P34.004: Underground Transmission Asset Data Analytics

Member Needs Assessment aims to work with member utilities to understand their unmet UGT asset management needs and investigate what research can help address those needs. The findings will be used in the development of R&D projects and the application of EPRI knowledge and tools to support UGT asset management applications.

UGT Asset Characterization and Performance Data Collection plans to support the identification and collection of data needed to support asset management by:

• Developing and annually updating data models for the efficient and effective extraction, transfer, and loading of test, diagnostics, performance, and failure data for use in industry and utility database applications and performance analysis. These models include detailed lists of what data should be collected and what kind of analysis and decisions can be supported. Data models and definitions developed in previous years for extruded, pipe-type, and self-contained cables, joints, and terminations are intended to be reviewed and updated and new asset data models may be developed.

• Working with member utilities to ensure that collection of equipment performance and failure data is performed according to guidelines that ensure that the correct data are gathered and documented in the correct format for subsequent analysis.

Insights from the Collection and Analysis of Industrywide Failure and Performance Data proposes to collect and analyze industrywide asset component failure and performance data with the goal of developing metrics such as failure rates. The new metrics may help utilities better understand component and subsystem performance (e.g., joint and termination defects; oil filled cable leak rates etc.), identify outlier designs and optimize maintenance, repair/replacement decisions, and specification practices. Annually issued reports summarize the development and applications in decision support, insights on component performance, and utility use cases.

Applying Advanced Data Science and Artificial Intelligence to Improve Defect Classification from Work Order Analysis to Support Underground Transmission Asset Management intends to evaluate the applications of various data science and artificial intelligence techniques to analyze alarm, inspection, and maintenance records to extract data for developing new metrics that could be applied to various types of underground cables and components.

Underground Transmission Line Risk Assessment Methodology Development aims to develop a conceptual framework for a risk assessment methodology to support UGT asset management. The goal is to provide analytics for underground lines, considering both individual components (such as conductors, pipes, terminations, pumping stations) and complete lines as an integrated system of components. Using industrywide data from condition assessment and failure modes and degradation research, subject matter expert experience, and other inputs (family, make, model, manufacturer, operating environment), a practical, holistic approach to transmission line risk assessment will be investigated.

UGT Condition Assessment Rule Based Expert System intends to investigate the feasibility of an analytical framework and AI techniques to capture and retain the knowledge of retiring transmission experts to support the development of rule-based expert systems for UGT condition assessment asset management decision support.