# Presentation: 401640

## DR Rate and Program DesignRON-02 Phase 2 Proposal

**January 31, 2006**

## Presentation Overview

**Objectives and Process**
**Approach: Phase 1 Research Findings**
-  Develop Rate Design Alternatives
-  Screen 1: Technical Potential
-  Screen 2: Resource Value
-  Screen 3: Bill Impact and Free-riders
-  Screen 4: Customer Acceptance
**Phase 2 Proposal**
- Work Plan & Timeline
- Research Team
- Research Agenda

## Objectives and Process

## Objective of Phase 2 Research

- Provide DR designs ready to pilot in CA
- Research
- 	Develop efficient, implementable rate and program designs for demand response
- Consultation
- 	Provide a structured process to evaluate rate designs – ‘design charrette’

## Starting Point and Objective Function

**Emerging CA Mkt Structure:**
**LTRA, Day-Ahead, Balancing**
- Alternative Mkt Structure:
- Day-Ahead and/or RT Spot Price

**Maximize Net Benefits**
- Maximize Participation
- Design for Emergency
- Design for Operating Reserves
- Design for Planning Reserves
- Design for Bill Control
- Design for Risk Mitigation

**Efficient, Implementable Rate Designs**

**Screening Process**
**“****Design Charrette”**

**NO**

**YES**

**Revise Design**

**Starting Point – Market Design**

**Starting Point –**** ****Objective Function**

**DR Rate and Program Evaluation Process**

**Potential DR Rate and Program Designs**

## Screening Process

_**Screen 2:**__** **__**Resource Value**_
**Is it worth much? Value to system and participants?**

_**Screen 3:**__** **__**Bill Impact**_
**Given the value, what can customers save?**

_**Screen 4: Customer Acceptance**_
**Given the savings and design, will customers participate?**

**Candidate Rate Designs**

_**Screen 1: Technical Potential**_
**Is this a significant opportunity?**

**Research team is selected to provide experts at each step**
**E3, LBNL: Stakeholder process**
**HMG: Building science and loads**
**E3, LBNL, NA: Avoided costs and market design**
**E3, NA: Rate design**
**FSC: Customer research**

_**Address major stakeholder perspectives **_
**Utilities (Procurement, Resource planning, Marketing)**
**CPUC, CEC (Regulatory and Policy)**
**Customers (Acceptance, Complexity, Bill Impact)**
**ISO, WECC (Operations, and Reliability)**

_**Characteristics of the Screening Process**_
**Transparency**
**Consistency**
**Ease of Use**
**Use of publicly available data and models**
**Consultation with stakeholders**

**Screening Process**

## E3 Research Team

## Approach: Phase 1 Results

## 
Efficient Capacity Rationing 
Ideal Rate Designs
Rate Design Criteria
Illustrative List of Candidate Designs
Phase 1 Results
Evaluation Screens

- Efficient Capacity Rationing
- Ideal Rate Designs
- Rate Design Criteria
- Illustrative List of Candidate Designs
- Phase 1 Results
- Evaluation Screens

**Selecting & Evaluating Candidate Designs**

## Efficient Capacity Rationing

**Both price rationing and quantity rationing can be efficient**
- Price rationing
- Types: dynamic (RTP, CPP), static (TOU)
- References: Boiteux, 1949; Steiner, 1957; Joskow, 1976; Crew and Kleindorfer, 1976; Hogan, 1992
- mandatory RTP is the most theoretically efficient: P = SRMC in real time, but has practical limitations
- Quantity rationing
- Types: priority service (direct load control, interruptible, curtailable), demand subscription
- References: Chao and Wilson, 1987; Spulber, 1992; Woo, 1990
- can achieve 90% of efficiency of mandatory RTP.

