pricing models and mechanisms for the promotion of demand … · 2013-01-30 · research report...

RESEARCH REPORT VTT-R-06388-09

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Pricing models and mechanisms forthe promotion of demand sideintegrationAuthors: Corentin Evens, Seppo Kärkkäinen

Confidentiality: Restricted


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Report’s titlePricing models and mechanisms for the promotion of demand side integration

Customer, contact person, address Order referenceTEKESJarkko PiirtoPL 69, 00101 Helsinki

1573/31/08

40298/08

Project name Project number/Short nameENETE 31305

Author(s) PagesCorentin Evens, Seppo Kärkkäinen 58/

Keywords Report identification codeDemand Side Integration, DSI, Demand Response VTT-R-06388-09

SummaryThis report is part of the first stage of the ENETE project. It intends to give descriptions of thedifferent pricing mechanisms that are currently in use or that have been tried in order to en-courage Demand Side Integration (DSI) into the different electricity markets. It presents onone hand price based options where the consumers receive different prices at different timesand on the other hand incentive based options where the consumers make some of their loadavailable for various services and are rewarded when their availability is used.

It also presents examples of various tariffs found around the world and ends with the opportu-nities and requirements for the different actors in the electricity business.

Confidentiality Restricted

ESPOO 08.09.2009

Written by

Corentin Evens,

Research scientist

Reviewed by

Hannu Pihala

Accepted by

Seppo Hänninen

VTT’s contact address

Corentin Evens, Tekniikantie 2, 02044 VTT

Distribution (customer and VTT)ENETE consortium

The use of the name of the VTT Technical Research Centre of Finland (VTT) in advertising or publication in part ofthis report is only permissible with written authorisation from the VTT Technical Research Centre of Finland.


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Preface

This report has been written by C. Evens and S. Kärkkäinen for VTT in the context of theENETE project, funded for the biggest part by TEKES. It comes in the following of workdone in the ADDRESS project for the EU Commission.

The purpose of the work is to identify and study the different options used to integrate theelectricity demand side into the markets and into network management. Indeed, the risingprices for energy, along with environmental concerns and policies call for a better use of theexisting infrastructures.

This report presents a history of demand side participation terminology followed by a presen-tation of the identified tariff systems. a review of some existing programs and, finally, conclu-sions regarding demand side integration for the different involved actors.

Espoo, 10.2.2010

Corentin Evens and Seppo Kärkkäinen


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Contents

Preface ........................................................................................................................2

1 Introduction.............................................................................................................6

2 Introduction to demand response ...........................................................................62.1 Background.....................................................................................................6

2.2 From DSM to DSI in restructured market ........................................................7

3 Characterisation of DSI types.................................................................................83.1 Price based...................................................................................................10

3.1.1 Time-of-use........................................................................................10

3.1.2 Time-of-use tariffs on demand charges .............................................10

3.1.3 Real-time pricing ................................................................................11

3.1.4 Critical peak pricing............................................................................13

3.1.5 Summary of the price based DSI .......................................................14

3.2 Incentive based.............................................................................................15

3.2.1 Direct load control ..............................................................................15

3.2.2 Interruptible/curtailable services.........................................................15

3.2.3 Demand bidding / Buyback programs ................................................17

3.2.4 Emergency demand response programs ...........................................18

3.2.5 Balancing market programs with upfront capacity payment ...............19

3.2.6 Ancillary services market programs ...................................................20

3.3 Demand aggregation ....................................................................................21

3.4 Technologies to support DSI.........................................................................22

4 Description of selected past and on-going projects ..............................................234.1 ENEL experience with ToU tariffs. ................................................................23


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4.1.1 Night Tariff (available from February 1st 2005)..................................23

4.1.2 Week-end tariff (available from February 1st 2005). ..........................23

4.1.3 DUE tariff (available from January 1st 2005) .....................................23

4.1.4 OTTOSETTE Tariff ............................................................................24

4.2 EDF (France) experience with DSI ...............................................................26

4.2.1 Heures pleines / Heures creuses (peak/off-peak hours) (Time of Use)26

4.2.2 EJP (Critical Peak pricing – Fixed-period CPP) .................................26

4.2.3 Tempo (Critical Peak pricing – Fixed-period CPP).............................27

4.3 RTE (France) - "Diffuse adjustment" on the “Balancing mechanism”............28

4.4 SINTEF (Norway) DSI pilots .........................................................................29

4.4.1 Time of Day (ToD) tariffs....................................................................29

4.4.2 Fixed Price With Return option (RTP)................................................30

4.4.3 Remotely controlled load shifting (DLC).............................................30

4.5 Austin Energy – DSM program (DLC)...........................................................31

4.6 Exelon (Commonwealth Edison) and The Community Energy Cooperative(RTP) ............................................................................................................33

4.7 California Statewide Pricing Pilot (ToU, CPP & DLC) ...................................35

4.8 Demand Turndown Trials (Balancing market participation)...........................36

4.9 Ontario Energy Board smart price pilot (ToU & CPP) ...................................37

4.10 ISO-New England demand response programs............................................45

4.10.1Real-Time Demand Response program (Capacity market) ...............45

4.10.2Real-Time Price Response Program (CPP).......................................46

4.10.3Day-Ahead Load Response Program (Demand side bidding) ...........47

4.11 PJM Interconnection demand response programs........................................47

4.11.1Economic Load Response program (RTP) ........................................47

4.11.2Emergency Load Response program (Capacity market) ...................48


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4.11.3Ancillary services market ...................................................................48

4.12 ERCOT Demand response programs (Balancing and ancillary services).....48

4.13 The Olympic Peninsula project (Aggregator, RTP, DLC) ..............................49

4.14 US survey of utility experience with RTP ......................................................52

4.15 US survey of household response to dynamic pricing of electricity...............54

5 Conclusions..........................................................................................................55

6 References ...........................................................................................................57


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1 Introduction

This report intends to give descriptions of the different pricing mechanisms that are currentlyin use or that have been tried in order to encourage Demand Side Integration (DSI) into thedifferent electricity markets.

The report presents first a historical context for DSI and descriptions of the different types ofDSI program types, what they are and the way they are most often designed. It also tries tostress out the issues and problems raised in applying those programs.

The following describes relatively shortly several pilots, programs or the work of other sur-veys involving DSI. These pilots and programs involve mainly regulated participants (DSOs,TSOs or US utilities) and we have extended their conclusions to some deregulated partici-pants. The reason for this is that deregulated actors do not give out publicly the results of theirfield tests or of their program for the sake of competitiveness.

