Inferring Home Heating Fuel Type from Energy Usage Data
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Solution Overview
Problem
Accurate energy usage comparisons and relevant efficiency tips for energy users are hindered when information about the fuel type used for heating and the presence of an air conditioner in their homes is unavailable, leading to degraded customer experience and reduced effectiveness of energy conservation programs.
Innovation Solution
A system that infers the fuel type used for heating and determines the presence of an air conditioner by analyzing energy usage data during different seasons, using linear discriminant functions and confidence levels from various data sources, and provides targeted energy efficiency tips based on these determinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If energy usage data is compared without home characteristic information, then the comparison process is simple, but the accuracy and relevance of the comparison deteriorates
Solution Approach 1:
The system performs preliminary actions by inferring home characteristics (fuel type, air conditioner presence) before conducting energy usage comparisons. This advance preparation ensures that comparisons are made between homes with similar characteristics, improving accuracy without adding complexity during the comparison process itself
Solution Approach 2:
The system uses the energy usage data itself to infer home characteristics through analysis patterns and comparisons with other homes. The data serves双重 purposes: both for inferring characteristics and for the actual energy comparison, eliminating the need for separate data collection processes
2Reliability
If home characteristic information is obtained from multiple external sources, then the accuracy of information improves, but the system complexity and data integration requirements worsen
Solution Approach 1:
The system segments the approach to obtaining home characteristic information by using multiple independent sources (utility data, parcel data, energy usage patterns) rather than relying on a single complex integrated database. Each source provides partial information that contributes to the overall characterization
Solution Approach 2:
The energy usage data serves multiple functions: it is used both to infer home characteristics and to perform the actual energy consumption comparisons. This multi-functionality reduces the need for separate data collection systems and simplifies the overall data infrastructure
3Ease of operation
If energy efficiency tips are provided without knowing home characteristics, then the system is simpler to operate, but the relevance and effectiveness of the tips deteriorates
Solution Approach 1:
The system applies local quality by tailoring energy efficiency tips to specific home characteristics (fuel type, presence of air conditioner) rather than providing generic advice. This ensures that the tips are relevant to each home's actual energy consumption patterns and infrastructure
Data Source
AI summary
A residential home characteristics inferring method and system that receives information about energy usage by an energy user, determines using a processor and the received information about energy usage average daily usage during a heating season and average daily usage during a shoulder season, and identifies the fuel type used for heating by the energy user using the determined average daily usage during the heating season and the determined average daily usage during the shoulder season.