## Ideal Rate Design

**Ideal Rate Design**

- With this market structure, an ideal rate design would have the following components:
- _monthly customer charge_* - to recover costs that vary with the number of customers on the system, such as metering, billing, and customer service*
- _distribution facilities charge_ per kW of design/contract demand* – to recover the costs of local distribution facilities*
- _location-specific, time varying firm energy charge_ – *to recover the time and location differentiated marginal costs of generation, transmission, and high-voltage distribution*

**Market Structure: ‘All-in’ Spot Market**

## Under this market structure, an ideal rate design would have the following components:
monthly customer charge - to recover costs that vary with the number of customers on the system, such as metering, billing, and customer service
distribution facilities charge per kW of design/contract demand – to recover the costs of local distribution facilities
generation capacity charge per kW of maximum demand - to recover the forward costs of generation capacity
location-specific, time varying energy charge – to recover the residual time and location differentiated marginal costs of generation, transmission, and high-voltage distribution

- Under this market structure, an ideal rate design would have the following components:
- _monthly customer charge_* - to recover costs that vary with the number of customers on the system, such as metering, billing, and customer service*
- _distribution facilities charge_ per kW of design/contract demand* – to recover the costs of local distribution facilities*
- _generation capacity charge_ per kW of maximum demand* - to recover the forward costs of generation capacity*
- _location-specific, time varying energy charge_ – *to recover the ***residual ***time and location differentiated marginal costs of generation, transmission, and high-voltage distribution*

**Market Structure: Forward Capacity Market**

**Ideal Rate Design**

## Market Structure and Rate Design

**What constitutes an “ideal rate design” depends on the market structure**
*‘**Consumer Reports’ style evaluation*

## Rate Design Criteria

- Economic efficiency is one of several rate design criteria (Bonbright, 1961)
- Efficient consumption
**Equitable apportionment of cost of service**
**Avoidance of undue discrimination **
**Meets utility revenue requirements**
**Year to year revenue stability for utility**
**Rate stability for customer**
**Simple to implement, easy to understand **
**Wide public acceptance**

## Illustrative Candidate DR Rates

## ‘Consumer Reports’ Style Evaluation

**Voluntary Demand Subscription Service with an enabling technology (PCT) was identified as best option for existing conditions**

**Summary of Phase 1 Results**

## Residential Demand Subscription 

- Customers subscribe to a firm service level with a monthly $/kW-mo charge.  Customers must not exceed this level during notice periods.
- Energy rates are reduced, but can maintain tier structure to minimize free rider bill impacts.
- Customers can reduce their bills by subscribing to a level below their maximum demand
- Subscription level can be enforced with a limiter device, or with a very high price for excess usage.
- If customers subscribe to their maximum demand, they need not alter their behavior.  For those customers that subscribe to lower levels of demand, however, some education and effort will be required for them to reduce their loads.

**Summary of Phase 1 Results**

## Screen 1: Technical Potential

## Example: Top Ten Contributors to System Peak

**Data from CEC Demand Forecast Office **

**Phase 1 end-uses selected**

**Technical potential screen**

## Example: non-time critical customer loads

**Example: non-time critical customer loads**

- In addition to the large end-use segments, there are smaller load segments with less time critical customer loads that have potential for demand response.
*Pool pumps*
*Electric water heat*
- ‘low-hanging’ fruit.

**Technical potential screen**

## Example: Residential PCTs

**More Utilities and forecast zones below**

**Approximately one third A/C saturation in PG&E territory**

**Savings per home are climate (forecast zone) dependent**

**Fraction of A/C on during peak is climate dependent**

**Technical potential screen**

## Technical potential screen

**Example: PCT DOE-2 results 2 – 6 pm**

- Analysis Repeated for Each of the Dispatched Days

**Period of curtailment**

**Average 1 kW savings**

**Rebound from PCT release **

## Technical potential screen

**Illustrative findings**

**List is illustrative, not exhaustive**

## Screen 2: Resource Value

## Resource Value Screen

- Offer to customers is driven by the value of the load reduction.
- Resource value screen evaluates whether the rate design provides significant value.

- Rate or Program Structure

- Value of Rate or Program

- Rate or Program Design

- Customer Bill Change       .

## Resource Value Screen

| Control | Utility
(Quantity) | Utility w/ customer over-ride | Customer
(Pricing) |
| --- | --- | --- | --- |
| Emergency
reserve  | K1D1VE
 | K4D4VE | K7D7VE |
| Operating reserve | K2D2VO | K5D5VO | K8D8VO |
| Planning reserve | K3D3VP | K6D6VP
 | K9D9VP |

**Components of Value**
**Vx = capacity value $/kW**
**Kx = enrolled kW**
**Dx = derating factor**
**(equivalent reliability)**

**Value Matrix**

## Uncertainty in customer-controlled DR

***WECC has stringent standards for counting load resources towards reserve requirements***
**WECC Nonspinning reserve currently requires that load be interruptible within 10 minutes.**