This reports ends with a review of the observed involved actors and their possibilities, needsand limitations regarding DSI.

2 Introduction to demand response

2.1 BackgroundThe electrical infrastructure installed to meet the required demand must be adequate withinthe generation, transmission and distribution systems to supply power in a safe, secure andeconomical manner. In many regions around the world, the electric power system is becomingover-stressed. Peak demand is approaching generation system capacity, boosting electricitycosts and increasing the risk of supply shortages in some regions of North America, Europe,and Australia.

Simultaneously there is a significant increase of renewable intermittent generation due to theneed to curb carbon emissions. Several countries, mainly in Europe, are achieving or willachieve in the near future large penetration of intermittent generation such as wind and solarpower. New operation practices are required to maintain the system security while keeping anacceptable economic performance of the power system. Such systems will require a differentapproach to system flexibility and control. The demand side will probably be integrated intosystem operation as a source of flexibility to support the system operator in dealing with in-termittent generation and keeping the system in balance.

While in the past the terminology dealing with demand side activity was referred to as De-mand Side Management (DSM) and Demand Response (DR), the newer term Demand SideIntegration (DSI) reflects the new approaches to integrate demand flexibility and controllabil-ity into the power systems operations.


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Restructured Industry(DSI)

Traditional Industry(DSM)

Peak Clipping

Valley Filling

Load Shifting

FlexibleLoad Shape

StrategicConservation

StrategicLoad Growth

Load Management

Peak Clipping

Valley Filling

Load Shifting

Dynamic EnergyManagement

EnergyEfficiency


Demand Response

Restructured Industry(DSI)

Traditional Industry(DSM)

Peak Clipping

Valley Filling

Load Shifting

FlexibleLoad Shape

StrategicConservation


Load Management

Peak Clipping

Valley Filling

Load Shifting

Dynamic EnergyManagement

EnergyEfficiency


Demand Response

Figure 1. Targets of demand side integration [5]

2.2 From DSM to DSI in restructured marketPublications on DSM extend back to the 1970’s. A compilation of early technical articles areorganized in [1] and textbooks on DSM concepts and methods have been published in [2] and[3].

As discussed in [4] the applicability of DSM terminology has been in question with the ad-vent of competitive electricity markets. Many end-use customers are no longer under an envi-ronment of centralized management driven by utilities. The concept of customer-driven re-sponse or demand response is more compatible with competitive market principles than cen-tralized utility-driven load management. In restructured regions, the demand-side is generallycomprised of energy retailers (i.e., utilities, energy service providers, and other load servingentities) participating in wholesale electricity markets on behalf of end-use customers. To-gether energy retailers and end-use customers may provide valuable demand-side services byutilizing demand-side resources to support grid or market needs.

Based on observations from interactions with diverse organizations regionally and interna-tionally, the authors in [5] note several terminology shifts that have occurred. Among them,Load Management is increasingly being replaced by the term Demand Response. Energy Ef-ficiency is commonly being used to refer to Strategic Conservation. Also Flexible Load Shapeis being replaced by the concept of Dynamic Energy Management, which is enabled throughdynamic systems.


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Despite these terminology shifts, load shaping concepts originally devised in vertically inte-grated utility environments are still applicable in restructured environments. Figure 1 associ-ates load shape objectives in traditional industries with those in restructured industries.

Demand response is related to load shaping and refers to a set of strategies which can be usedin competitive electricity markets to increase the participation of the demand-side or end-usecustomers, in setting prices and clearing the market.

- When customers are exposed in some way to varying electricity prices, they may respondby shifting the time of day at which they demand power to an off-peak period, and/or byreducing their total or peak demand through energy efficiency measures or self generation.They may also have the possibility to sell back their loads to the market.

- Alternatively, they may choose not to respond at all and pay the market price for electric-ity instead.

To the extent that they do respond, the profile of demand in the market will be smoothed,which, in turn, feeds back into prices. This action will clip the peaks significantly and, to alesser degree, will lower average prices. The net effect of the demand response is to ease sys-tem constraints and to generate security and economic benefits for the market as a whole.

3 Characterisation of DSI types

There are several alternative or complementary ways to affect customer behaviour in a com-petitive electricity market.

Tariffs and pricing are the main factors in a competitive market when trying to affect custom-ers. In an unbundled electricity market, the customers are affected by two types of tariffs andpricing, namely network and retail tariffs. Both of them can include components promotingdemand side integration.

Regulated network tariffs can include time-of-use (ToU) tariffs to achieve load levelling. Spe-cial demand charges are used to decrease the maximum load and special contracts like ancil-lary service contracts, where, for example, load control by the network operator is allowed inspecial situations. From past experience, it should be noted that the regulator may not acceptvarying tariffs on network charges (see the Norwegian example chapter 4.4.1). The reasonstated is that it could interfere with the normal market mechanisms.

Competitive or partly regulated retail pricing can include components similar to the networktariffs above. In addition, other types of price based varying tariffs, such as "real-time pric-ing", have been developed to reflect the costs improve the transparency. Such tariffs are usu-ally spot price based so that hourly prices are known one day before. These are discussed inmore details below.


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Demand response can be classified according to the way load changes are triggered [6]:

Price-based demand response refers to changes in usage by customers in response tochanges in the prices they pay: it includes real-time pricing, critical-peak pricing, andtime-of-use rates. If the price differentials between hours or time periods are signifi-cant, customers can respond to the price structure with significant changes in energyuse, reducing their electricity bills if they adjust the timing of their electricity usage totake advantage of lower-priced periods and/or avoid consuming when prices arehigher. Customers’ load use modifications are entirely voluntary.

Incentive-based demand response refers to programs proposed by utilities, loadserving entities, or a regional grid operator. These programs give customers load re-duction incentives that are separate from, or additional to, their retail electricity rate,which may be fixed (based on average costs) or time-varying. The load reductions areneeded and requested either when the grid operator thinks reliability conditions arecompromised or when prices are high. Most demand response programs specify amethod for establishing customers’ baseline energy consumption level. Hence, ob-servers can measure and verify the magnitude of their load response. Some demandresponse programs penalize customers that enrol but fail to respond or fulfil their con-tractual commitments when events are declared.

These two types, as well as the subtypes defined in each of them, are not mutually exclusive.Consumers can very well and often do, enrol at the same time in price and incentive basedoptions. There are however regularly limitations as the same power capacity can not be of-fered in different programs. Obtaining benefits from selling the same power reduction to dif-ferent programs at the same time is generally not allowed.

