Potential Study: LDC Profiles Working Group Meeting Update - - PowerPoint PPT Presentation

Working Group Meeting Update

Achievable Potential Study: LDC Profiles

January 22, 2015

LDC Load Profile Development

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IESO Achievable Potential Analysis

LDC Load Profiles Development Tasks

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LDC Profile Review Tasks

Develop profiles for remaining ± 60 LDCs Finalize all profiles Completed Dec 21 – Jan 25 Review draft profiles with all LDCs:

• Follow up with LDCs to address questions, gaps and to

clarify items.

• Adjust with new data when applicable

Completed Webinar to discuss profiles Completed Review profiles with Working Group and obtain feedback Develop profiles for Working Group LDCs Completed Completed

IESO Achievable Potential Analysis

Interaction with LDCs

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LDCs profiles revised based on received comments / data 45 48 Total number of LDC Profiles 64 LDCs responded with comments or revised data Follow up with conference calls / meetings 75 LDCs profiles approved without revision 16 LDCs provided no comments 11

IESO Achievable Potential Analysis

Summary of Changes from Draft to Final Versions

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Global Changes

Added estimated energy load associated with common areas in multi-unit residential buildings to commercial sector Relatively Insignificant Impact Relatively Insignificant Impact Relatively Insignificant Impact Updated NAICS code 2131 mapping from “mining” to commercial “large office” and “small office” Commercial EUIs were revised with updated 2009 Commercial Building SCIEU data received directly from NRCan at end of November 2015 “Construction/Contractor” NAICS codes mapped to “other commercial buildings” Relatively Insignificant Impact

IESO Achievable Potential Analysis

Summary of Changes from Draft to Final Versions

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LDC Specific Changes

Relatively Insignificant to Significant Impact

• LDCs provided additional data
• LDC Profile was updated with new data

Profile Template

Added “Final Profile” tab with summary of the profile:

• Final 2014 profile by sector and subsector in terms of kWh and %
• Reference sources

IESO Achievable Potential Analysis

Development of LDC Profiles

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Next Steps Questions about next steps? Update LDC Profiles to final version Submit final version profiles to LDCs

IESO Achievable Potential Analysis

LDC Load Profiles

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Nexant Canada, Inc. TD Canada Trust Tower 161 Bay Street, 27th Floor M5J 2S1 Toronto Canada www.nexant.com

Working Group Meeting Update

Achievable Potential Study: Forecast Development

January 22, 2015

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Forecast Development

IESO Achievable Potential Analysis

Load Forecast Development

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Purpose of Load Forecast

Objective:

• Develop a disaggregated reference load forecast for each LDC:
• Annually from 2015 to 2020
• By sector and sub-sector
• By end-use

Key items taken into consideration:

• Standards and codes
• Persistance of savings
• Other influences

Context:

• LDC profile provides snapshot of 2014 LDC load
• Load forecast projects changes from 2015 to 2020

IESO Achievable Potential Analysis

Methodology: LDC Load Forecasts (2015 -2020)

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Gross Forecast Net Forecast Reference Forecast Disaggregated Reference Forecast

IESO Achievable Potential Analysis

Methodology: Gross Forecasts (2015 -2020)

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2014 OEB Energy Sales by Sector Gross Annual Energy Sales Growth Rates

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Gross Forecast

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2014 OEB energy sales by sector as reported in LDC Load Profiles, and adjusted for weather as appropriate. Gross sector annual energy load growth rates derived from IESO model Energy Sales by sector by year for each LDC

Net C&S Annual Savings

IESO Achievable Potential Analysis

Methodology: Net of Codes and Standards (C&S) Forecast (2015 -2020)

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Net sector annual energy load growth rates (includes impact

• f codes and standards)

derived from IESO analysis Energy Sales by sector by year for each LDC (inclusive of codes and standards) Net of C&S Forecast

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Gross Forecast

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Energy Sales by sector by year for each LDC

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IESO Achievable Potential Analysis

Methodology: Subtract Persistent Savings (Reference Case Forecast (2015 -2020))