**WECC Minimum Operating Reliability Standards Standards BAL-STD-001-0-WECC — Real Power Balancing Control Performance**

**WRS2. Acceptable types of nonspinning reserve. **The nonspinning reserve obligations identified in WR1, WRS1.1, and WRS1.2, if any, can be met by use of the following:
**(a) load which can be interrupted within 10 minutes of notification**
- (b) interruptible exports
- (c) on-demand rights from other entities or Control Area/Balancing
- (d) spinning reserve in excess of requirements in WR1
- (e) off-line generation which qualifies as nonspinning reserve (see definition)

**Resource Value Screen**

## Example: Derating a PCT load reduction 

- DERATING FACTORS ARE MULTIPLIED TOGETHER
- OVERALL DERATING FACTOR  = 0.48

**Derating factors at each stage are in red**

## Net Social Welfare

**Net Social Welfare**

- Rates not based on market value result in some efficiency loss
- Voluntary rates allow preference discovery and preference matching
- *High transaction costs (e.g. technology) can lower welfare gains of mandatory rates

*****

**Resource Value Screen**

## Screen 3: Bill Impact and Free-Riders

## Bill Impact Screen

- Rate or Program Structure

- Value of Rate or Program

- Rate or Program Design

- Rate or program design affects customers bill savings.
- Bill impact screen evaluates whether the rate will provide the customer significant savings.

- Customer Bill Change       .

## Example of Demand Subscription 

- Demand subscription charge = $10.92/kW-mo.  (30% of total revenues).
- Other residential tier $/kWh rates reduced by 30%.
- Rate is revenue neutral based on average DS of 95% of max demand.
- Large users receive a relative lower % discount because the DS charge in this example is constant ($/kW-mo), while the average rate increases with size.

**Bill Impact Screen**

## Free Rider Potential

**TOU**

**DSS**

- Voluntary enrollment in customer control DR programs (pricing) is the most subject to free-riders.

**Free Rider Screen**

## Screen 4: Customer Acceptance

## Phase 1 research on customer acceptance (conducted by FSC):
Assessed factors affecting enrollment and response 
Calculated projected enrollment rates for illustrative designs

- Assessed factors affecting enrollment and response
- Calculated projected enrollment rates for illustrative designs

**Customer Acceptance Screen**

## Enrollment and Response Estimation Framework 

- Enrollment and Response Estimation Framework

**RATE/PROGRAM DESIGNS**

- Enrollment Rate

**OPT-OUT**

**Attractiveness of Design**
- Bill Savings, Volatility, Frequency of Events, Tech Package

**Attractiveness of  Available Alternatives**

**Participation Costs**
- Partial Outage, Transaction, Risk, and Equipment costs

- Enrollment Rate

**OPT-IN**

**Attractiveness of Design**
- Bill Savings, Volatility, Frequency of Events, Tech Package

**Participation Costs**
- Partial Outage, Transaction, Risk, and Equipment costs

**Attractiveness of  Available Alternatives**

**DEMAND RESPONSE IMPACT**

**Customer Factors**
- Awareness, Attitude, Intention, Behavior

**Customer Factors**
- Awareness, Attitude, Intention, Behavior

**Notes:**
Big Connection between enrollment rates,  responsiveness, and DR impacts
Emphasize the big lever of opt-in versus opt-out
Thereafter, same elements, different proces. 
Factors that determine the attractiveness of the design  and their relative importance are well studied. However, the results of those studies vary depending on what attributes are includes in the study, and are often not complete.
Participation Costs –  an incomplete component. 
Partial outage costs are the same for opt-in an opt-out
Transaction costs are different. In the case of opt-in, individuals incurr a the costs of informing themselves of the rate/program. 
Attractiveness of alternative designs matters in both cases. The more attractive, the larger the share that it will pick up
Customer Factors are very different for opt-in versus opt out. 
Awareness matters a lot in opt-in design, less so in opt-out designs
The factors that influence if  a customer has a positive attitude are different
In opt-in, intention to adopt matters. In opt-out, intention to switch out is what matters.
Effectiveness of targeting defines the technical potential. 
Did we enroll customers with the ability to reduce load?
Did we enroll customers who are price responsive?
Enabling Tech and the size and volatility of price signals affects their level of response (interconnected with decision to enroll)
Reliability of response, burn out and churn are affected by experience with the program and time. 
Overall demand response impacts vary over time and across implementation. The speed in which a program ramps up depends a lot on implementation

