Building Energy Metrics for Zone-Level Leak Detection
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Solution Overview
Problem
As buildings age, deteriorating insulation and weather seals lead to energy inefficiencies, making it difficult for homeowners to identify and repair energy leaks, and there is a lack of baseline metrics for comparing energy efficiency.
Innovation Solution
A method and system that collects data from indoor and outdoor sensors, utility meters, and HVAC devices to calculate energy performance metrics, providing comparisons with similar buildings and recommending improvements, while also suggesting contractors for repairs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If building materials are used to insulate and seal buildings, then energy efficiency is improved, but over time the materials deteriorate and energy efficiency decreases
Solution Approach 1:
The system performs preliminary detection of energy leaks using sensors and algorithms before they significantly impact energy efficiency. By continuously monitoring temperature differentials, air flow, and humidity patterns, the system identifies deteriorating building materials early, allowing proactive maintenance before complete failure occurs.
Solution Approach 2:
The system establishes a feedback loop where sensor data from the building is continuously analyzed to assess the condition of building materials. The analysis results are fed back to homeowners through the interface, enabling them to understand the current state of their building envelope and take appropriate actions to maintain energy efficiency.
2Temperature
If HVAC systems work harder to compensate for energy leaks, then internal temperature stability is maintained, but energy costs increase
Solution Approach 1:
The system detects energy leaks and identifies their locations before they cause significant temperature fluctuations. By providing early warning and location information, the system enables preventive repairs that eliminate the need for increased HVAC operation to compensate for thermal losses.
3Loss of energy
If building occupants try to identify energy leak sources manually, then potential savings can be achieved, but the complexity of identification increases due to multiple potential sources
Solution Approach 1:
The system divides the building into multiple zones with dedicated sensors in each zone. By segmenting the detection space and analyzing temperature differentials and air flow patterns zone-by-zone, the system systematically identifies energy leak sources without overwhelming complexity, providing clear location information to homeowners.
Solution Approach 2:
The system introduces an intermediary intelligent analysis layer between the physical energy leaks and the homeowner. Sensors detect physical parameters, the analysis algorithm processes this data to identify leak sources and locations, and the interface presents simplified information to the homeowner, mediating the complexity of the detection process.
4Measurement precision
If comprehensive sensor data is collected and analyzed, then accurate energy metrics are obtained, but system complexity and data processing requirements increase
Solution Approach 1:
The system employs multi-functional sensors that measure multiple parameters (temperature, humidity, air flow) simultaneously. The same sensor infrastructure supports both energy leak detection and general building performance monitoring, reducing overall system complexity while maintaining measurement precision through unified data collection.
Data Source
AI summary
A method and system can provide building energy performance metrics that can help identify specific zones within a building which may have energy efficiency problems. The method and system can collect data from: indoor temperature sensors and humidity sensors present in each zone of a building; one or more temperature sensors and humidity sensors present outside of the building; one or more utility meters; and one or more HVAC devices. This data from the sensors can be aggregated and formed into a first profile. The energy efficiency calculation system can analyze the first profile to provide various energy performance metrics which can include, but are not limited to, energy efficiency ratios for air conditioners, the R-value or thermal resistance of the building, an amount of heat loss for the building, energy consumption by the building, current HVAC performance parameters, and utility usage comparisons.