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Persistent and influenced energy savings by year by LDC Persistence of OPA/IESO funded Program Savings and Other Influenced Savings Energy Sales by sector by year for each LDC (inclusive of codes and standards and net of persistent / influenced savings) Reference Forecast Energy Sales by sector by year for each LDC (inclusive of codes and standards) Net C&S Forecast

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IESO Achievable Potential Analysis

Methodology: LDC Disaggregated Reference Forecasts (2015 -2020)

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Energy Sales % by Subsector by End Use LDC Load Profile Calibrated end use and subsector values per year, by LDC Calibrate to Reference Case Forecast Compound annual energy growth rates by end use End Use Growth Rates

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Compound annual energy growth rates by subsector Subsector Growth Rates

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Energy sales by sector, by subsector, by end use, by year by LDC Disaggregated Reference Forecast

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IESO Achievable Potential Analysis

Example Draft Findings: LDC Reference Forecast

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Version

Version 1

LDC Name

LDC #1

IESO Zone

Bruce

Residential Commercial Industrial 2014 OEB Load (Weather Adj) 159,473,525 193,109,780 44,458,286 Annual Gross Growth Rates (%) Gross Forecast (kWh) Residential Commercial Industrial Res Com Ind 2015 163,460,363 194,017,858 47,189,554 2015 3% 0% 6% 2016 164,432,811 195,893,130 48,006,052 2016 1% 1% 2% 2017 165,925,140 196,914,529 49,479,397 2017 1% 1% 3% 2018 166,194,444 198,877,105 49,798,812 2018 0% 1% 1% 2019 167,082,678 199,406,951 49,978,169 2019 1% 0% 0% 2020 168,142,463 200,770,327 50,260,655 2020 1% 1% 1% Annual Net Growth Rates (%) Net Forecast (kWh) Residential Commercial Industrial Res Com Ind 2015 160,936,594 196,870,385 48,672,929 2015

• 2%

1% 3% 2016 160,165,921 193,999,733 46,695,366 2016

• 3%
• 1%
• 3%

2017 164,419,267 197,941,253 48,950,421 2017

• 1%

1%

• 1%

2018 165,924,703 200,859,241 50,120,288 2018 0% 1% 1% 2019 166,189,697 203,926,349 50,158,173 2019

• 1%

2% 0% 2020 167,075,956 202,143,024 49,976,573 2020

• 1%

1%

• 1%

Persistent/Influenced Savings (kWh) Reference Forecast (kWh) Residential Commercial Industrial Res Com Ind 2015 160,528,793 195,839,164 48,204,193 2015 407,801 1,031,220 468,737 2016 159,961,034 193,481,628 46,459,864 2016 204,887 518,105 235,502 2017 164,309,080 197,662,618 48,823,769 2017 110,187 278,635 126,652 2018 165,880,578 200,747,659 50,069,568 2018 44,126 111,582 50,719 2019 166,151,173 203,828,932 50,113,893 2019 38,524 97,417 44,281 2020 167,051,319 202,080,722 49,948,254 2020 24,637 62,301 28,319

Schedule and Next Steps

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IESO Achievable Potential Analysis

LDC Load Forecast Development

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Send final LDC Profiles and request info regarding significant loss of load. Next Steps Questions about load forecast development activities? LDCs provide data regarding significant load loss. Develop draft LDC load forecast.

Jan 25 Feb 5 Feb 5 Feb 19

Finalize LDC load profiles and forecast.

IESO Achievable Potential Analysis

LDC Load Forecast Development

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Nexant Canada, Inc. TD Canada Trust Tower 161 Bay Street, 27th Floor M5J 2S1 Toronto Canada www.nexant.com

Working Group Meeting Update

Achievable Potential Study: Archetype Programs

January 22, 2016

IESO Achievable Potential Analysis

Archetype Programs

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Objective:

• Define recommended program groupings (referred to as archetype programs) applicable to

Ontario, and to be used as the basis for the achievable potential modelling.

• Model at archetype program level to estimate achievable potential at LDC level.

Purpose of Archetype Programs Key element in potential analysis modelling:

• Archetype programs are applied to LDC load profiles to derive achievable potential at LDC

level.

