Resurrecting A
Load Research Program
Susan Romer
NSTAR
2006 AEIC Load Research Conference
September 2006
1
NSTAR Territory
•Massachusetts’ Largest Investor-owned
Electric And Gas Utility
•Transmitting & Delivering Electricity &
Natural Gas For More Than 100 Years
•Serve @1.4 M Residential & Business
Customers In Over 100 MA Communities
Electric
NSTAR Electric
Gas
Residential
970,000
160,000
Business
225,000
20,000
Total
1,195,000
180,000
NSTAR Gas
Combined Gas &
Electric
•@ 3,200 employees
2
NSTAR - Electric
•
Three Electric Operating Companies
– Boston Edison Company (BECO)
– Commonwealth Electric (COMM)
– Cambridge Electric (CAMB)
•
•
•
4,959 MW – Peak Load (08/02/06-4 PM)
23,236 GWh – 2005 Annual Energy
17% Share of ISO-New England Load
•
Load And Customers Served by 13 Competitive Suppliers as of July 2006
– 47% of load
• (Industrial – 77%; Commercial – 28%; Residential 16%)
– 18% of customers
• (Industrial – 59%; Commercial – 26%; Residential 17%)
3
Where’s Load Research
Load Research
1999
Sales??
2005
Load Services
2000
Energy Supply
1993-1998
Homeless
1993
Dismantled
1980-1993
Rates
PURPA Baby
Finance & Accounting
> Energy Supply
> Load Services
> Load Research – 1 Analyst
> Load Settlement & Load Response – 3 Engineers
4
Detour Impact
1992 - 10 Year Rate Freeze
 Loss of employees with knowledge
1993 - MA Electric Deregulation
 No senior management sponsor
1999 - Merger
2000> - Management Changes
 No field commitment
Load Research
 “Those Meters Are Only Used For Research”
 Data not available when needed
 Load data gateway shifted to others
5
Regulatory Requirements
• Continuous Load Research
• Meet 95/10 Sample Results Accuracy Levels
• Most Northeast Utilities Perform Load Research At 95/5
Accuracy Levels
• Many Northeast Utilities Use Same Month Profiles For
Settlement Month
6
Opportunities
• 2004 Rate Case and No Load Research Data
• Awareness of ISO Settlement Dispute B/W Two Other Parties
• Understanding of How Interchange Point Malfunction Can
Impact the Calculation of System Loads
• 2005 Energy Policy Act DST Change
Fear of
Financial
Exposure
=
Senior
Management
Sponsorship
7
Load Research Supports
• Estimation of Competitive Supplier Loads and ICAP Values
• Development of Rates Charged to Customers
• Unbilled Energy Sales And Unbilled Revenues Balances
• Billed/Unbilled Sales & Substation Forecasts
• Accrual Of Purchased Power Expense As Compared to Actual
• Development of Rates Charged to Customers
• Local Network Service Billing for Wholesale Customers
• Regional Network Transmission Billing for ISO
• Development of Engineering Loss Studies
8
Load Settlement & Load Research
•Determine suppliers’ load obligations from load research
for the purposes of ISO-New England energy market settlement
•A contributing factor to unaccounted for energy (UFE)
Metering Error – Meter Failures
Load Profiling Error** – Sample Estimates
Accounting Error – Billing Estimates
Distribution Loss Estimation Error – Incorrect Loss Factors
Theft
Un-metered Energy – Company Use
•Revenue
 Annually @$2 Billion
Profiled
Loads
55%
TOU
Loads
45%
9
Load Research Program
Assessment Observations
• Age of the Samples - Over 9 Years Old
• Significant Data Loss – 47% for BECO
• Sample Sizes All Less than 30 Per Stratum
• Sample Bias Caused By Installation Procedures
– Over 50% Indoor Meters
– “Don’t Really Need THOSE Meters”
• Relative Precisions Averaged from 20-30%
10
Sample Augmentation Plan
We Need To Consider Options To Improve The Sample
Results Until The New Samples Are Installed.
