Working with AMI DataEric JungSouthEastern Illinois Electric Cooperative

Load ModelingHourly data advantages

Accuracy! (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 SetupInterval files

Desired 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 ContinuedOutage file (fast ping) for desired day

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

ValidationPulse count to KW multiplier: (≠ Kh)

Verify meter type, multiplier and module match

Multiplier = (Kw * 1000)/Pulse count

EstimationIf 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 ModificationSum 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 InfoTake 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% AMIOne 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 CorrectionMatch 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

AccuracyAbsolute: 3.3% (average deviation)

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

Normal < 5 A error per phase at feeder level

Two Feeder ExamplesJohnston 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 learnedCheck 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!

Blink File ImportSetup 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 ImportSimilar 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

Multiple Outage File ImportLink 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 AnalysisSingle outage file:

Color by custom based on phase

Highlights line section outages

Multiple outage fileColor by custom based on status change

ConclusionsAMI 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 InfoEric Jung

Engineering and Purchasing ManagerSouthEastern Illinois Electric Cooperativeericjung@seiec.com