In [7], other definitions are given stating that markets for demand response in liberalised sys-tems can operate in two ways:

Market led: the customer responds directly to market pricing signal, causing behav-ioural or consumption changes. Prices are set by market mechanisms (interaction be-tween wholesale and retail markets).

System led: the system operator, or a service aggregator or agent, signals the demand-side customers that there is a requirement for load reduction or shifting. These are of-ten reliability-based programs where the prices are set by market or system operator(wholesale markets).

In addition to these programs, there are other possibilities to influence the energy use at con-sumers' premises. Information to customers can affect their behaviour. One example is TV orradio information on a critical situation in the national electricity balance, which can lead to areduction in consumption. Another way is to give feedback to customers based on his meas-ured consumption and special analysis/comparison to other similar customers, including somehints on energy conservation. This can be part of bills, web-based feedback or by direct indi-cation on meters or local devices.


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3.1 Price based

3.1.1 Time-of-use

Time-of-use (ToU) tariffs are a price based option to activate demand response. The conceptis that consumers pay a different price for different blocks of time. Most of them present dif-ferent prices for some periods of the day, such as for example, night and day or peak and off-peak tariffs. ToU rates reflect the average costs of generation and delivery of power duringthose time periods.

ToU tariff is the DSI solution that requires the least control and the lowest installation costs.Its main target is to obtain load shifting from high demand to low demand or from peak to off-peak periods. The effect observed is indeed a reduction in the load at high price periods andan increase at low price periods.

As a result of ToU tariffs, we can observe a consumption peak in the beginning of the less ex-pensive periods due to most of the connected appliances being started or tuned up at the sametime. To dampen the disturbance, it is usually seen that the tariff periods are slightly shifted intime for different groups of customers.

The consumers willing to enrol to ToU tariffs are typically medium to small consumers. Thecriterion for the participation of the small consumers is often the presence of electric waterheating or space heating with some storage capability. Other small consumers often don't findit beneficial to pay increased metering costs for little savings since the only loads they couldshift without too important a loss of comfort are appliances such as washing machines, dryersand dish washers.

The communication system required for ToU tariffs can usually be a one-way system wherethe retailer or the utility sends the tariff signals to the consumers and the consumers are justequipped with a multi-rate meter. It is therefore enough to read the meter in order to knowhow much electricity has been consumed during the different price periods. In addition, ToUtariffs can be combined with direct load control schemes (see 3.2.1).

3.1.2 Time-of-use tariffs on demand charges

Time of Use tariffs can also be applied on the network charges. The characteristics of suchprograms are the same as those of basic ToU tariffs. There is however an additional barrier.The regulator must accept such a tariff. For example in Norway, the regulator declared after apilot test that such projects wouldn't be allowed in the future because of their potential distur-bance of the ordinary market mechanisms.


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Table 1. Time of Use tariffs

Participants in-volved

Network operator Retailer Consumer

Their needs Reduce the need fornetwork improvements

Reduce their capacity needsand diversify their offer

Savings on bill

The service providedto them

Load shifting Load shifting Time varying tariffs

Signals received Yearly consumption for eachtariff period

In some cases, di-rect load control

Barriers encoun-tered and solution

For small consumers, the savings don't always cover the metering costs orthe actual shiftable load is deemed too small to bring benefits.

Results, response,success

Large response from small consumers equipped with a relatively largeshiftable load (e.g. electric space or water heating)

Lessons learnt andissues

The consumption peak at the switch to low price periods should be mitigated

3.1.3 Real-time pricing

Real-time pricing (RTP) gives a price for electricity that varies typically hourly to reflectvariations in the wholesale price of electricity. Generally, customers are notified of RTPprices the day before or a few hours before the delivery time.

There are two typical types of RTP. The first one is the day-ahead RTP in which customersreceive every day the prices for each of the next day's 24 hours. The second one is a two-partRTP in which the customers pay a ToU or a day-ahead RTP tariff for a baseload, but arecharged or remunerated for any deviation from the baseload at the spot market price. This de-sign serves to protect the consumers from RTP volatility, but allows them to achieve savingsby reducing their load at high prices.

As of now, RTP tariffs apply often only to large consumers (e.g. Georgia Power's program, inUSA, is open to consumers with a connected load of 900kW or more). Small consumers areexcluded from these programs because the costs of hourly metering and of communication aretoo high to make them interested and utilities usually don't want to have to deal directly withso many customers.

There has been however experiences of RTP for small consumers. They most often involvedirect load control solutions. It is difficult to expect consumers in their household to verifyeveryday the received tariff and plan their consumption according to it. Such a scheme wouldlead very quickly to consumers loosing their motivation and not reacting anymore. It has beennoticed that a good response remains possible even in the long run if the consumers are con-tacted actively (e.g. by phone or by email) when the prices reach above a predefined level.


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Figure 2. One-part (left) and two-part (right) real-time pricing (RTP) [8]

Table 2. Real-time pricing


Network operator Retailer Consumer


Reduce their capacity needsand diversify their offer

Savings on bill orcompulsory tariff

The service pro-vided to them


Signals received Hourly consumption for eachconsumer

Wholesale electricityprice


For small loads, the savings don't cover the metering costs.

Risks related to high-price periods. Can be negated by two-part tariffs and/orprice caps.

Time and resources needed to monitor the prices daily. Solutions are to sendparticular signals when high prices arise or to install an automated load controlsystem.

The volume of MW curtailed might be foreseeable


Where RTP tariffs are not compulsory, very few consumers are willing to par-ticipate


In USA, about 10 to 15% of load reduction could be achieved at very highprices.

Two-rate tariffs have more success where available.


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3.1.4 Critical peak pricing

Critical peak pricing (CPP) is a combination of ToU and RTP pricing systems. The basic ratestructure is ToU, but under specified trigger conditions, the normal peak price can be replacedby a much higher CPP price. Such conditions usually are that the system reliability is verylow or that supply prices are unusually high.

The CPP offers can be mostly sorted in several categories:- Fixed-period CPP: the time, the duration and the number of calls per year are predeter-

mined, but the specific days are not. The events are usually called on a day-ahead basis.- Variable-period CPP: the time, the duration and the days are not predetermined. Thermo-

stats with automatic response options are some typical loads available for this type ofCPP.

- Variable peak pricing: it is the same as other CPP systems, but here the peak price is rede-fined every day to reflect the market and network status.