Characteristics of Archetype Programs:

• Concept of archetype program.
• Definition of:
• Measures that are included
• Subsectors and end uses being addressed
• Delivery mechanism and supply chain
• Financial incentive
• Challenges and opportunities to consider
• Attributes: Marketing approach, customer experience, type of incentive
• Application of archetype program:
• Adoption curve and assumptions

IESO Achievable Potential Analysis

Archetype Programs

Overview of methodology to develop archetype programs

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Gap analysis per sub-sector and end-use Develop list and review existing and proposed Ontario programs Jurisdictional research of North American programs Performance of existing Ontario programs Research characteristics of success Archetype Programs

IESO Achievable Potential Analysis

Draft Residential Archetype Programs

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Consumer

Archetype Programs

Systems and Equipment Audit and Direct Install Whole-Home

• Educate customers.
• Install highly cost-effective

measures.

• Direct to other programs.
• Archetype addresses need for

consumer self-installed measures.

• Archetype is contractor-driven.
• Addressing need for installing

measures that require outside contractors to install.

• Implement shell/envelope

measures.

• Energy efficiency upgrades that

are not “plug and play.”

Description

• Residential direct install

(focus on settings, peripheral and non-shell / envelope measures)

Example Programs

• Coupon program
• HVAC program
• Appliance retirement
• Assessment (may include

blower door test), recommendation and installation of shell / envelope measures

IESO Achievable Potential Analysis

Draft Residential Archetype Programs

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Behavioural Low Income Aboriginal New Construction

Archetype Programs

• Drives behavioral changes in

conservation.

Description

• Benchmark reporting with

recommendations

Example Programs

• Approach centralized

management and existing resources for low income community to support energy conservation

• Low income home

assistance program

• Improve home electricity

efficiency for aboriginal communities.

• Aboriginal program
• Target highly cost-effective

measures in new construction.

• May offer additional tier for

green building market.

• Residential new contruction

prorgam

IESO Achievable Potential Analysis

Draft Commercial and Industrial Archetype Programs

Archetype Programs

Retrofit Audit and Energy Partners

• Identify operational and control

measures.

• Direct to other programs.
• Engage in behavioral, strategic

energy management.

• Addresses need to overcome

cost barriers and increase efficiency of equipment.

Description

• PSUI program
• Retro-comissioning

Example Programs

• Retrofit program

IESO Achievable Potential Analysis

Draft Commercial and Industrial Archetype Programs

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Small Business

Archetype Programs

New Construction

• Archetype is direct install

approach to implement fast, cost-effective CDM measures where energy management is not a major cost.

• Target businesses with <50 kW

average annual demand.

• Supply-chain program that

engages design and construction upstream

Description Example Programs

• Small business lighting

(expand to include other end uses)

• High performance new

construction

IESO Achievable Potential Analysis

Example Archetype Program Description: Retrofit

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Current Status 2014 Evaluation Findings Target Sectors Target End-uses Measures Included Marketing Strategy Customer Experience Incentive Type Incentive Ammount Best Practices and Potential Enhancements Estimated Adoption Review Profile Attributes Application

IESO Achievable Potential Analysis

Example Archetype Program Description: Retrofit

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Current Status

• Retrofit program with three tracks:
• Prescriptive: Set rebates based on number of equipment units

installed per building.

• Engineered: Pre-qualified efficiency measures, but applicants

have the opportunity to adjust estimated savings on the basis of their facility’s characteristics.

• Custom: Energy efficiency projects that are specific to a facility

and which, due to site characteristics, have savings and costs that differ from prescriptive or engineered measures

Review

IESO Achievable Potential Analysis

Example Archetype Program Description: Retrofit

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2014 Evaluation Findings

• Program share of savings has slightly grown for the prescriptive and

engineered track.

• 94% of 2014 energy savings for prescriptive and engineering tracks

were lighting projects.

• 77% of 2014 energy savings for the custom track was non-lighting.
• The number of projects increased yet the average net energy

savings per project decreased.

