1 / 23

Working with AMI Data

Working with AMI Data. Eric Jung SouthEastern Illinois Electric Cooperative. Load Modeling. Hourly data advantages Accuracy! (less than 5% variance) Fast load allocation Hourly data disadvantages File verification & estimation difficult and time consuming

xander
Download Presentation

Working with AMI Data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Working with AMI Data Eric Jung SouthEastern Illinois Electric Cooperative

  2. Load Modeling • Hourly data advantages • Accuracy! (less than 5% variance) • Fast load allocation • Hourly data disadvantages • File verification & estimation difficult and time consuming • Must mix with traditional load allocation if AMI not 100% deployed

  3. File Setup • Interval files • Desired interval Di • Desired interval -1 Di-1 • Desired interval +1 Di+1 • Desired interval, different day (similar load characteristics) • Desired interval, different day 2 • Repeat until all meters have a reading

  4. File Setup Continued • Outage file (fast ping) for desired day • CIS data • Multiplier • Billing rate (optional) • Reactive load • Matching field to outage table • Location number link to Premise ID

  5. Validation • Pulse count to KW multiplier: (≠ Kh) • Verify meter type, multiplier and module match (Kw * 1000) / Multiplier = Pulse count

  6. Estimation • If valid read from desired interval (Di) use it directly • If not use Di-1 or Di+1 • If all three invalid use same interval from different day • Repeat until valid reads for all meters

  7. Reading Modification • Sum total load by interval • Apply adjustment factor by percentage difference between intervals. • Ie. Di-1 total load is 5% < Di. Divide all Di-1 reads by 95% • Suggest applying adjustment factors by billing rate.

  8. Additional Load Info • Take phasing from Outage file on single phase meters • Three phase loads must come from another source: • CIS • Mapping • Reactive load must come from CIS

  9. Table links - Blue Data source - Green

  10. Load Application for 100% AMI • One load group • Set sources to swing • Set CF% to 100% • PF % only applies to those without KVAR • Apply load and save errors!

  11. Load Application for < 100% AMI • All AMI data in one load group • Settings for this load group will be as for 100% AMI • Remainder will be as traditional • Run load allocation and save errors!

  12. Phasing Correction • Match load file phasing with error file from load application • Use “re-phase elements in file” updateable utility to phase according to load file • Re-run load application and view errors • Errors will be connectivity errors

  13. Accuracy • Absolute: 3.3% (average deviation) • Individual phase variation >10A indicates phasing or loading errors. • Normal < 5 A error per phase at feeder level

  14. Two Feeder Examples • Johnston City NW (average feeder) • Shell East (very accurate)

  15. Lessons learned • Check large industrial loads • If load down during peak, consider adjusting to realistic level for analysis • Trust the Twacs phasing, but check for phase rolls in software • Scrutinize the pulse count multipliers! • There will be errors!

  16. Blink File Import • Setup blink file using AMI momentary outage data • Suggest weekly or monthly intervals • Use “apply reliability indexes” utility • Element name,saidi,saifi,caidi… • Element name,blink week 1,blink week 2…

  17. Blink Analysis • Set “color by custom” • Graphical indication of blinking line sections

  18. Blink Analysis Example

  19. Single Outage File Import • Similar to blink file import • Leave only location and on/off status in file • Convert outage status into 1 (on) or 0 (off) • Save as CSV and load as “reliability.txt” • Provides a snapshot of system status

  20. Multiple Outage File Import • Link several outage files together based on location • Create one master database with several on/off entries (maximum of 6) • i.e. Element name,2pm result, 4pm result… • Provides progress view of system restoration

  21. Outage Analysis • Single outage file: • Color by custom based on phase • Highlights line section outages • Multiple outage file • Color by custom based on status change

  22. Conclusions • AMI data can bring load model accuracy to the next level • Apply reliability indexes utility is an extremely flexible tool • AMI data is not likely to save time on load allocation

  23. Contact Info • Eric Jung • Engineering and Purchasing Manager • SouthEastern Illinois Electric Cooperative • ericjung@seiec.com

More Related