- Critical peak rebate: this is the CPP variation of the two-part RTP. The consumers receivea rebate for the load reduction they produce during the critical peak periods, but remain onfixed rates otherwise.

Critical peak pricing is usually appreciated by large and small consumers with controllableloads because they offer a good security of decreased consumption costs while keeping therisks quite low. There is however a concern on the part of the network operators or marketagents about the reliability of the load reduction. The consumers are not entitled to any prede-fined reaction and the total realized load reduction can at best be a guess. That can be an issuewhen considering the possibility of selling or using it.

Table 3. Critical peak pricing

Participants involved Network operator Retailer Consumer


Reduce their capacityneeds and diversify theiroffer

Savings on bill



Signals received Metered response from theconsumer

Notification of peakperiods.In some cases, di-rect load control

Barriers encounteredand solution

The volume of MW curtailed might difficult to foresee


Load reduction capability ranging from 20 to about 50% for residential con-sumers depending on the program and the technologies.


The presence of automation technologies increases largely the responserate.

Good level of satisfaction on the consumers side.


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3.1.5 Summary of the price based DSI

The Figure 3 is a fictional example of what the price signals could be like for a single daywith the different price based DSI systems presented in this work.

In general, these DSI tariffs are designed in a way such as if an "average" consumer doesn'tchange its consumption pattern, the bill should remain unmodified and only with load shiftingcan money be gained or lost. Defining this "average" consumer and assigning load curves tothe consumers is a crucial part of the price-based programs. When the data is available, it canbe derived from earlier measurements. It is otherwise based on estimated load curves for eachtype of consumers typically depending on their appliances, their yearly consumption, the typeof building and the geographical location. It has to be noted that the price-based demand re-sponse is totally voluntary: it is the decision of the customer to react or not to price changesalthough in some cases some customer automation can be used to provide the response auto-matically.

For the introduction of this type of programs, especially at small consumers' level, an enroll-ment incentive is often proposed. This incentive is however usually removed when the pro-gram is stabilized and its profitability has been assessed.

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CPP

ToU

Flat tarif f

Figure 3. Fictional example of the three price-based DSI systems presented


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3.2 Incentive based

3.2.1 Direct load control

A direct load control (DLC) program allows the program operator to remotely shut down orcontrol a consumer's electrical equipment on short notice. Direct load control programs areusually offered to residential or small commercial consumers for equipment such as air condi-tioning, water heaters or space heaters.

Depending on the situation, the control of the appliances can be realized in different ways.The easiest and early used system was to simply turn off the controlled appliances for the du-ration of the event or for some other agreed period of time. The control was in that case real-ized using a one-way communicating switch.

With the development of technologies, the control strategies could become more sophisti-cated. First, each switch could be addressed and controlled independently from the others.Then the control actions became more subtle. The controlled unit could be turned down orhave their running cycle adjusted instead of being turned off. This can typically be achievedby changing the thermostat setting point of any heating or cooling device.

An important issue regarding DLC is the acceptance of the consumers towards loosing somecontrol over his own installation as well as loosing some comfort. That is why, most often,programs offer the possibility for the consumer to override the control. Depending on the pro-gram, there can be a penalty for using that override option.

The savings on the consumer's bills can vary from a program to another. Some programscombine DLC with CPP and the savings are obtained by reducing the load during the criticalpeak periods and during the on-peak periods on regular days. Another option is to offer anannual incentive or a general tariff reduction for consumers who agree to have their load con-trolled. This last option is often preferred for the simplicity of the metering and communica-tion system. In the cases where no penalty is incurred for overriding a control signal, no spe-cial metering or feedback installation is required.

Although DLC can be a stand-alone program, it is most often just a mean to increase the effi-ciency or to just make possible some other DSI possibilities such as for example capacitymarket or emergency demand response programs. Direct control can also increase the profit-ability and the attractiveness of the mentioned price based tariffs.

A problem sometimes encountered in an unbundled situation is to know who (distributionsystem operator) operates the actual load control and among whom (TSO, distribution systemoperator, retailer, aggregator) and how the costs and benefits are shared.

3.2.2 Interruptible/curtailable services

Interruptible or curtailable (I/C) services are options integrated into the retail tariffs. Theyprovide a rate discount or a bill credit for agreeing to reduce the load during system contin-gencies or during very high market price period. Some penalties can be assessed for a failureto curtail the load as agreed. Such programs have traditionally been offered to the largest con-sumers (usually industrial, sometimes commercial).


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Table 4. Direct load control

Participants involved Network operator or Retailer Consumer

Their needs Reduce the need for network improve-ments

Savings on bill


Consumption profile shaping Remote operation of con-trolled devices

Signals received Metering of state and/or consumption ofcontrolled device

Control signals directly to de-vices


There is a need for an override option. Its impact is difficult to predict.

The consumer has to create a new architecture of his own electrical installa-tion and to define several networks with different levels of priority.


This type of projects usually gives good results


Consumers want a feedback from their consumption and their savings.

Table 5. Interruptible/curtailable services


Retailer Network or system opera-tor

Consumer

Their needs Optimise purchases andsales

Manage contingencies ata reduced cost

Payment


Consumption profile shap-ing

Consumption profile shap-ing

Remote operation ofcontrolled devices

Signals received Metering of state and/orconsumption of controlleddevice

Metering of state and/orconsumption of controlleddevice

Control signals directlyto devices or eventnotification


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3.2.3 Demand bidding / Buyback programs

Demand side bidding (DSB) is a rather new instrument to get customer loads into the marketand it can also be classified as market based DSI ([10], [11], [12], [13], [14]). It is a termwhich refers to the opportunity offered by some electricity trading markets for consumers tochoose when and how to participate in real-time and day-ahead-spot markets. The process al-lows the consumer to be paid a market price for withdrawing load, when required by the mar-ket operator, in a similar way that generators are paid to supply. Consumers will bid for aspecified reduction, duration and availability, after which the bids will be ranked and chosenaccording to the market requirement. All bidders are typically paid the highest accepted bidoffer or, in the case of certain developing DSB markets, a minimum capped rate.

DSB markets have been introduced to support many aspects of maintaining an efficient andreliable electricity market. Different markets call for different planning horizons and responsetimes. Reflecting this, operators will assign a service requirement to a bid window, as definedin Figure 4

Figure 4. Service requirements for operators

DSB markets usually have a minimum load bid (e.g. 1 or 10 MW), which means that onlylarge customers can participate in the market. For small customers new types of aggregatorsare needed to collect aggregated loads and bid them into the market.