Review

IESO Achievable Potential Analysis

Example Archetype Program Description: Retrofit

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Target Sectors Target End-uses

• All commercial and industrial sub-sectors.
• All commercial and industrial end-uses.

Measures Included

• All commercial and industrial measures.

Profile

IESO Achievable Potential Analysis

Example Archetype Program Description: Retrofit

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Marketing Strategy

• Joint-marketing / co-branding
• Trade allies and channel partners

Customer Experience

• Technical assistance.
• Customers receive advice / recommendations for measures

that can save them energy.

Incentive Type

• Customer rebate
• Focus on barriers related to the up-front cost of energy

efficiency measures.

Attributes

IESO Achievable Potential Analysis

Example Archetype Program Description: Retrofit

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Incentive Ammount Best Practices and Potential Enhancements

• Adoption curve:
• Consider non-economic incentive influences and

attributes.

• Impact of economic incentives.

Estimated Adoption

• Maximum incentive amount allowable for positive benefit-cost

ratio (applies only to cash incentives offered directly to customers)

• Compares incremental savings to incremental cost.
• Summary of best practices and potential enhancements.
• Examples from other jurisdictions.
• Performance of similar programs in other jurisdictions.

Application

IESO Achievable Potential Analysis

Next Steps

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Tasks Questions about next steps?

Develop archetype program descriptions Review and finalize archetype program descriptions with sub- Working Group and IESO Review draft list of archetype programs Feb 5 Mar 4 Feb 19

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Questions

Nexant Canada, Inc. TD Canada Trust Tower 161 Bay Street, 27th Floor M5J 2S1 Toronto Canada www.nexant.com

Working Group Meeting Update

Achievable Potential Study: Adoption Curves

January 22, 2016

IESO Achievable Potential Analysis

Adoption Curves

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Purpose of Adoption Curves Objective:

• Develop adoption curves to estimate particiaption in each archetype program

from 2015 to 2020.

• The estimated participation will be used in the model to derive the estimated

achievable potential savings for each archetype program.

Key items taken into consideration:

• Historic program participation
• Transition from previous framework to CFF
• Design and launch period for new/enhanced programs
• Non-incentive influences
• Incentive level

Adoption curves:

• Estimate of achievable annual participation in archetype programs from

2015 to 2020.

Adoption Curves

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IESO Achievable Potential Analysis

Adoption Curves

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• Adoption curves represent the percentage of participation, of eligible customers

in a program.

• The adoption curves typically includes:
• A program launch period
• An accelerated increase in participation
• A decreased in accelerated participation and plateau as maximum

participation is approached

• Programs that started in Ontario during the previous framework will have moved

passed the launch period and will be on a slope of increased participation.

• Program enhancements aim to accelerate the rate of participation.
• New programs to be launched during the Conservation First Framework will

start at the beginning of the launch period.

IESO Achievable Potential Analysis

Status Quo Adoption Curve: Program Design Started in 2010

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100% 80% 60% 40% 20% 2010 2035 2030 2025 2020 2015 2040 Participation of Eligible Customers Year

IESO Achievable Potential Analysis

Status Quo Adoption Curve: Program Status in 2015

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100% 80% 60% 40% 20% 2010 2035 2030 2025 2020 2015 2040 100% 80% 60% 40% 20% Participation of Eligible Customers Year

IESO Achievable Potential Analysis

Enhanced Program Adoption Curve

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2035 2030 2025 2020 2015 2040 100% 80% 60% 40% 20% Participation of Eligible Customers Year

IESO Achievable Potential Analysis

New Program Adoption Curve

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2035 2030 2025 2020 2015 2040 100% 80% 60% 40% 20% Participation of Eligible Customers Year

IESO Achievable Potential Analysis

Modelling Adoption Curves Using Bass Diffusion Model

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 5 10 15 20 Majority Adopters Late Adopters Innovators Time

• From marketing/product

development

• Accepted theory for

product diffusion

• Evolution from introduction

to saturation

• Apply same principle to

energy efficiency and program archetypes

IESO Achievable Potential Analysis

Theory: Bass Diffusion Model

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 5 10 15 20 Time

Variable: Market Share (S) Variable: Time (t)

