Data Cleaning in Large Customer-Owned Electricity Meter Systems

Electricity meter data is crucial for both utility companies and their customers. Meter data has a variety of uses such as energy and power consumption analysis, grid optimization, infrastructure planning, and achieving environmental goals. Meter Data Management System (MDMS) is a large customer-owned meter network with over 20,000 meters operated by the Department of Defense (DoD). MDMS meters measure energy and demand over fixed time intervals and report this data to a centralized server that stores and compiles data into reports. Users can change the parameters of these reports to suit their needs. Due to its size, complexity, and communication requirements, a variety of systemic MDMS issues resulted in erroneous meter data. Specifically, seven meter data issues were observed, and their causes were analyzed and defined. A novel data cleaning method was developed using a sequential series of seven algorithms to clean the data, creating more accurate meter data. Results are presented for West Point's MDMS data.

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Published
2024-10-13
DOI
https://doi.org/10.1109/naps61145.2024.10741871
Primary Topic
Electricity Theft Detection Techniques
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article
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article

Data Cleaning in Large Customer-Owned Electricity Meter Systems

Nicholas G. Barry, Aaron St. Leger, Bach Nguyen
Electricity Theft Detection Techniques
article

Data Cleaning in Large Customer-Owned Electricity Meter Systems

Nicholas G. Barry, Aaron St. Leger, Bach Nguyen
article en

Abstract

Electricity meter data is crucial for both utility companies and their customers. Meter data has a variety of uses such as energy and power consumption analysis, grid optimization, infrastructure planning, and achieving environmental goals. Meter Data Management System (MDMS) is a large customer-owned meter network with over 20,000 meters operated by the Department of Defense (DoD). MDMS meters measure energy and demand over fixed time intervals and report this data to a centralized server that stores and compiles data into reports. Users can change the parameters of these reports to suit their needs. Due to its size, complexity, and communication requirements, a variety of systemic MDMS issues resulted in erroneous meter data. Specifically, seven meter data issues were observed, and their causes were analyzed and defined. A novel data cleaning method was developed using a sequential series of seven algorithms to clean the data, creating more accurate meter data. Results are presented for West Point's MDMS data.

United States Military Academy (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 82%
Electricity Theft Detection Techniques
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