Demand bidding in the wholesale market is under the same rules as any other bidder. Thatincludes not only the minimum bet requirement, but also the participation fees and the re-sponsibility for power imbalances. It is therefore important to insure the profitability of theprogram that the available load reduction is forecasted as accurately as possible.


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Table 6. Demand bidding / buypack programs


Wholesale market operator Consumers

Their needs Increased liquidity on the market Sell back power at high prices.


Access to the wholesale market

Signals received Bid offers Acceptance/rejection of bid


Minimum size of a bid (typically of a few MW)


Few consumers participate because it is risky. Some very large consumerscreated a trading activity in order to participate in the wholesale market.

3.2.4 Emergency demand response programs

These programs provide incentive payments to consumers for a load reduction during periodswhen reserve shortfalls arise.

Table 7. Emergency demand response programs

Participants involved Network or System opera-tor

Consumers or agregators

Their needs To increase his reservecapacity

The service provided tothem

A curtailment capacity

Signals received The request of load reduction somehours before

Barriers encountered andsolution

The use of this request of reduction load must be limited : maybe lessthan 4 events per year.

Lessons learnt and issues The capacity must be paid even if curtailment is not called


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3.2.5 Balancing market programs with upfront capacity payment

The capacity, or balancing energy, market allows the wholesale market participants to pur-chase additional resources to correct their buying-selling imbalances. The market operator,often the TSO, examines the supply-demand balance typically 30 minutes before the deliverytime and procures additional energy, by buying it on the balancing energy market, to coverany shortages on behalf of all market participants.

In these programs, the consumer can offer load curtailment as system capacity in the sameway as generators or other delivery resources can offer production. Customers typically re-ceive an up-front payment to be on stand-by and an additional payment if the capacity iscalled and delivered. They usually receive notice to keep their capacity on stand-by one dayor several hours ahead, but the call for the utilization of that capacity is done only severalminutes ahead.

Table 8. Balancing market programs with upfront capacity payment

Participants involved Capacity market op-erator

Consumers or aggregators

The service provided tothem

Increased liquidity onthe market

Opportunity to sell some load reduction

Signals received Bid offers Bid acceptation or reject, hours ahead for stand-by, minutes ahead for reduction.


The short time response required can be difficult to adopt by aggregators.

Minimum bet size (e.g. 100MW), aggregation is needed for small con-sumers.

Advanced metering is necessary.

Results, response, suc-cess

When applied to small consumers, not often competitive.

When applied to small consumers, load reduction is viewed not to be reli-able (reduction achieved < announced)

Lessons learnt and is-sues

When offering bets on the market, better tools should be used to evaluatethe load reduction capacity of small consumers.


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3.2.6 Ancillary services market programs

Customers can here bid a load curtailment in their transmission network operator (TSO) orregional transmission operator (RTO) markets as operating reserves. If their bids are accepted,they are paid the market price for committing to be on stand-by and, if the curtailment isneeded, they are called by the TSO/RTO and are paid according to their bid or to the marketprice.

The ancillary services are resources used by the TSO/RTO to counter the imbalances of theBalance Responsible Parties. The time span of the notification typically ranges from a fewseconds to about 10 minutes.

Table 9. Ancillary services market programs


Network or System operator Consumers or agrega-tors

Their needs A load curtailment with very fast (within 10 minutesor less) and very reliable response


Increased liquidity on the market Access to the ancillarymarkets

Signals received Bid offers Acceptance / rejection ofbid

Barriers encoun-tered and solu-tion

Response within 10 minutes or less (load control can be operated from an Op-eration Center).

Inadequacy between announced availability and delivered availability.

Large minimum to bid offers volume.

For the moment, several European System Operator are reticent to create anancillary services market because it could become difficult to control the per-formances of the service. And this performance is very important for the ElectricSystem security.


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3.3 Demand aggregation

One obstacle in the promotion of DSI is that small and medium size customers usually don’thave direct access to different types of market either due to the market rules or due to the hightransaction costs in market entry. To decrease this kind of barriers new players/business op-portunities have been developed based on the aggregation of small distributed energy re-sources consisting of flexible loads, DG and energy storages. The concept behind aggregationis to use a set of distributed resources, coordinate them and present them as a single entity toother actors.

In this connection two main types of aggregators can be defined: demand aggregators andgeneration aggregators. The first group of aggregators is collecting demand response (DR)from different types of flexible customers and offering the aggregated DR to different marketactors: actually it can include also the generation at customer premises, for ex. the utilizationof back-up generators in DR. The second group is collecting and using a group of dispersedgenerators in aggregation and offering that into market. This kind of aggregated generation isoften called “Virtual power Plant (VPP)”. A combination of these two types of aggregators isalso possible.

Most of the existing demand aggregators use direct load control measures at consumers prem-ises in order to offer services to transmission or distribution system operators. Demand aggre-gator can also implement diverse price based tariffs to offer ancillary services.

Up to now, demand aggregators have focused on large or medium consumers such as indus-trial or commercial loads. The cases involving small (domestic) consumers are often reservedfor installations including electric space or water heating or cooling.

Demand aggregators often insist on the fact that their consumers won't have anything to payto participate and only receive benefits or offer a fixed payment. It seems important for theconsumers not to take financial risks. However, the aggregator will encounter penalties if hedoesn't provide the other actors the load reductions he announced.


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3.4 Technologies to support DSI

New technologies such as Smart Meters and Energy Boxes will add value to the basic De-mand Response proposition. Effective DR schemes often include technical equipment such asSmart Meters, enabling hourly metering reading, information feedback to customers via in-house displays, automated direct load control and/or two-way communication. These schemeshave the attribute of being relatively low cost, yet effective.

More advanced functionalities will unleash the full potential of DR. Some utilities (oftenthrough the distribution subsidies) and telecommunication companies are developing variousforms of Smart Energy Boxes that can allow:

- Multi appliances direct control (water boilers, air conditioning, etc), plug & play enabled;- Scheduling of electric appliances turn on or off;- Decentralised generation facilities management;- A wide range of energy related services and even other additional services.

Energy Boxes can add functionalities to Smart Meters. They can also help to anticipate SmartMetering implementation in countries were these projects are suffering delays, for specificcustomer targets. In this case a data logger makes the reading on the old meter and thus pro-vides the useful information to the box. Though this information may not be reliable for elec-tricity invoicing, it acts as a platform for functionalities and services. The benefit of this typeof technology is the optimal level of energy savings it enables; the disadvantage is often thecost, which is comparatively high and for certain applications unnecessarily prohibitive. Thishas been discussed in more details in the chapter 3.