IESO Achievable Potential Analysis

Theory: Bass Diffusion Model

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Parameters: p = coefficient of innovation

• It’s an external effect
• An external effect where program archetypes can influence adoption

q = coefficient of imitation

• It’s an internal effect
• It is considered as an inherent property of the market and technology

m = maximum market share

IESO Achievable Potential Analysis

Derive Status Quo Adoption Curve

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100% 80% 60% 40% 20% 2010 2035 2030 2025 2020 2015 2040 Participation of Eligible Customers Year m = Maximum Market Share Historic Program Performance

IESO Achievable Potential Analysis

Status Quo Adoption Curve: Program Status in 2015

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100% 80% 60% 40% 20% 2010 2035 2030 2025 2020 2015 2040 100% 80% 60% 40% 20% Participation of Eligible Customers Year

IESO Achievable Potential Analysis

Enhanced Program Adoption Curve: Non-Incentive Influences

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2035 2030 2025 2020 2015 2040 100% 80% 60% 40% 20% Participation of Eligible Customers Year Change in Parameter: P (Non-Incentive Influences)

IESO Achievable Potential Analysis

Enhanced Program Adoption Curve: Economic Incentive

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2035 2030 2025 2020 2015 2040 100% 80% 60% 40% 20% Participation of Eligible Customers Year Change in Economic Incentive (Price Elasticity)

IESO Achievable Potential Analysis

Development of Adoption Curves

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Impact of economic incentives Status quo adoption curve Impact of external effects due to program (enhancement due to non-incentive influences) Bass Diffusion Model Assess impact of attributes Assess impact of price elasticity Property Methodology

Non-Incentive Influences: Archetype Program Attributes

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IESO Achievable Potential Analysis

Defining Influences of Program Participation

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Examples:

• Should I pay incentives to trade allies or directly to customers?
• Should I market the program to a specific target group of customers, or should I do a

mass marketing campaign? Program designers make tradeoffs when developing programs.

• Tradeoffs must be negotiated to achieve multiple, potentially conflicting objectives:

customer satisfaction, cost-effectiveness, energy savings targets

IESO Achievable Potential Analysis

Defining Influences of Program Participation

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Examples:

• Customers may not participate if they aren’t aware of the program (marketing).
• Even with equal incentive amounts, commercial customers may be less likely to

participate than residential customers because doing so takes time away from their business (sector). Program designers make tradeoffs when developing programs.

• Some program design attributes can be substitutes or complements: award-winning

marketing campaigns may drive demand and offset the incentive amount required to induce participation The incentive amount is not the only reason people participate.

IESO Achievable Potential Analysis

Defining Influences of Program Participation

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Example:

• Increasing spending on promotional materials may allow us to reach more people and

increase participation in a program. Program designers make tradeoffs when developing programs.

• Programs have a set of attributes that influence program adoption, and they apply to

all energy efficiency programs. The incentive amount is not the only reason people participate. Program design attributes affect participation, and they are independent of what’s offered by the program.

IESO Achievable Potential Analysis

Archetype Program Non-Incentive Attributes

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Marketing approach Approach to make customers aware of utility programs and encouraging energy efficiency and associated, utility- sponsored programs. Options for a marketing strategy have a range of influence and cost. Type of incentive Customer experience Addresses how customers acquire energy savings. The ease

• f participation, or mechanism of participation, can influence

customer adoption of energy efficiency. This attribute addresses barriers to energy efficiency, such as lack of knowledge about energy efficiency benefits, low availability of energy efficient products, or capital expenses associated with energy efficiency equipment.

Category Description

IESO Achievable Potential Analysis

Archetype Program: Non-Incentive Attributes

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Marketing approach

• Target customer segment
• Mass marketing
• Joint marketing/co-branding

Type of incentive Customer experience

• Customer rebate
• Sales incentive (rewards channel partners or trade allies)
• Upstream incentive / mark-downs
• Technical assistance
• Direct install
• Self-directed
• Behaviour

Category Type

IESO Achievable Potential Analysis

Archetype Program: Non-Incentive Attributes

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Target customer segment Analysis to identify customer groups or customer profiles but generates tailored messages. The resulting marketing materials are more likely to influence customers, but require additional effort to develop and align with customer preferences.

