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Real-time Ranking of Electrical Feeders using Expert Advice Hila Becker  1,2 , Marta Arias  1 1 Center for Computational Learning Systems 2 Computer Science Department Columbia University
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Electrical System 1. Generation 2. Transmission 3. Primary Distribution 4. Secondary Distribution
The Problem ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Some facts about feeders and failures ,[object Object],[object Object],[object Object]
Feeder data ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Machine Learning Approach ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Feeder  Ranking Application ,[object Object],[object Object],[object Object],[object Object],[object Object]
Application Structure Static data SQL Server DB ML Engine ML Models Rankings Decision Support GUI Action Driver Action Tracker Decision Support App Outage data Xfmr Stress data Feeder Load data
Decision Support GUI
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Simple Solution ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Performance Metric ,[object Object]
Performance Metric Example ranking outages 0 8 0 7 0 6 1 5 0 4 1 3 1 2 0 1
Real-time ranking with MartiRank ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Real-time ranking with MartiRank time time time
How to measure performance over time ,[object Object],[object Object],[object Object]
Using MartiRank for real-time ranking of feeders ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Learning from expert advice ,[object Object],[object Object],[object Object],[object Object],[object Object]
Learning from expert advice ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Weighted Majority Algorithm  [Littlestone & Warmuth ‘88] ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Weighted Majority Algorithm  e 1 . . . e 2 e 3 e N N Experts w 1 w 2 w 3 w N 1 0 0 1 ? w 1 *1 + w 2 *0 + w 3 *0 +  . . .  + w N *1 >0.5 <0.5 1 0 1 ,[object Object],[object Object]
In our case, can’t use WM directly ,[object Object],[object Object]
Dealing with ranking vs. binary classification ,[object Object],[object Object]
Dealing with a moving set of experts ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Online Ranking Algorithm  e 1 . . . e 2 e 3 e B w 1 w 2 w 3 w B ? F1 F4 F3 F2 F5 F4 F2 F1 F3 F5 F1 F3 F5 F4 F2 F1 F3 F4 F2 F5 F1 F3 F4 F2 F5 F3 F1 F4 F2 F5 e B+1 e B+2 w B+1 w B+2
Other parameters ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Experimental Comparison ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Performance – Summer 2005
Performance – Winter 2006
Parameter Variation - Budget
Future Work ,[object Object],[object Object],[object Object],[object Object]

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Real-time Ranking of Electrical Feeders using Expert Advice

Notes de l'éditeur

  1. Generation: a prime mover, typically the force of water, steam, or hot gasses on a turbine, spins an electromagnet, generating large amounts of electrical current at a generating station Transmission: the current is sent at very high voltage (hundreds of thousands of volts) from the generating station to substations closer to the customers Primary Distribution: electricity is sent at mid-level voltage (tens of thousands of volts) from substations to local transformers , over cables called feeders, usually 10-20 km long, and with a few tens of transformers per feeder. Feeders are composed of many feeder sections connected by joints and splices Secondary Distribution: sends electricity at normal household voltages from local transformers to individual customers
  2. Many occur in the summer when the load on the system increases, during heat waves When an O/A occurs, the load that had been carried by the failed feeder must shift to adjacent feeders, further stressing them. This can lead to a failure cascade in a distribution network
  3. (e.g. age and composition of each feeder section) and e.g. electrical load data for a feeder and its transformers, accumulating at a rate of several hundred megabytes per day) Software engineering challenges to manage data
  4. with sufficient accuracy so that timely preventive maintenance can be taken on the right feeders at the right time.
  5. How to deal with impending failures that are corrected on the basis of our ranking
  6. Use data within a window, aggregate dynamic data within that period in various ways (quantiles, counts, sums, averages, etc.) Re-train daily, or weekly, or every 2 weeks, or monthly, or…
  7. Use data within a window, aggregate dynamic data within that period in various ways (quantiles, counts, sums, averages, etc.) Re-train daily, or weekly, or every 2 weeks, or monthly, or…
  8. No human intervention needed Changes in system are learned as it runs
  9. Every 7 days Seems to achieve balance of generating new models to adapt to changing conditions without overflowing system
  10. if a model was successful in the previous summer but was retired during the winter, it should be rescued back in the upcoming summer if similar environmental conditions reappear.