resurrecting a load research program
DESCRIPTION
Resurrecting A Load Research Program. Susan Romer NSTAR 2006 AEIC Load Research Conference September 2006. NSTAR Territory. Massachusetts’ Largest Investor-owned Electric And Gas Utility Transmitting & Delivering Electricity & Natural Gas For More Than 100 Years - PowerPoint PPT PresentationTRANSCRIPT
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Resurrecting ALoad Research Program
Susan RomerNSTAR
2006 AEIC Load Research ConferenceSeptember 2006
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NSTAR Territory
NSTAR Electric
NSTAR Gas
Combined Gas & Electric
•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
•@ 3,200 employees
Electric Gas
Residential 970,000 160,000
Business 225,000 20,000
Total 1,195,000 180,000
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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%)
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Where’s Load Research
1993-1998Homeless
1993Dismantled
1999Sales??
Load Research
1980-1993Rates
PURPA Baby
2005Load Services
2000Energy Supply
Finance & Accounting > Energy Supply > Load Services > Load Research – 1 Analyst > Load Settlement & Load Response – 3 Engineers
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Detour Impact
Loss of employees with knowledge
No senior management sponsor
No field commitment “Those Meters Are Only Used For Research”
Data not available when needed
Load data gateway shifted to others
Load Research
1992 - 10 Year Rate Freeze1993 - MA Electric Deregulation1999 - Merger2000> - Management Changes
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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
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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
Senior ManagementSponsorship
Fear ofFinancial Exposure
=
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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
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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 FailuresLoad Profiling Error** – Sample EstimatesAccounting Error – Billing EstimatesDistribution Loss Estimation Error – Incorrect Loss FactorsTheftUn-metered Energy – Company Use
•Revenue Annually @$2 Billion
ProfiledLoads55%
TOULoads45%
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Load Research ProgramAssessment 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%
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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
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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
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Residential R-1 Relative Precisions MPU Vs. Ratio Estimation
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
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
Pre
cisi
on
%
MPU Ratio
Improved Average Relative Precision From 16.33 to 13.10
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Small GS G-1 Relative Precisions MPU vs. Ratio Estimation
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
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
Pre
cisi
on
%
MPU Ratio
Improved Average Relative Precision From 25.72 to 11.17
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Post StratificationAssignment Distribution
Strata OriginalAssignment
Post Stratified
Assignment
1 20 21
2 25 23
3 25 30
4 25 21
Strata OriginalAssignment
Post Stratified
Assignment
1 28 36
2 24 21
3 27 26
4 28 24
ResidentialR-1
Small General ServiceG-1
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Residential R-1 Relative PrecisionsRatio Estimation Post-Stratified
Ratio Estimation vs. Ratio - Post Stratified Commonwealth Rate Residential General Service R1
July 2005
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
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
Pre
cisi
on
%
Ratio Ratio-Post Stratified
Improved Average Relative Precision From 13.10 to 10.97
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Small GS G-1 Relative Precisions Ratio Estimation Post Stratified
Ratio Estimation vs. Ratio - Post Stratified Commonwealth Small General Service G1
July 2005
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
40.0
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
Pre
cisi
on
%
Ratio Ratio-Post Stratified
Improved Average Relative Precision From 11.17 to 9.83
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Relative Precision Ranges
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
Reduction in Variability in the Precision Values
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New Sample DesignsObjectives• 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
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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• 13 Sampled Rates
– @2002 Sample Meters• 11 100% Monitored Rates (TOU)
– @4400 Meters• @225 Interchange Meters
Current Samples
BECO COMM CAMB TOTAL
R-1 109 100 140 349
R-1-WH 102 102
R-2 99 99
R-3 138 90 64 292
G-0 0
G-1 115 120 124 359
G-2 0
G-2C 90 90
G-2I 90 90
743 310 328 1381
New Samples
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-2 160 160
823 594 603 2020
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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
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Load Research Roadmap
Re-Engineer To MonthlyProduction
Redesign and Install
New Samples
Build Sample Tracking
System
Load Research
Recast Analysis
Use Same Month Profiles For Settlement
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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
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Now, Who’s Driving the Bus?
Load Research
Data Heaven