Marketing Approach

Joint marketing / co- branding Mass marketing This marketing strategy is designed to cast a wide net and reach the largest number of customers. Since all customers receive the same marketing messages, the message may not apply to some

• customers. The investment in this strategy is concentrated on

developing the product message, and no additional costs are incurred to target specific customers. This marketing approach is designed to enhance existing efforts by market channel allies. For example, a utility seal of approval for contractors, a preferred contractor database, or enhanced in-store displays for retail partners. This approach is designed to encourage customers “already in the market” to adopt more energy efficient measures. The additional costs of this approach may include enforcement of brand standards.

IESO Achievable Potential Analysis

Archetype Program: Non-Incentive Attributes

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Technical assistance Customers receive advice/recommendations for measures that can save them energy. This may include design assistance for major renovations or new construction, e.g. recommendations for the type of HVAC configuration that saves the most energy, given a home’s construction and occupants’ habits as determined by channel partners.

Customer Experience

Behaviour Direct install This approach is designed to minimize customer involvement and routine disruption while providing clear benefits to the customer. A behavioral experience educates customers about how their energy consumption compares to peer groups. It also educates customers about their existing energy consumption in an effort to help them identify alternative behaviors or investments that can save energy. Self-directed The customer identifies energy efficiency opportunities and programs that are most beneficial to them, without providing utility interventions beyond marketing for program awareness or customer rebates for purchase of energy efficiency equipment.

IESO Achievable Potential Analysis

Archetype Program: Non-Incentive Attributes

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Customer rebate Focus on barriers related to the up-front cost of energy efficiency

• measures. Utility-sponsored programs can encourage more

program participation by lowering the incremental costs of energy efficiency measures included in the program, relative to baseline efficiency measures.

Type of Incentive

Upstream incentive / mark-downs Sales incentive Incentives are designed to rewards channel partners or trade allies for sales of energy efficiency measures. In the case of consumer- facing measures, this may include incentives to salespeople that work in retail outlets, or it may include spiffs for sales of higher- efficiency measures typically installed by contractors. Sales incentives are designed to overcome barriers related to lack of knowledge about energy efficiency benefits, or lack of familiarity with new products. Incentives are designed to reduce point-of-sale costs, or encourage distributors and retailers to increase the share of energy efficiency product offered. This strategy is designed to

• vercome barriers associated with lack of product availability.

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Quantification of Attributes

IESO Achievable Potential Analysis

Type of Customers and Type of Projects

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Project Type

• Simple: Low cost and

relatively easy to install.

• Complex: Medium to high

cost and more complicated to install. Customer Type

• Residential
• Commercial
• Industrial

Simple Project Residential Complex Project Simple Project Commecial Complex Project Simple Project Industrial Complex Project

IESO Achievable Potential Analysis

Choice Model with Statistical Analysis: Residential Sector Example

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To quantify the influence of an attribute a choice model with statistical analysis is used

Simple Project Program Option A

a) Target customer segment b) Mass marketing c) Joint marketing/co-branding a) Technical assistance b) Direct install c) Self-directed d) Behaviour a) Customer rebate b) Sales incentive c) Upstream incentive

Marketing Approach Customer Experience Type of Incentive b c a b c a Program Option B

Selection: A more than B A slightly more than B Equal B slightly more than A B more than A Question: Which program represents the best

• pportunity for utility-

sponsored programs to influence customers’ energy efficiency decisions?

IESO Achievable Potential Analysis

Choice Model with Statistical Analysis: Residential Sector Example

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Simple Project Program Option C

a) Target customer segment b) Mass marketing c) Joint marketing/co-branding a) Technical assistance b) Direct install c) Self-directed d) Behaviour a) Customer rebate b) Sales incentive c) Upstream incentive

Marketing Approach Customer Experience Type of Incentive a c a b b b Program Option D

Selection: C more than D C slightly more than D Equal D slightly more than C D more than C Question: Which program represents the best

• pportunity for utility-

sponsored programs to influence customers’ energy efficiency decisions?

