customer-friendly demand response

July 21, 2006

Customer-Friendly Demand Response

Chris King

Chief Strategy Officer, eMeter

Chair, SVLG Demand Response Subcommittee

2© eMeter Corporation 2006

Who’s eMeter?

Company Background & Qualifications

• Founded in Silicon Valley in 1999 by original executive group from CellNet

– Team pioneered advanced metering infrastructure technology

• Develop and sell Advanced Meter Information Systems (AMIS) software

1. Advanced Metering Business Process Management (BPM)

2. Meter Data Management

3. AMI Integration Platform

• Experience in all aspects of AMI implementation

– AMI technologies,

– Software implementation,

– Data collection and management,

– Deployment & operations,

– Business and regulatory strategy

Business Focus

• Software & professional services

• Strategic consulting on AMI issues


Why is Demand Response Important?Price-based

•Tool for customers to manage bills

•Keeps wholesale prices in check

Reliability

•Protects the grid

•Prevents rolling blackouts

Over 975 MW Over 975 MW shed in 60 shed in 60 secondsseconds

Generator Down, Emergency Control

(SCRAM)

Generator RestorationStarted

RestorationSuspended

More Generation Down, System re-SCRAM

RestorationStarted

TIMETIME

SY

ST

EM

SY

ST

EM

LO

AD

(M

W)

LO

AD

(M

W)

Case Study 1: Loss of 1,000 MW Power Plant


Main Job of Customers is Not Energy

Source: Primen


Even Facility Managers Spend Little Time on Energy

Source: Primen


Customers & Utilities Don’t Speak the Same Language

Source: Primen


Primary Customer Energy Concerns

Source: Primen


Tools That Help With Pricing

Source: Primen


Market Research – Commercial Customer Concerns

Statements regarding energy efficiency investments

Source: Quantum Research


Commercial Pricing Preferences

Source: NYSERDA


What is DR: Price-Based vs. Reliability Programs

Price-based

•Goal is to provide price signal

•Demand reductions occur via voluntary end-use customer response

•Reductions are included in load forecasts

•Response levels become more predictable as a function of:

–Transparency/foreknowledge of prices

–Weather

–Experience

–Diversity (number and types of customers)

Examples: critical peak pricing, real-time pricing


What is DR: Price-Based vs. Reliability Programs

Emergency/reliability

•Goal is “load acting as a resource”

•Demand reductions occur via dispatch by system operators

•Reductions are included in resource/supply portfolio

–Same as a power plant (with limitations)

•Response levels more variable

–Minimal foreknowledge by end-use customers

–Dispatch reasons varied

–Less diversity in loads involved

Examples: interruptible programs or demand bidding programs with penalties


Customer-Friendly Demand Response

Principles developed by SLVG (subset)

•Voluntary

–Default programs must have no penalty for “opting-out”

–PUC ruling on critical peak pricing for large commercial customers adopted SVLG’s principle

•Easy to participate

–Minimize complex forms and procedures

–Avoid specific peak reduction targets (e.g. minimum of 100 kilowatts)

•Easy to understand

–Maintain stable programs over time

•Easy to reduce demand

–Promote availability of automation technology through incentives and rebates

•Good value

–Customers should be fairly rewarded for their efforts

–The benefits should be maximized relative to the cost


Case Study 2: CPUC Ruling on Critical Peak Pricing

Decision in spring 2006

Requires utilities to implement “default” critical peak pricing for customers above 200 kW

•Decision does not say when

•Decision says the rate design will be covered in a “future” rate case

–Unlikely to see anything before the summer of 2008

Customer-friendly features

•Promoted by SVLG in the proceeding

•Adopted in decision

Key customer protections

•CPP is to be voluntary, meaning customers can opt-out with zero penalty to their current time-of-use rate

•Opting out must be very easy – no more than a phone call or email

•Customers have bill protection for their first year

–Can pay no more on the CPP price than the TOU

•Customers must be fully informed as to the likely bill effects


Critical Peak Pricing: What is it?

