Working with AMI DataEric Jung

SouthEastern Illinois Electric Cooperative

Load Modeling

Hourly data advantagesAccuracy! (less than 5% variance)Fast load allocation

Hourly data disadvantagesFile verification & estimation difficult and time consuming

Must mix with traditional load allocation if AMI not 100% deployed

File Setup

Interval filesDesired interval DiDesired interval -1 Di-1Desired interval +1 Di+1Desired interval, different day (similar load characteristics)

Desired interval, different day 2Repeat until all meters have a reading

File Setup Continued

Outage file (fast ping) for desired day

CIS dataMultiplierBilling rate (optional)Reactive loadMatching field to outage tableLocation number link to Premise ID

Validation

Pulse count to KW multiplier: (≠ Kh)

Verify meter type, multiplier and module match

Multiplier = (Kw * 1000)/Pulse count

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

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.

Additional Load Info

Take phasing from Outage file on single phase meters

Three phase loads must come from another source:CISMapping

Reactive load must come from CIS

Outage Data

Location #

Meter #

Module #

Phase

Substation

Master Table

Location #

Meter #

Module #

Phase

Substation

Multiplier

Load Interval 1

Load Interval 2

KVAR

Interval Data 1

Module #

Meter #

Meter Type

Pulse Count

Kw (converted pulse)

 

Table links - BlueData source - Green

CIS Data

Location #

PF%

Multiplier

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!

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!

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 errorsErrors will be connectivity errors

Accuracy

Absolute: 3.3% (average deviation)

Individual phase variation >10A indicates phasing or loading errors.

Normal < 5 A error per phase at feeder level

Two Feeder Examples

Johnston City NW (average feeder)

Shell East (very accurate)

Modeled Actual % Diff KW 3098.2 3007.7 3.01% KVAR 608.9 635.7 4.22% A Amps 148.5 139.8 6.19% B Amps 133.9 134.6 0.49% C Amps 138.7 133.5 3.86%

Modeled Actual % Diff KW 3959.0 3964.8 0.15% KVAR A Amps 209.1 211.1 0.93% B Amps 151.2 149.1 1.44% C Amps 165.4 160.0 3.34%

Lessons learned

Check large industrial loadsIf 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!

Blink File Import

Setup blink file using AMI momentary outage dataSuggest weekly or monthly intervals

Use “apply reliability indexes” utility Element name,saidi,saifi,caidi…Element name,blink week 1,blink week 2…

Blink Analysis

Set “color by custom”

Graphical indication of blinking line sections

Blink Analysis Example

Single Outage File Import

Similar to blink file importLeave 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

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

Outage Analysis

Single outage file:Color by custom based on phase

Highlights line section outages

Multiple outage fileColor by custom based on status change

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

Contact Info

Eric JungEngineering and Purchasing ManagerSouthEastern Illinois Electric Cooperativeericjung@seiec.com