Transformer Load Management
Actively monitor the loading on transformers across the distribution system
Transformers are critical and expensive assets that are essential to the safe and reliable deliver for electricity. Transformers are unmetered assets and understanding their performance and limitations requires the analysis of downstream data
Challenges
For decades utilities have relied on estimated data extrapolated from profiled monthly service point billing determinant data to determine the system peak load for seasonal peak-days across this system. Based upon class average load profiles (CALPs), engineers would then allocate the "peak-day’ load across all of system transformers based upon the CALPs of the downstream service points to estimate the peak load at each transformer. As AMI becomes ubiquitous this error prone calculation process can be replaced with simple arithmetic
What PowerRunner Provides
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Identify locational impacts of load and DER on every system asset
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Avoid overloading transformers and potential outages
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Evaluate the locational impact of DER
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Improve CAIDI SAIFI metrics
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Identify unanticipated load increases
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Use loading history on each transformer to evaluate expected loss-of-life
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Identify optimal sizing for transformer replacement - right size new transformers to handle existing load and possible load growth
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Use dashboards and alerts to identify transformers experiencing loading above the nameplate rating
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Focus an analyst’s attention on worst case offenders by region or by feeder.
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Identifying at-risk transformers
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Create lists of transformers that can be used in replacement programs.
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Maximizing usable life
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Understand the impact of sudden load growth
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Perform ‘what-if’ analysis to investigate strategies for managing new load
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Identifying under-utilized transformers which could have additional load added to maximize the value of the asset
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Make informed decisions with up-to-date information during storm restoration, car-pole accidents or routine pole maintenance
Use PowerRunner's Dashboard to
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View geospatial mapping of transformer overloads
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Provide a list of top overloaded transformers
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Provide users with a spatial view of search results
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Drill-downs from map or grid to a more detailed view of the transformer
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Identify winding failure suspects
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Provide a graphical view of load profile and voltage data
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Empower operators to customize maps for their investigation needs of the moment
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Transformer and substation representation with informative data pop-ups
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Relationships between transformers and service points using network connectivity lines
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Display layers and slider controls allow operators to modify how the data is filtered and represented geospatially