Measurement Data Cleaning
The increase in metering and monitoring devices on the distribution grid have created an influx of SCADA and AMI measurement data. The abundance of this data has promising applications across planning and operational studies, but there are also challenges to unlocking the full value of it.
Today, much of the data is not readily usable due to data quality issues - missing data, time synchronization issues, zero values, noise introduction, etc. In addition, identifying and addressing all possible data quality issues for large data sets can be challenging. The data handling processes are largely manual and vary depending on how the data will be applied in planning and operational studies, which can result in significant time required from engineers to make use of these new datasets.
EPRI’s Research
Recognizing this need, EPRI has been developing methodologies to automatically detect measurement data problems and remediate based on intended applications. The overall goal of these efforts it to:
- Increase efficiency of processing, understanding, and correcting measurement data.
- Improve utilization of data to build models and more reliably perform planning/operational studies.
EPRI’s work spans multiple areas including:
- Identifying uses of measurement data across operations and planning applications
- Providing methods to clean, structure, and make measurement data easier to utilize in planning and operational studies
- Developing a tool that automatically detects, and processes time-series measurement data issues based on intended applications.
To learn more about this work, check out the below reports
| Title | Objective |
| Guidance on Measurement Data Cleaning for Planning and Operations: 2023 Edition, 3002027260 |
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| Measurement Data Use Case Repository - 3002030155 |
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| Measurement Data Cleaning Tool - Supplemental Project Notice |
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