System and method for building heating optimization using periodic building fuel consumption with the aid of a digital computer
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Solution Overview
Problem
Current methods for estimating building heating and cooling energy consumption are invasive, time-consuming, and prone to inaccuracies due to the need for detailed energy audits and specialized testing equipment, making it difficult to quantify energy savings from building shell upgrades effectively.
Innovation Solution
A system and method using a digital computer to calculate building heating and cooling fuel consumption through empirically-measured values and readily-available data, such as utility billing information, which simplifies the process by deriving building-specific parameters like thermal conductivity and HVAC efficiency through short-duration tests, allowing for hourly or periodic fuel requirement calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional energy audits with detailed testing equipment are used, then measurement precision of building thermal parameters is improved, but device complexity and time consumption increase significantly
Solution Approach 1:
The patent uses readily available utility billing data as a proxy or copy of actual energy consumption, eliminating the need for complex physical testing equipment. Instead of directly measuring thermal parameters with specialized devices, the system calculates them from existing fuel consumption records, thereby simplifying the measurement process while maintaining practical accuracy for energy optimization purposes
Solution Approach 2:
The patent replaces mechanical/physical testing systems (blower door tests, thermal cameras, R-value measurements) with a computational system that processes utility billing data. This substitution eliminates the need for specialized testing equipment and complex audit procedures, using mathematical models to derive thermal parameters from energy consumption patterns instead
2Measurement precision
If conventional energy audits are performed, then building thermal parameters are obtained, but time consumption and cost increase
Solution Approach 1:
The patent utilizes utility billing data that has already been collected and recorded before the energy optimization analysis is performed. This preliminary collection of energy consumption data eliminates the need for time-consuming on-site testing and measurements during the audit process, as the data is already available in digital format from utility companies
Solution Approach 2:
The system uses existing utility billing records as a substitute for new measurements, copying data that already exists rather than generating it through time-consuming field tests. This approach retrieves building thermal parameters from historical energy consumption patterns without requiring physical presence or extended testing periods
3Measurement precision
If detailed energy audits are conducted, then accurate thermal conductivity data is obtained, but ease of operation deteriorates due to complexity
Solution Approach 1:
The system allows building owners to obtain thermal conductivity estimates and energy optimization recommendations by simply providing utility billing data, without requiring them to coordinate complex testing schedules or hire specialized auditors. The computational system automatically processes the data and generates results, making the process as easy as submitting a spreadsheet or database file
Solution Approach 2:
The patent replaces the manual, expertise-intensive energy audit process with an automated computational system that processes utility billing data through mathematical models. This substitution eliminates the need for trained auditors to perform physical measurements and complex calculations, making the process accessible to building owners without specialized knowledge
Data Source
AI summary
A system and method to evaluate building heating fuel consumption with the aid of a digital computer 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.