Computer-implemented system and method for modeling building heating energy consumption
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Solution Overview
Problem
Current methods for estimating building heating energy consumption are costly, time-consuming, and invasive, relying on detailed energy audits that are prone to inaccuracies due to mismeasurements and data assumptions, and fail to effectively quantify energy savings from building shell upgrades.
Innovation Solution
A computer-implemented system and method that calculates building heating energy consumption using empirically-measured values from utility billing data and short-duration tests to derive building-specific parameters, such as thermal conductivity and HVAC system efficiency, allowing for the simulation of indoor temperature and fuel consumption over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional energy audit methods are used to estimate building heating energy consumption, then detailed thermal conductivity parameters can be obtained, but the process becomes costly, time-consuming, and invasive
Solution Approach 1:
The patent creates a simplified computational model that copies the essential thermal behavior of a building without requiring physical measurement of all building components. The model uses readily available data (utility bills, weather data, building characteristics) to replicate heating energy consumption patterns, eliminating the need for invasive physical audits while maintaining sufficient accuracy for energy savings estimation
Solution Approach 2:
The patent replaces the mechanical/physical measurement system (blower door tests, thermal cameras, physical inspections) with a computational/data-driven system. Instead of physically measuring thermal conductivity through invasive tests, the system uses mathematical models and available data to estimate heating energy consumption, significantly reducing time and invasiveness while providing practical accuracy
2Measurement precision
If conventional energy audit methods are used to estimate building heating energy consumption, then thermal conductivity parameters can be determined, but inaccuracies arise due to mismeasurements and data assumptions
Solution Approach 1:
The patent enables the building's existing data infrastructure to serve the measurement function. Utility billing data, weather station data, and building characteristic data that already exist in the system are repurposed to estimate heating energy consumption, eliminating the need for separate measurement campaigns that introduce human error and assumption-based inaccuracies
Solution Approach 2:
The system uses actual heating energy consumption data from utility bills as feedback to validate and refine the computational model. By comparing model predictions with actual measured consumption over time, the system continuously improves accuracy without requiring re-measurement of building parameters, reducing both error sources and the need for invasive follow-up audits
3Loss of information
If detailed energy audits are performed to quantify energy savings from building shell upgrades, then building-specific parameters can be obtained, but the process remains complex and invasive
Solution Approach 1:
The patent segments the energy savings analysis into distinct computational components: baseline consumption modeling, upgrade scenario modeling, and differential calculation. Each component uses simplified inputs (utility bills, weather data, building characteristics) rather than requiring comprehensive physical measurements of all building systems, reducing overall process complexity while maintaining quantification accuracy
Solution Approach 2:
The computational model serves multiple functions simultaneously: it estimates baseline heating energy consumption, predicts post-upgrade consumption, calculates energy savings, and identifies cost-effective upgrades. This multi-functionality eliminates the need for separate analysis processes, reducing complexity while providing comprehensive energy savings quantification for building shell improvements
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach simplifies the estimation of heating energy consumption, reduces the need for intrusive testing, and accurately quantifies energy savings from building shell improvements, providing a more accurate and cost-effective method for energy management.
Implementation Method 1
a building's thermal conductivity UATotal... HVAC system efficiency... differences between indoor and outdoor temperatures... building's thermal efficiency
Implementation Method 2
a poorly insulated house or a building with significant sealing problems will require more overall HVAC usage to maintain a desired interior temperature
Data Source
AI summary
A computer-implemented system and method to evaluate building heating fuel consumption is described. The evaluation can be used for quantifying personalized electric and fuel bill savings. Such savings may be associated with investment decisions relating to building envelope improvements; HVAC equipment improvements; delivery system efficiency improvements; and fuel switching. The results can also be used for assessing the cost/benefit of behavioral changes, such as changing thermostat temperature settings. Similarly, the results can be used for optimizing an HVAC control system algorithm based on current and forecasted outdoor temperature and on current and forecasted solar irradiance to satisfy consumer preferences in a least cost manner. Finally, the results can be used to correctly size a photovoltaic (PV) system to satisfy needs prior to investments by anticipating existing energy usage and the associated change in usage based on planned investments.