IESO Achievable Potential Analysis

Choice of Attributes: Example Residential Customers

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• 10 to 12 Choice selection between two alternative program options.
• Statistically, the Multinomial Logit (MNL) model provides a conditional probability

distribution for uncertainty around program design choices, given a set of alternative designs.

• MNL Model estimates choice as a function of the attributes and provides the

values to define p (non-incentive effect) in the Bass Diffusion Model equation.

Non-incentive effects for: Residential Archetype Programs addressing Simple Projects

Derive non-incentive effects variable: p by sector and project type (6 in total)

IESO Achievable Potential Analysis

Choice Model and Adoption Curves

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• Residential customers

 Simple Projects  Complex Projects

• Commercial customers

 Simple Projects  Complex Projects

• Industrial customers

 Simple Projects  Complex Projects Choice Selection by Sector and Project Type 1 Statistical Analysis 2 Define Archetype Programs by Sectors and Project Types 3 Develop Status Quo Adoption Curves for Each Archetype Program 4 Apply Non-incentive Effects Variable p to Each Archetype Program Status Quo Adoption Curve 5

IESO Achievable Potential Analysis

Implications

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• A customer’s response to non-incentive influences is determined by sector and

project type. For example:

• Residential customers will respond similar to non-incentive influences when

they have to install a simple project, or

• Industrial customers will respond similar to non-incentive influences when

they have to install complex projects.

• The analysis defines the non-incentive attributes with the most influence for each

archetype program. The success of the attribute depends on implementing the best practices associated with the attribute. For example:

• For an archetype program with sales incentive identified as the customer

experience attribute with the highest influence, achieving the estimated potential will depend on successfully working with channel partners and trade ally networks.

Economic Incentives: Price Elasticity

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IESO Achievable Potential Analysis

Economic Incentives for Archetype Programs

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Incentives and Price Elasticity

Demonstrate impact Research

• Price elasticity estimated based on EIA-861 data from 2012 –

2014.

• Consists of utility data on incentive spending, non-incentive

program spending, and DSM program savings achieved in each year, by economic sector.

• Assess resulting adoption curves with sector specific elasticity

value and change to incentive value.

• Select final change in incentives based on the resulting savings

versus the impact on cost and budget. Status quo

• Price elasticity value per sector.
• Status quo incentive per program is weighted-average of

existing incentives for measures included in current programs (weight based on relative program participation by measure) % change in participation % change in incentive Price elasticity

IESO Achievable Potential Analysis

Enhanced Program Adoption Curve: Economic Incentive

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2035 2030 2025 2020 2015 2040 100% 80% 60% 40% 20% Participation of Eligible Customers Year Change in Economic Incentive (Price Elasticity) Example: = 0.45 Change in incentive = 10% Result: Change in participation = 4.5% Change in Parameter: P (Non-Incentive Influences) Status Quo (Reference Case Forecast)

Next Steps

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IESO Achievable Potential Analysis

Work Plan and Next Steps: Assess Non-incentive Influences

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Tasks Questions about next steps?

Develop survey instrument and presentation material Survey responses forward to Nexant for analysis Distribute survey to:

• LDCs in Sub-WG and Working Group (approximately12)
• IESO program experts (5-7)
• Expert panel (3)
• Nexant program experts (8-10)

Webinar to present and explain the survey Survey completion within 5 working days Review methodology with IESO and expert panel Completed Feb 8 Feb 5 Feb 8 Feb 12 Feb 12

IESO Achievable Potential Analysis

Work Plan and Next Steps: Adoption Curves Development

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Tasks Questions about next steps?

Complete research and analysis of price elasticity Review and finalize adoption curves with sub-Working Group and IESO Complete analysis of non-incentive influences Feb 19 Mar 4 Feb 19 Develop draft adoption curves Feb 26

77 <Insert Footer>

Questions

Nexant Canada, Inc. TD Canada Trust Tower 161 Bay Street, 27th Floor M5J 2S1 Toronto Canada www.nexant.com