Substation Equipment Spares Strategy Evaluation Model Development
There is a growing concern among utilities due to increasing transmission asset delivery lead times. To help address the concern, EPRI researchers are developing a methodology to help utilities understand the risks associated with different strategies for ordering and stocking substation equipment spares.
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Establish the value and use of various types of circuit breaker performance data (e.g., work orders, defects, failure records, relay data etc.)
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Collect and analyze industrywide data to develop maintenance, asset management and model specific insights
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Utilize the insights and utility’s fleet data to develop maintenance and replacement ranking framework
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Guide utilities on what data they should have access to for asset management analytics
Power Transformer Through Fault Analytics
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Develop & validate algorithms to assess the susceptibility of a power transformer to through faults.
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Establish value and use of various types of asset performance data (e.g., historical battery test data)
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Collect and analyze industrywide data to develop maintenance, asset management and model specific insights
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Research currently underway focuses on batteries, disconnect switches, capacitor banks and relays.
Advanced Analytics (e.g., Machine Learning, Natural Language Processing etc.) evaluates various techniques to identify whether they can be used:
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To develop methods to transform a variety of asset performance data into an analysis ready format
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To develop methods to analyze the transformed data
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To categorize maintenance and outage records into meaningful categories
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To extract actionable information such as dominant issues and trends, non-apparent patterns and relationships
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For predictive analytics.