Techniques
•
Ratio Estimation
– Takes Advantage Of The Correlation Of The Variable Of Interest With Another
Variable To Increase Precision
•
Post Stratification
– Can Be Used Within A Sample Study, But Can Also Be Utilized To Post
Stratify Transferred Data From Another Utility With Similar Population
Characteristics
•
Load Data Transfer
– A Transfer of Load Data From One Distribution Company To Another
Distribution Company For Certain Samples. Can Utilize Post Stratification To
Fit The Transferred Data To The Sample
11
Preliminary Test Results
• 2 Primary Goals
– To Improve the Current Sample Results in the Interim
– To Use Ratio Estimation as an Expansion Methodology
• Tested 2 Samples for July 2005
– Commonwealth Residential R-1
– Commonwealth Small General Service G-1
• Looked At Relative Precisions
– Ratio Estimation Versus Mean-Per-Unit
– Ratio Estimation Versus Ratio Estimation Post-Stratified
• Did Not Look At Load Data Transfer, Yet
12
Residential R-1 Relative Precisions
MPU Vs. Ratio Estimation
Mean Per Unit vs. Ratio Estimation
Commonwealth Residential General Service R1
July 2005
40.0
Improved Average Relative Precision From 16.33 to 13.10
35.0
30.0
Precision %
25.0
20.0
15.0
10.0
5.0
0.0
1
25
49
73
97
121 145 169 193 217 241 265 289 313 337 361 385 409 433 457 481 505 529 553 577 601 625 649 673 697 721
MPU
Ratio
13
Small GS G-1 Relative Precisions
MPU vs. Ratio Estimation
Mean Per Unit vs. Ratio Estimation
Commonwealth Small General Service G1
July 2005
40.0
Improved Average Relative Precision From 25.72 to 11.17
35.0
30.0
Precision %
25.0
20.0
15.0
10.0
5.0
0.0
1
25
49
73
97
121 145 169 193 217 241 265 289 313 337 361 385 409 433 457 481 505 529 553 577 601 625 649 673 697 721
MPU
Ratio
14
Post Stratification
Assignment Distribution
Residential
R-1
Small General Service
G-1
Strata
Original
Assignment
Post
Stratified
Assignment
Strata
Original
Assignment
Post
Stratified
Assignment
1
20
21
1
28
36
2
25
23
2
24
21
3
25
30
3
27
26
4
25
21
4
28
24
15
Residential R-1 Relative Precisions
Ratio Estimation Post-Stratified
Ratio Estimation vs. Ratio - Post Stratified
Commonwealth Rate Residential General Service R1
July 2005
40.0
Improved Average Relative Precision From 13.10 to 10.97
35.0
30.0
Precision %
25.0
20.0
15.0
10.0
5.0
0.0
1
25
49
73
97
121 145 169 193 217 241 265 289 313 337 361 385 409 433 457 481 505 529 553 577 601 625 649 673 697 721
Ratio
Ratio-Post Stratified
16
Small GS G-1 Relative Precisions
Ratio Estimation Post Stratified
Ratio Estimation vs. Ratio - Post Stratified
Commonwealth Small General Service G1
July 2005
40.0
Improved Average Relative Precision From 11.17 to 9.83
35.0
30.0
Precision %
25.0
20.0
15.0
10.0
5.0
0.0
1
25
49
73
97
121 145 169 193 217 241 265 289 313 337 361 385 409 433 457 481 505 529 553 577 601 625 649 673 697 721
Ratio
Ratio-Post Stratified
17
Relative Precision Ranges
Reduction in Variability in the Precision Values
Residential
Small
General Service
Mean Per Unit
10.4 - 34.3
17.9 - 38.3
Ratio
07.9 – 29.2
05.9 – 30.8
Ratio Post Stratified
06.5 – 20.2
06.5 – 25.0
18
New Sample Designs
Objectives
•
Achieve Design Accuracy Of +/- 5% At The 95% Confidence Level For All
Hours Of The Year
•
Stay Within Budget Constraints
•
Use Stratifying Variables That Will Achieve The Targeted Accuracies For All
Hours Of The Year
•
Utilize A 100% (Certainty) Stratum In The Design Process When Feasible
•
Have Longevity Of At Least Five Years
•
Represent Target Populations Optimally
•
Have A Minimum Of 30 Sample Points In Each Stratum
•
Minimize Sample Bias In The Installation Procedures
19
Current and Proposed Program
•
•
•
Do We Need A Separate Sample
For R-1 Water Heating (WH)? No
Do We Need A Separate Samples
For R-2? Yes
Do We Need Separate Samples
For BECO’s G-2 Commercial And
G-2 Industrial? No
• Proposed
•
Current Samples
BECO
COMM
109
R-1-WH
102
102
R-2
99
99
R-3
138
90
140
TOTAL
R-1
64
349
292
G-0
G-1
0
115
120
124
359
G-2
0
G-2C
90
90
G-2I
90
90
743
310
328
1381
13 Sampled Rates
– @2002 Sample Meters
•
100
CAMB
New Samples
11 100% Monitored Rates (TOU)
– @4400 Meters
• @225 Interchange Meters
BECO
COMM
CAMB
TOTAL
R-1
220
176
160
556
R-2
82
88
80
250
R-3
161
165
165
491
G-1
200
165
198
563
G-2
160
823
160
594
603
2020
20
Program Objectives
• Have a quality, compliant, and maintainable load research program
• Lower risks of disputes in regulatory proceedings and in ISO
settlements
• Minimize loss of data
• Improve the predictability of costs of operations, maintenance, &
future capital expenditures
21
Load Research Roadmap
Load Research
Re-Engineer
To Monthly
Production
Use Same
Month Profiles
For Settlement
Build
Sample Tracking
System
Recast
Analysis
Redesign and
Install
New Samples
22
Next Steps
• Sharing Performance Metrics
– Between Metering, Meter Data Management, & Load Services
– Sample Installation Rate; Data Retrieval Rate; Interval Meter Check
•
•
•
•
•
•
Installing The New Samples – 2006 and 2007
Build a Sample Tracking System
Improve Data Validation Procedures
Re-Engineer Load Profile Production to Monthly For Settlement
Implement A Process Of Load Study Cycling And Replacement
Cross Training
–
Cloning the Old Fashion Way
23
Now, Who’s Driving the Bus?
Data
Heaven
Load
Research
24