Building Thermal Lag Estimation Without Internal Temperature Data
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Solution Overview
Problem
Existing energy use analysis tools in commercial buildings are ineffective in predicting actual energy use compared to design estimates, as they rely on internal space temperature data which is often not accurately recorded.
Innovation Solution
A method to determine a building's natural thermal lag (NTL) using only energy data and external temperature data, eliminating the need for internal temperature data, by analyzing the relationship between energy usage and lagged external temperature indices through regression analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If internal space temperature data is used to determine natural thermal lag, then measurement precision may be improved, but device complexity and data availability worsen due to lack of accurate internal temperature recordings
Solution Approach 1:
The patent extracts the NTL determination process from dependence on internal temperature data and makes it independent by using only external temperature and energy usage data. This removes the requirement for internal temperature sensors and recording systems, simplifying the data collection infrastructure while maintaining NTL measurement capability.
Solution Approach 2:
The patent introduces energy usage data as an intermediary variable that connects external temperature to building thermal response. Instead of directly measuring internal temperature, the method uses energy consumption patterns as a proxy indicator of thermal lag, enabling NTL determination through readily available utility data.
2Measurement precision
If internal space temperature recording systems are installed, then NTL determination accuracy improves, but loss of substance increases due to required infrastructure
Solution Approach 1:
The patent enables the building energy system to determine its own thermal characteristics using data already generated by its operation. Energy usage data, which is naturally produced by the building's HVAC system, serves dual purposes: both operating cost tracking and thermal lag characterization, eliminating the need for separate measurement infrastructure.
Solution Approach 2:
The patent makes utility company energy data serve multiple functions: billing, energy management, and building thermal characterization. This multi-functional use of existing data infrastructure eliminates the need for dedicated internal temperature recording systems, reducing infrastructure requirements while maintaining measurement capability.
3Ease of operation
If generalized parameters and tables are used for energy use analysis, then ease of operation improves, but predictive strength worsens when comparing design estimates with actual energy use
Solution Approach 1:
The patent transitions from static generalized parameters to dynamic, building-specific thermal lag values. By calculating unique NTL for each building based on its actual energy consumption patterns, the method adapts to individual building characteristics while maintaining operational simplicity through automated calculation processes.
Solution Approach 2:
The patent uses actual energy usage data as feedback to determine building-specific thermal lag parameters. This feedback loop allows the system to learn and adapt to each building's actual thermal response characteristics, improving prediction accuracy by replacing generalized assumptions with measured building behavior.
Data Source
AI summary
The invention provides an improved method for determining the natural thermal lag (NTL) of a building, where the improvement includes using the 15 minute interval energy usage data for the building, and data the external temperature to determine the NTL. This improved method has the advantage of being independent of any need to acquire data regarding internal temperature of the building in question.