In addition to these Energy Boxes, appliances manufacturers are currently developing goodsthat could interact with the Energy Box, allow more control from the user through an interac-tive display and return feedback on the effects of the actions taken.


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4 Description of selected past and on-going projects

4.1 ENEL experience with ToU tariffs.

In 2005 Enel has offered some TOU tariffs to its domestic customers with digital remotelyread and managed meter.

4.1.1 Night Tariff (available from February 1st 2005)

This tariff is dedicated to domestic customers with a supply contract of 3kW for the firsthouse, medium consumption – starting from 2640 kWh/year – and with a monthly bill ap-proximately over 55 euros. Possible customers here are mainly working couples or singles.

A blue band is defined from 7 pm to 1 am every day of the week and 24h/day on national fes-tive days. In this blue band an average discount of 16% on the normal flat tariff, defined bythe regulator for residential domestic customers, is offered under the condition that at least26% of the total consumption is concentrated in the blue band.

The greater the concentration of the consumption in the blue band, the greater the applied dis-count and the savings on the bill is. Fix charges are the same as the normal flat tariff.

If the threshold of 26% on the blue band is not reached in each bimonth (billing is bimonthly)the blue band consumption is charged at the normal flat tariff defined by the regulator for resi-dential domestic customers.

Small households can achieve savings from 10 to 80 Euros/year with this tariff.

4.1.2 Week-end tariff (available from February 1st 2005).

This tariff is dedicated to the same domestic consumers as the Night Tariff described above.Here, the blue band is defined as being 24h/day on Saturday, Sunday and national festivedays.

In this blue band an average discount of 22% on the normal flat tariff, defined by the regulatorfor residential domestic customers, is offered, under the condition that at least 26% of the totalconsumption is concentrated in the blue band.

This tariff works according to the same principles as the Night Tariff and allow the same sav-ings of 10 to 80 Euros/year.

4.1.3 DUE tariff (available from January 1st 2005)

This tariff is dedicated to domestic customers with a supply contract of 3 kW for the secondhouse and domestic customers with supply contracts of 4,5–15KW both for the first and thesecond houses. Possible customers here are mainly families that frequently use their secondhouse or with high consumption.


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The blue band is here defined from 8pm to 7 am from Monday to Friday, 24h/day on Satur-day, Sunday and national festive days. In this blue band an average discount of 15% on thenormal flat tariff, defined by the regulator for residential and non residential domestic cus-tomers, is offered, under the condition that at least 57% of the total consumption is concen-trated in the blue band.

Consumptions not in the blue band are charged with a tariff 1% greater than the normal flattariff defined by the regulator for residential and non residential domestic customers.

The greater the concentration of the consumption in the blue band, the greater the discountapplied and the saving on the bill is.

If the threshold of 26% on the blue band is not reached in each bimonth (billing is bimonthly)consumption in the blue band is charged at the normal flat tariff defined by the regulator. Fixcharges of the bill are greater than the ones applied to the normal flat tariff.

Households can achieve savings from 10 to 70 Euros/year with this tariff.

In 2006 DUE tariff has been slightly modified reducing the average discount applied from15% to 10%. Furthermore a new tariff called OTTOSETTE has been introduced (see below).

4.1.4 OTTOSETTE Tariff

This tariff is dedicated to domestic customers with a 3kW supply contract for the first houseand medium consumption starting from 2640 kWh/year.

The blue band is defined from 8 pm to 7 am from Monday to Friday and 24 hours/day on Sat-urday, Sunday and national festive days. In this blue band an average discount of 6% on thenormal flat tariff, defined by the regulator for residential domestic customers, is offered, un-der the condition that at least 57% of the total consumption is concentrated in the blue band.

The greater the concentration of the consumption in the blue band, the greater the discountapplied and the saving on the bill is.

If the threshold of 57% on the blue band is not reached in each bimonth (billing is bimonthly)consumption in the blue band is charged at the normal flat tariff defined by the regulator fordomestic residential customers. With this tariff savings from 10 to 80 Euros/year can beachieved.

Table 10. Possible savings per year for customers

3.000 kWh/year 4.000 kWh/year 5.000 kWh/year

Night (26% the blue band) € 19 € 50 € 73

Weekend (26% the blue band) € 16 € 46 € 68

Due (70% the blue band) € 38 € 51 € 64Note: bimonthly billed amount:

First house: 75 € with a consumption of 3.000 kWh/yearSecond house: 104 € with a consumption of 3.000 kWh/year


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Table 11. Customers who have adopted the DUE tariff

DUE tariff Customers at the end of

2005 2006Residential 111.676 530.855

Non Residential 87.089 261.470

TOTAL 198.764 792.325

Table 12. Customers who have adopted the NIGHT, WEEKEND and OTTOSETTE tariff, in2006

Customers at the end of 2006

NIGHT 439.346

WEEKEND 25.864

OTTOSETTE 33.306

These tariffs have been in effect until the complete market liberalization in July 2007. FromJuly 1st 2007 customers who had adopted the Enel TOU tariffs have been automaticallyswitched to the flat normal tariff defined by the Italian Regulator.

3 months after the regulator has issued new TOU tariffs.


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4.2 EDF (France) experience with DSI

4.2.1 Heures pleines / Heures creuses (peak/off-peak hours) (Time of Use)

This tariff took place in 1965 and was designed to level the load because of power plant con-straints. It provided lower tariffs during the night and sometimes during the afternoon and al-lowed EDF to shift a part of the consumption.

Domestic hot water devices are controlled directly and are automatically started during off-peak hours and stopped during peak hours. In order to avoid a severe demand ramp when thetariff is changing from off-peak to peak, the different consumers are subjected to several dif-ferent timetables.

Figure 5. effect of the peak/off-peak Time of Use tariff adopted progressively in France since1965 (we can observe the large smoothing effect on the global daily load curve – expressed inp.u. on Y axis)

4.2.2 EJP (Critical Peak pricing – Fixed-period CPP)

This is a contract between EDF retailer and a consumer. It consists of a very low tariff exceptduring the days labelled "EJP day". The price of a kWh on an EJP day reflects the costs of theglobal system (in particular costs of production) during this period. There are 22 EJP days in ayear and EDF informs the consumer the day-ahead. An EJP day begins at 7 am and finishes at1 am the following day. The purpose of this tariff was to improve the system safety by avoid-ing load shedding


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The TSO (RTE) is an indirect participant. There is an agreement between EDF and RTE inorder to separate the EJP days in different areas for grid congestions and so on. RTE can de-cide some EJP for his own constraints.

