumption. The autonomous system serves itself by making intelligent thermal management decisions.
Solution Approach 2:
The system continuously monitors real-time occupancy data and ambient conditions, then uses this feedback to dynamically adjust set-point temperatures. This closed-loop control ensures energy efficiency while adapting to changing building conditions.
2Device complexity
If manually chosen set-point temperatures are used, then device complexity is reduced, but adaptability deteriorates
Solution Approach 1:
The system transitions from static manual set-point selection to dynamic automatic adjustment based on real-time conditions. Set-point temperatures continuously adapt to occupancy changes and ambient conditions, enabling the system to respond flexibly to varying thermal demands.
Solution Approach 2:
The system autonomously monitors occupancy data and ambient conditions, then self-adjusts set-point temperatures without external intervention. This enables the system to adapt to changing conditions while maintaining manageable complexity through automated decision-making.
3Use of energy by moving object
If set-point temperatures are dynamically adjusted based on real-time data, then energy efficiency is improved, but device complexity increases
Solution Approach 1:
The system performs autonomous thermal management by automatically collecting occupancy data, analyzing ambient conditions, and adjusting set-point temperatures without external control. This self-service capability optimizes energy efficiency while keeping operational complexity manageable through automation.
Solution Approach 2:
The system implements continuous monitoring of occupancy and ambient conditions, using this real-time feedback to dynamically optimize set-point temperatures. This closed-loop approach improves energy efficiency while managing complexity through systematic data-driven control.
4Productivity
If autonomous set-point adjustment is implemented, then productivity is improved through energy optimization, but ease of operation deteriorates
Solution Approach 1:
The system autonomously manages thermal control by automatically determining set-point temperatures based on occupancy and ambient conditions, eliminating the need for manual operation. This self-service capability maximizes energy optimization while reducing operational intervention requirements.
Solution Approach 2:
The system uses real-time feedback from occupancy sensors and ambient condition monitors to automatically adjust set-point temperatures, optimizing energy efficiency without requiring manual control. The feedback-driven automation improves productivity through continuous energy optimization.
Data Source
AI summary
Methods, systems, and computer program products for thermal management of buildings using intelligent and autonomous set-point adjustments are provided herein. A method includes capturing a user-selected setting that represents a desired balance between (i) energy usage and (ii) thermal comfort associated with a building; capturing, via a communication link with one or more hardware devices associated with thermal management of the building, one or more items of real-time information pertaining to the thermal management of the building; determining one or more set-point temperatures for the building based on (i) the user-selected setting, (ii) the items of real-time information pertaining to the thermal management of the building, and (iii) one or more constraints; and outputting the set-point temperatures to the hardware devices associated with the thermal management of the building for execution of a thermal management schedule to be carried out in accordance with the set-point temperatures.