Building Energy Simulation Calibration via Variable Extraction
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Solution Overview
Problem
Current methods for assessing and calibrating building energy usage profiles are inaccurate due to unverified occupant and system behavioral factors, requiring complex data sets and evaluations, which leads to poor decision-making in energy management.
Innovation Solution
A digital system that uses a spreadsheet program with macros and Visual Basic code to analyze historical energy data, simulate energy consumption, and calibrate energy usage profiles by adjusting building parameters and implementing energy efficiency measures, providing graphical and tabular reports for energy savings projections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex evaluation of large number of inputs and outputs is performed using traditional energy simulation methods, then measurement precision of energy consumption is improved, but device complexity and loss of time increase significantly
Solution Approach 1:
The patent extracts and isolates the critical variables that most significantly impact energy consumption from the large set of all possible building parameters. By identifying and focusing only on the most influential variables (such as HVAC system characteristics, building envelope properties, and occupancy patterns), the system achieves accurate energy consumption assessment without requiring complex evaluation of all inputs and outputs, thereby reducing device complexity while maintaining measurement precision.
Solution Approach 2:
The patent segments the energy consumption assessment into distinct modules: baseline energy usage profile development, variable identification and prioritization, and simulation execution. This segmentation allows the system to process information in manageable stages, reducing overall device complexity while maintaining comprehensive accuracy through systematic analysis of energy consumption components.
2Measurement precision
If comprehensive data sets and complex evaluations are used to calibrate energy usage profiles, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent performs preliminary action by pre-establishing the baseline energy usage profile using standard building science principles and typical operational parameters before conducting the actual calibration process. This preliminary baseline serves as a starting point that requires minimal adjustment during calibration, significantly reducing the time needed to achieve accurate energy usage profiles while maintaining measurement precision through targeted refinement of key variables.
Solution Approach 2:
The patent applies parameter changes by focusing calibration efforts on the most sensitive and influential parameters rather than adjusting all possible variables. By identifying which parameters have the greatest impact on energy consumption and concentrating calibration resources on those specific parameters, the system achieves accurate energy usage profiles faster, reducing loss of time while maintaining measurement precision.
3Measurement precision
If unverified occupant and system behavioral factors are included in energy modeling, then measurement precision may improve, but reliability decreases due to inaccuracy
Solution Approach 1:
The patent applies self-service by using the collected energy consumption data to automatically refine and update the building's energy model over time. The system learns from actual operational patterns and automatically adjusts parameters to match observed behavior, reducing the need for manual verification of occupant and system behavioral factors. This automated adaptation improves reliability by base on actual performance data rather than unverified assumptions, while maintaining measurement precision through continuous refinement.
Data Source
AI summary
A method for analyzing energy savings for a building is provided. The method includes receiving a historical energy usage and a weather data for a building, a set of operations parameters describing building operations and a set of building system parameters describing building systems. A baseline configuration is submitted to a first energy consumption simulation to determine a baseline energy usage profile. A calibrated configuration is determined from the baseline configuration and the historical energy usage. The calibrated configuration is submitted to a second energy consumption simulation to determine a calibrated energy usage profile. A hypothetical configuration is determined from the calibrated configuration and a set of energy improvement measures. The hypothetical configuration is submitted to a third energy consumption simulation to determine a hypothetical energy usage profile and report. The set of energy improvement measures are approved and implemented based on the hypothetical energy usage profile.