The consumers can decrease their annual bill by decreasing their consumption on EJP days. Inpractice, industrials have their own generators used 22 days in the year when EJP is declared.

The EJP tariff started in 1982. For the residential consumers, it has been replaced by Tempo(see below) for the new contracts. Nowadays, EJP is not proposed anymore. It is applied onlyon on-going contracts.

Results

In 1994, a day with EJP was subject to about 7 000 MW of curtailment ( ~ 10 % on total con-sumption). That volume dropped to 2 400 MW in 2008 ( ~ 3 % on total consumption). In thiscase, the part of residential curtailment represents about 400 MW. We have to remember thatthis tariff is not proposed anymore and that only current contracts are still in action.

EDF assesses that a residential consumer with EJP tariff decreases his peak consumption byabout 50%. We observe a shift of load : the consumer’s consumption decreases by 57 % from7 am to 1 am and increase by 39 % from 1 am to 7 am with a peak at 1 am (at 1 am, the con-sumption is multiplied by 4, that is to say 2 times the normal consumption without EJP).

Overall, the reaction of small businesses is very low. The reactions vary but on average, thecurtailment is about 0,2 kW per costumer against 0,7 kW for a residential consumer. In total,there is only about 32 MW of small business’ curtailment.

4.2.3 Tempo (Critical Peak pricing – Fixed-period CPP)

This tariff started in 1996. It was designed for small consumers in complement of the EJP tar-iff which is more targeted for large consumers. This tariff has been not proposed since 2004.

Every day, at 5 pm, EDF presents on its web site, the colour of the next day: red, white orblue (3 tariffs). The colour is also sent to each home on a box at 8 pm day ahead and the con-sumers can be also informed by e-mail or SMS. There is a maximum of 22 red days and 43white days in a year.

Each day, regardless of its colour, is composed of two periods with a different price: off-peakand peak (Time of Use Tariff). All in all (with the three colours), there are 6 tariffs, all prede-termined and fixed.

EDF also proposes a box which can control electric heating and domestic hot water devicesaccording to the colour of the day and the program chosen by the consumer (comfort, eco …)

Gradually 300,000 residential customers and more than 100,000 small business customershave chosen tempo. This tariff reflects better the real time costs of production.


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Results

- In 2008, a red day offered about 400 MW of curtailment. EDF estimates that on average,residential consumers decrease their consumptions in peak hours by 50 % and by 25 % inoff-peak hours. A part of the consumption is shifted to off-peak hours. The curtailmentvolume is twice higher in houses with electrical heating than in houses without electricalheating (In percentage, the consumption decreases by 37% instead of 30% because thehouse with electrical heating consume more, so the difference in percentage is lower).

- Tempo was chosen by consumers in order to reduce their electricity bills and customersare generally happy with this tariff.

- The curtailment has been observed to decrease in situations with several consecutive reddays.

Difficulties for the retailer (EJP or Tempo)

- The retailer has to design the price of each tariff in order to give incentive to consumers tochange their uses but without losing money. It is difficult because the regulatory frame-work can change. For example, in France, the network tariff is fixed independently andthe tariff designed by the retailer could become uninteresting when it changes.

- The retailer has a limited number of red days or EJP days in a defined period of time. Thatbrings some management constraints.

4.3 RTE (France) - "Diffuse adjustment" on the “Balancing mecha-nism”

This system can be seen as a “Capacity/Balancing market program” with the TSO but theconsumer is not paid if the curtailment is not called. The TSO typically calls the curtailmentsome hours before.

It is a new experimental mechanism proposed to aggregators in 2008. A player can aggregatea lot of consumers and propose to the TSO (RTE) an offer (volume, price) in the BalancingMechanism. The aggregated offer must be higher than 10 MW.

The Balancing Mechanism aims to mobilise reserves to ensure the generation-consumptionbalance in real time. Through a bidding system, the players of the market communicate thetechnical and financial conditions on the basis of which RTE can modify their generation orconsumption programmes. RTE makes up for any imbalances by selecting offers, after havingranked them according to a merit order criterion and by taking into account the technical con-straints expressed by the partners.

This mechanism has been already proposed to high consumers since 2003 but in practice,there is just a few participants (20 to 40MW) and usually notavailable during interesting peri-ods.

In order to be useful, the program should propose a payment for unused capacity and the in-formation systems should be simplified, i.e. to make it easier than the one used by producers.


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4.4 SINTEF (Norway) DSI pilots

SINTEF Energy Research is part of SINTEF, a Norwegian research center. They have been incharge of studying the diverse DSI pilots run under the "Market Based Demand Response"project (2005-2008) [1].

The involved actors identified in the project and their potential benefits they can achieve arelisted here:

- Flexible consumer: Improved energy economy when consumption is reduced in high priceperiods.

- DSO: DSI can reduce bottlenecks problems and system losses in peak hours. The cus-tomer satisfaction can be increased and new AMR services can be commercialised in thefuture.

- Power supplier: New and attractive contracts can be an advantage. There is also a poten-tial for reduction of the volume risk in high price periods.

- TSO: Increased demand side participation improves the functioning of the electricity mar-kets as well as the operation of the power systems.

- Technology manufactures and vendors: Opening or developing markets for smart metersand other new products such as price dependent load control devices.

4.4.1 Time of Day (ToD) tariffs

The ToD tariffs are ToU tariffs on network costs and thus initiated by a regulated market par-ticipant.

A special authorization was required from the regulator (NVE) for the pilots. It should benoted that NVE stated in the end of the project that "ToD tariffs and other network tariffs thatmotivate to change of load pattern, will not, at this stage, be allowed on a general basis. Thisis because of the potential disturbance of the ordinary market mechanisms".

ToD "energy tariff" for households

The form of the tariff is obtained by dividing the existing energy part into one part coveringthe network losses and one part with high price in the expected peak hours on working days.The design is such that an average consumer who would not change his behavior would bebilled the same amount as under the standard tariff.

A special authorization was required from the regulator (NVE) for the pilots. It should benoted that NVE stated in the end of the project that "ToD tariffs and other network tariffs thatmotivate to change of load pattern, will not, at this stage, be allowed on a general basis. Thisis because of the potential disturbance of the ordinary market mechanisms".