$-

$0.10

$0.20

$0.30

$0.40

$0.50

$0.60

Sunday Monday Tuesday Wednesday Thursday Friday Saturday

Pri

ce

per

kW

h

Off-Peak

Peak (12-6 pm)

Critical Peak (12-6 pm)

Critical Peak Notification to Customer (by 5 p.m.)


Case Study 3: Two-Part Real-Time Pricing

Georgia Power Company

Very high participation

•1,700 customers (80% of those eligible)

•> 5,000 MW peak load; 500 to 1,000 MW peak reduction

•Voluntary

•Day-ahead (75%) and hour-ahead (25%) hourly pricing

•Prices based on wholesale market with adjustments

Features

•Customer pays for baseline level of usage at standard tariff prices

•Deviations from baseline – increases or decreases – billed at RTP price


kW

1 24

Actual load

Customer “sells” load at high RTP prices

Customer “buys” load at low RTP prices

Baseline

Hour of Day

Two-part RTP Example

Source: Christensen Associates


0.60

0.70

0.80

0.90

1.00

1.10

1.20

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Hour

Nor

mal

ized

Loa

d

0

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6

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Loga

rithm

of

Pric

e ($

/MW

)

Load at highest prices

Highest prices

Reference Load

Load at moderate prices

Reference prices

Moderate prices

Load Response, by Price Day-type



Price Elasticities: Commercial Office Buildings

0.000

0.050

0.100

0.150

0.200

0.250

0.300

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1 3 5 7 9 11

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Elasticity is the amount load is reduced when the on-peak price is doubled


Price Response Curve

Utility able to predict response accurately based on price level, using historical data

0%

5%

10%

15%

20%

25%

30%

35%

$0 $1,000 $2,000 $3,000 $4,000 $5,000 $6,000

$/MWh

% L

oa

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uc

tio

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Case Study 4: Anaheim Peak Time RebateProgram concept

•Identify critical peak days a day in advance based on forecast high temperatures in Anaheim

•Notify customers a day in advance via automated telephone and, if desired, email

•Customers reduce consumption between noon and 6 p.m. on critical peak days

•Reduction is recorded via hourly meters and the data sent back after midnight

•Customers receive a rebate of $0.35 per kWh for each kWh below their “baseline” usage on the event day (what they normally would have used from noon to 6 p.m.)

Program benefits

•Provide customers with choices

–Realize bill savings by curtailing peak demand during the top 50 to 100 hours per year (“critical” peaks)

•Reduce utility cost to serve

–Lower peak capacity needs in the long run once programs are in place, tested, and shown to deliver reliable load reductions


Peak-Time Rebate

Establish customer baseline

•Three highest of previous 10 non-event weekdays

Rebate is reduction times the price (30 cents per kWh rebate)

No risk to customer

No need to meet specific reduction targets

kW

1 24Hour of Day

12

Peak hoursPeak reduction


Program OperationsExperimental sample provided with meters

•Sample designed by Professor Frank Wolak of Stanford University

Recruitment

•Recruitment via direct mail

•No incentive payment

Customer education

•Customers sent fact sheets and a refrigerator magnet

•Webpage added to anaheim.net with FAQs and other info

•Customer service via 800 number and email enabled

Events

•12 events in 2005

•Included both days when California grid had problems

Results

•13% peak reduction – same as reduction measured in critical peak price program

•SDG&E has proposed rolling this out to all of its small business and residential customers


Case Study 5: Auto-DR

Nationwide test by Lawrence Berkeley National Labs

Automated response to hourly prices

•Prices published on server

•Customer systems grab prices automatically

•Energy management system controls load in response to prices


Auto DR Results


Auto DR Results: Office Buildings


Customer Shed Strategies


Conclusions

Demand response and energy information are of interest to a subset of businesses

•For whom controlling energy costs is a major concern

•Who are provided with tools to manage energy costs

Some good success stories

Customer-friendly demand response programs are:

•Simple

•Easy to participate in

•Are supported by automation tools and automated response

•Have risks that are known and easily managed

•Stable over time

•Offer good value for customer efforts

customer-friendly demand response

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