Adaptive Smart Meter Data Sampling for Cost and Privacy
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Solution Overview
Problem
The collection of data from Advanced Metering Infrastructures (AMIs) poses challenges related to consumer privacy and high costs for data storage and transmission, necessitating a solution that balances data quality with privacy concerns and economic feasibility.
Innovation Solution
An adaptive sampling method that retrieves balancing constraints from smart meter sensors to determine subsamples of data, which are then transmitted to an optimization engine for solving optimization problems, utilizing stratified sampling to reduce data volume while maintaining spatio-temporal resolution and protecting user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If data aggregation is used to reduce transmission and storage costs, then data transmission cost is reduced, but data quality and spatio-temporal resolution may deteriorate
Solution Approach 1:
The patent applies partial action by selectively sampling only a subset of smart meter data rather than processing all data. The system determines subsamples based on balancing constraints, performing aggregation on partial data to reduce transmission costs while maintaining sufficient spatio-temporal resolution for optimization purposes
Solution Approach 2:
The patent changes the sampling parameters dynamically based on balancing constraints. By adjusting the subsampling rate and selection criteria according to specific constraints, the system optimizes the balance between data reduction for cost savings and data quality for maintaining resolution
2Object-affected harmful factors
If data aggregation is used to protect consumer privacy, then privacy protection is improved, but data availability for analysis may worsen
Solution Approach 1:
The patent extracts only the necessary subset of data required for optimization analysis while leaving detailed individual consumer data aggregated or excluded. By taking out only essential information patterns rather than raw individual data, the system protects privacy while maintaining data availability for network optimization
Solution Approach 2:
The system performs partial data collection by selecting subsamples that provide sufficient information for analysis without exposing complete consumer data. This partial action approach ensures privacy protection while retaining enough data availability to solve optimization problems
3Measurement precision
If full smart meter data is collected and transmitted, then data quality and analysis accuracy are improved, but data storage and transmission costs increase
Solution Approach 1:
The patent implements partial data transmission by determining subsamples of smart meter data based on balancing constraints. This approach transmits only the necessary portion of data required for accurate analysis, reducing storage costs while maintaining sufficient data quality for optimization purposes
Data Source
AI summary
In an approach for adaptive sampling of smart meter data, a computer retrieves one or more balancing constraints associated with one or more smart meter sensors. The computer retrieves meter sensor data from the one or more smart meter sensors according to the one or more balancing constraints. The computer determines a subsample of the meter sensor data, and then transmits the subsample of the meter sensor data to an optimization engine for use in solving an optimization problem.