## Reliability of Estimation Methods

**Revealed Preference **
**Models**

- Enrollment
**Less Reliable Estimate**

- Enrollment
**More Reliable Estimate**

- Responsiveness
**More Reliable Estimate**

**Experience in **
**Similar Programs**

**Recruitment**
** ****into Pilots **

**Participant **
**Surveys**

- Responsiveness
**Less Reliable Estimate**

**Stated Preference**
** ****Models**

**Pilot/Field **
**Testing**

**Price **
**Elasticities**

**Experience **
**with the **
**Real Thing**

**Notes:**
We looked at the pro’s and cons of each method. The current research focuses a lot on the response (price and substitution elastic ties) and on the rate/program attributes customers prefer, they say little about whether customers will enroll or how they will react to default rates. 
Example of Stated Preferences Model (Momentum Study) 
Tells us a lot about the factors that affect customer preferences but doesn’t tell us much about the share of customers who will enroll in a program.
The value of the information depends a lot on the survey design
Enrollment rates are vastly different based on opt-in vs opt-out
Note how the market share varies little from rate to rate. 
Delve into the pro’s and cons of the method (if time allows). 
Example of data from Actual experience  - Industrial RTP
The confidence level we can have based on experience from similar programs depends on the degree of similarity of the program and the region
The variation is still rather large for both opt-in and opt-out programs – implementation matters
Enrollment is higher with default rates
The variation is much greater than implied by the momentum studies regardless of whether we use an opt-in or opt-out design 
(Optional Note: reports of enrollment rates vary widely. Our graph uses the results from the LBNL report RTP Pricing as Default or optional Service for C&I Customers (8/05). In contrast, the self-reported numbers in the Survey of Uitlity Experience with RTP(12/04) indicate a 16% market penetration)
Field Testing provides us the best information about enrollment rates, but so far they have mostly focused on responsiveness. 
The value of information from field tests depends on how closely it matches the real world. More constraints, weakens the results significantly (e.g. enrollment incentives)

## Steady State Enrollment Rates for Sample DR Rates/Programs

- Illustrative ‘Opt-in’ Enrollment Estimates

**Notes:**

Only included opt-in for
Simplicity
Little actual experience with opt-out programs
Use a few concrete examples
Note that numbers can be updated with better data
Point out that Georgia Power RTP was excluded because it is not revenue neutral.

Notes
It’s possible for someone to claim PCT and Switch numbers are low. In comparison, DLC numbers range from 5% to 28%, but usually include a variety of end-uses besides A/C. I found a Kansas City Power & Light presentation claiming that their market research showed 26% for PCT’s and 22% for switches (of course they didn’t provide details about the market research)
There are additional states with RTP pograms. Although we don’t have concrete data from them, we have the answer they provided in the Survey of RTP. Those were not included because we didn’t want to confound methods (confirmed vs. survey) and because, in some instances (e.g. Georgia Power) the market penetration numbers provided by the program manager were vastly different than the confirmed data. 

## Customer Acceptance Findings

- Targeting strategies, enabling technologies, and marketing have a _substantial_ effect on both enrollment and response rates
- Momentum’s enrollment estimates are based on customer preference modeling assuming 100% awareness.
- FSC’s lower estimates are based on actual program experience.  These estimates are uncertain but the ranges are reasonable.
*Phase 2 screen will build upon participation literature and experience and will be augmented by quantitative research. *

## Phase 2 Proposal

## Phase 2 Proposal Summary

- Deliverables:
- suite of prototype DR rate and program designs for California
- set of screening tools to evaluate any DR program design
- Process:
- consultative stakeholder process
- E3 takes lead in framing questions, conducting research, writing drafts

## Phase 2 General Approach 

- Engage stakeholders throughout process
- Consider wide spectrum of candidate designs
- Make screens flexible to allow for future evolution of market and regulation
- Make rate design consistent with DR value

- The success of Phase 2 should be measured
-  by implementation of DR designs
-  with broad stakeholder support

## Phase 2 Proposed Tasks

- Develop MOU
- Finalize Research Plan
- Develop Screening Tools and Designs
- Initial Screening of Candidate Programs
- Complete Screening Tools and Program Designs
- Final Screening of Prototype Programs
- Final Report

## Phase 2 Timeline