MET ETHODS HODS FOR OR CALCULA CULATING TING LEA EAKA KAGE GE - - PowerPoint PPT Presentation

PLUGGING GGING THE E HOL OLES ES IN LEAK EAKAGE: GE: MET ETHODS HODS FOR OR CALCULA CULATING TING LEA EAKA KAGE GE OU OUT OF OF AND D INTO O UPSTR TREAM EAM RES ESIDENTIAL DENTIAL LIGHTING GHTING PROGRA OGRAMS MS

Tami Buhr, Opinion Dynamics Amy Buege, Itron

What is Lighting Program Leakage…and Wh Why do

• We Ca

e Care? e?

IEPEC 2017 2

▪ Sales of program-discounted bulbs to customers of another utility

▪ Can’t limit sales with upstream program design

▪ Lighting program savings are shrinking as market transforms

▪ Limiting leakage is one way to maximize remaining savings ▪ But first, we need to be confident in how to measure it

IEPEC 2017 3

▪ Little consistency in measurement or application of leakage across country ▪ Reviewed 11 TRMs and the UMP

▪ Less than half mentioned leakage (5 of 12) ▪ Only two described leakage methods

▪ In-store interviews ▪ GIS Analysis

Me Meas asuring uring Leak akage: age: The he Sta tate e of th the Industr dustry

State Mentioned tioned Up Upstre ream am Res.

• s. Lighti

ting Leak akage Estima imatio ion Met ethods hods Descr scrib ibed? d? Arkansa sas Yes Yes UMP Yes Yes Illinois inois Yes No Pennsylv sylvania ia Yes No New York Yes No Mass ssac achuse setts ts No No Indiana iana No No Texas as No No Connec ecticut ticut No No Minneso esota ta No No Wiscons sconsin in No No Ver ermo mont No No

IEPEC 2017 4

▪ Estimate leakage by asking customers for the name of their electric utility ▪ Main objective is usually to estimate program free- ridership ▪ Sample stores may not be selected in a manner to accurately estimate secondary objectives such as leakage (coverage bias) ▪ Can only measure leakage

• ut

Leak akage age Met Metho hods: ds: In-St Store re Cust stomer

• mer Inter

erce cept pt Inter ervie views ws

IEPEC 2017 5

▪ Estimate leakage by mapping participating retailers and utility customers

▪ Define store territories by drawing distance-based buffers around each store

▪ Leakage rate is the percentage of opposing utility households within the buffer ▪ Sales weight the results so that stores with more sales have a greater influence

• n overall leakage rate

Leak akage age Met Metho hods: ds: GIS Analysis alysis

IEPEC 2017 6

▪ Requires simplifying assumptions about customer purchase behavior (questionable internal validity) ▪ Can estimate both leakage out and leakage in, though sales data are required for the most precise estimates

Leak akage age Met Metho hods: ds: GIS Analysis alysis (2 (2)

Two

• Met

Methods, hods, Two

• Uti

tilit lities, ies, On One Bo Borde der, , Zero

• Wal

alls ls

IEPEC 2017 7

▪ Ameren Illinois Company (AIC) and Commonwealth Edison (ComEd) ▪ Estimate leakage along the AIC/ComEd border using intercepts and GIS ▪ AIC: 725 participating stores ▪ ComEd: 1,151 participating stores

IEPEC 2017 8

Defini ining ng Leak akage age Ou Out t & Le Leak akage age In for AIC IC Leakage Out Leakage In

AIC Program bulbs ComEd Program bulbs

Inter ercep cept t Met Method hod Detai etails ls

IEPEC 2017 9

▪ Conducted intercept interviews at between 23-26 stores

▪ AIC: 335 ▪ ComEd: 400

▪ Examined leakage from sampled stores within 15 miles of AIC/ComEd border ▪ Most sampled participating stores near territory borders, mirrors population

Population Sample Utility Stores Within 15 Miles of Border Part. Stores Border % Stores Within 15 Miles of Border Part. Stores Border % AIC 47 725 5% 1 26 4% ComEd 106 1151 9% 2 23 9%

Resul sults: ts: In-Store re Inter ercepts cepts

IEPEC 2017 10

▪ Intercept interviews at stores within 15 miles of AIC/ComEd border did not identify any customers from the neighboring utility purchasing program- discounted bulbs ▪ Overall intercept sample reflects population pretty well in terms

• f distance to all borders, but

sample size is too small to estimate leakage out of or into a single border

AI AIC ComEd mEd Leak akage ge Ou Out 0.00% 0.00% Leak akage ge In 0.00% 0.00% Tot

• tal

al Leak eakage age 0.00% 0.00%

GIS Met Method hod Detai etails ls

IEPEC 2017 11

▪ Uses sales data from participating stores ▪ Store territory = 15 mile buffer surrounding the store

▪ Assumes that all customers within the territory have equal opportunity to purchase bulbs ▪ We distribute program-discounted bulbs sold at each store equally across all households in territory

▪ Focused on “leakage susceptible stores” along AIC/ComEd border

▪ Those that have customers from neighboring utility within store territory

Resul sults: ts: GIS Analysis alysis

IEPEC 2017 12

▪ Calculated leakage out and leakage in for both utilities for both years ▪ AIC has more bulbs leaking in than leaking out ▪ ComEd has more bulbs leaking out than leaking in

▪ ComEd had more leakage- susceptible stores near the border than AIC, which also sold more program-discounted bulbs than AIC leakage- susceptible stores

AIC ComE mEd Leaka kage ge Out 2.51% 1.68% Le Leaka kage ge In 3.16% 1.33% Tot

• tal

al Leaka kage ge 0.65%

• 0.35%

Sensi nsitivity tivity Analysi alysis s of Rad adius ius Par Paramet ameter er

IEPEC 2017 13

▪ The leakage estimates can vary significantly using different buffer radii ▪ These differences may be due to the irregular shape of the AIC/ComEd border, varying communities on either side of the border, and sporadic shifts in household density

Utility ty 10 10-Mil ile e Radius ius 15 15-Mil ile e Radius ius 20 20-Mil ile e Radius AI AIC 8.53% 0.65%

• 4.92%

ComEd mEd

• 6.35%
• 0.35%

1.13%

Ex Example ample of Par Param ameter er Sensitivity sitivity for Single le AIC IC Store re

IEPEC 2017 14

Radiu ius s (in miles) s) AIC C Cust stomer

• mers

ComE mEd Cust stomer

• mers

% % Leaka kage ge Out to ComE mEd 10 10 13,784 453 3% 15 15 19,537 2,531 11% 20 20 23,301 20,544 47%

Intercept Method GIS Method

Key y Tak akea eaways ys

IEPEC 2017 15

▪ Pros

▪ Can produce accurate estimate

• f leakage out for overall territory

if sample stores locations are representative of population

▪ Cons ns

▪ Samples are too small to estimate leakage to a single utility ▪ Not practical to estimate leakage in ▪ Expensive

▪ Pros

▪ Both leakage out and leakage in ▪ Can use to estimate leakage to single utility ▪ No sample required ▪ Is inexpensive

▪ Co Cons

▪ Requires untested simplifying assumptions ▪ Requires access to bulb sales data from opposing program for leakage in estimates to be precise

tbuhr@opiniondynamics.com 617-492-1400 ext 4654

Tami Buhr

Thank ank you