Building Energy Analysis Using Balance Points and Exception Ranks
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Solution Overview
Problem
Current methods for analyzing building energy data lack efficiency in providing accurate, data-focused analysis results to determine energy expenditures and performance, leading to suboptimal energy management and control of building systems.
Innovation Solution
A computer-implemented energy analysis system that connects to energy data sources, performs analysis, and generates results including exception ranks and balance points, using a processor, communication interface, and memory with energy analysis logic to determine user-defined and control building data, and displays results through a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional energy analysis methods are used, then analysis can be performed, but the accuracy and efficiency of providing data-focused analysis results is insufficient
Solution Approach 1:
The energy analysis system segments the analysis process into distinct modules: data collection from multiple sources, data validation and cleaning, energy consumption calculation, anomaly detection, and reporting. This segmentation allows each module to be optimized independently, improving both accuracy through specialized processing and efficiency through parallel execution of modular components.
Solution Approach 2:
The system introduces an intermediary data processing layer between raw energy data and analysis results. This intermediary layer includes automated data validation, normalization, and preprocessing functions that enhance the quality of input data before analysis, thereby improving measurement precision while maintaining high processing throughput through automated routines.
2Reliability
If comprehensive energy data collection is implemented, then analysis completeness improves, but system complexity increases
Solution Approach 1:
The energy analysis system is designed as a universal platform that can collect and process multiple types of energy data (electrical, gas, water, steam) from various sources using a single integrated architecture. The system employs universal data interfaces and standardized processing routines that handle different data formats and sources uniformly, ensuring comprehensive data collection while minimizing system complexity through consolidation rather than multiplication of components.
Solution Approach 2:
The system dynamically adjusts processing parameters based on data characteristics and analysis requirements. It automatically modifies data sampling rates, validation thresholds, and analysis depth according to the specific energy source and building type, thereby maintaining comprehensive analysis coverage while optimizing system resource usage and reducing operational complexity through adaptive parameter management.
Data Source
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AI summary
An energy analysis system provides valuable input into building energy expenditures. The system assists with obtaining a detailed view of how energy consumption occurs in a building, what steps may be taken to lower the energy footprint, and executing detailed energy consumption analyses. The analyses may include, as examples, a balance point pair analysis to determine either or both of a heating balance point and a cooling balance point, an exception rank analysis to identify specific data (e.g., energy consumption data) in specific time intervals for further review, or other analysis. The system may display the analysis results on a user interface.