ToD "Power tariffs" for commercials and institutions

The traditional way to settle power tariffs for commercial customers is based on the peak loadof the individual consumer. In the pilots where ToD have been tried, the power tariffs wereset based on the consumer's consumption during the system's peak hours.


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4.4.2 Fixed Price With Return option (RTP)

The Fixed Price With Return option (FWR) is a pilot tariff conducted by Trondheim energy.It is an RTP tariff, but its presentation has been modified for marketing purposes. TrondheimEnergy considered the fact that domestic consumers have a limited knowledge of electricitymarkets as a barrier for proposing a straightforward RTP tariff. That is why they have chosento present it as being a flat rate and the possibility for the consumer to sell back unused or tobuy additional power. The pilot shows that compared to a standard RTP tariff, the consumersresponse is similar, but is sometimes larger when high prices occur. It is assumed that the rea-son is that the FWR marketing was focusing on the possibility for the consumers to actuallymake money on high price situations.

4.4.3 Remotely controlled load shifting (DLC)

Based on the ToD tariffs mentioned above, Malvik Everk developed a pilot for direct loadcontrol. Forty households customers with hourly metering (Malvik Everk has realized a fullroll out of AMR to the consumers prior to the pilot) participated in the pilot. 10% of them hada waterborne space heating system with an electrical boiler of 12-15kW while the others had astandard electrical water heater of 2-3kW. The control was performed through Power LineCarrier (PLC) and relays connected to a connection terminal for the AMR system. An identi-fied risk of PLC was a failure in communications due to changes in the system configurationor when terminals are moved between different substations. For that reason, an overrideswitch was installed at each household to reduce the risk of non-reconnection after the event.

A small extra feature of this pilot is "El-Button". It is a small watch-like magnet token thatcan be positioned on appliances such as washing machines or dryers with the peak hoursshowed in red to remind the consumers not to use the appliances during those hours.

The average demand response realized during the pilot is showed in the following table.

08:00-10:00 17:00-19:00

Customers with electrical waterborne space heating system ~2,5-3kWh/h ~1,3kWh/h

Customers with electrical water heater ~1kWh/h ~0,5kWh/h


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4.5 Austin Energy – DSM program (DLC)

Austin Energy (Texas, USA) is giving away free programmable thermostats that are keepingcustomers comfortable and cutting Austin’s summer peaks.

In addition to the Energy Star rating that helps customers save up to 15% on their heating andcooling bills, these thermostats have an embedded communications chip that enables Austinto remotely cycle air conditioning usage on peak days. With over 50,000 participants, thePower Partner program contributes an average of 45 megawatts of peak capacity to Austin’soverall supply portfolio.

Alongside the thermostat, the program features a web programming tool which allows partici-pants to program their thermostat over the web – from anywhere with an internet connection.

Austin had faced rising peaks as central air conditioning became more and more prevalent inthe Austin area. In order to solve peak capacity challenges without building a plant or pur-chasing power off the spot market, Austin developed a portfolio approach of energy effi-ciency, demand response, and overall conservation programs.

The portfolio approach, including a broad range of strategic conservation, load shifting, andpeak clipping resources, provides real value to participants while at the same time allowingAustin Energy to cut peak procurement costs and keep electricity prices low for everyone.

The Choices

As Austin evaluated options for the Power Partner program, answers to technology, commu-nications, and implementation choices were not immediately obvious.

The team at Austin conducted in-depth research and analysis of virtually every major vendorin the space, coupled with interviews with other utilities currently implementing load man-agement programs.

Of the many issues that the team evaluated, they spent the most time considering one way vs.two way communications, VHF (lower frequency) vs. 900 MHz (higher frequency) paging,and determining the right mix of control switch and “smart” thermostats for their service terri-tory.

Two-way communicating thermostats can provide utilities with more data on their load man-agement system, such as verification of receipt of signal, temperature data, and overall usagetrends. They also enable real time and critical peak pricing rate options when coupled with anAMI system by verifying the receipt of a critical pricing signal.

The drawback on this technology, however, is cost of the return communications path. From adesign perspective, the additional power required to generate a return signal requires costlytechnology – think of it as virtually integrating a cell phone into every thermostat. Eventhough cellular technology would not be used in this application, it’s an easy way to envisionwhat a two-way communications module might require. This can translate into a cost of overdouble that of a oneway solution – which, when identically configured, provides the sameload shed capacity as its two-way counterpart.


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While a two-way communicating thermostat provided lots of intriguing bells and whistles, theend result in terms of megawatts was no different than that which could be achieved with aone-way stat. The cost adder on the two-way device coupled with high recurring communica-tions costs lead Austin Energy away from a two-way system and encouraged to look at differ-ent methods of system measurement and verification such as physical inspections and statisti-cal sampling.

Higher vs. lower frequency paging can make all the difference in a load management programas signal strength and penetration determine whether an end device receives the utility’s sig-nal to control. For a load management system – especially thermostat gives participants a freeDemand Response enabled programmable thermostat based, where the receiver is static andindoors – VHF (lower frequency) has proven to provide markedly better reception than 900MHz (higher frequency) due to its heightened ability to penetrate buildings and walls. Higherfrequencies are often stronger for mobile endpoints – like a police car, for example - as thesesignals are more inclined to reflect off of objects and therefore provide more seamless cover-age.

In the end, Austin chose to utilize their existing and operable VHF communications infra-structure - a technology that met their needs at the lowest possible cost – and chose a one-way, VHF communicating “smart” thermostat provided by Comverge.

Throughout the 2005 testing and deployment of the second generation thermostat, the team-work and communication between both teams enabled a more robust and ultimately moresuccessful product to be developed – from hardware to firmware to system communications tothe web interface.

Initially the program was launched as a pilot of 3,000 residential points, but within six monthsit had ramped up to 10,000 points. The program currently has:

- over 21,000 single family residential participants;

- 25,000 multi-family participants;- over 4,000 small commercial participants.

The program offers no cash or rebate incentives to participants when they sign up – only theSuperStat, which is a difference from many of the nation’s demand response programs whichoften offer rebates of up to $100 to sign up. Participants receive the free SuperStat in ex-change for allowing their A/C to be cycled back on weekdays from 4:00 pm – 8:00 pm duringthe summer months (June – September).

The program is never run on a holiday or weekend, which means that many participants willnever even be home during an “event.”

Austin uses a 33% cycling strategy with an Adaptive Algorithm, intelligence that customizesthe cycling time to each individual compressor, thereby eliminating free-riders. As compres-sors can be oversized or undersized for the amount of space they cool, their run times varyconsiderably – from an oversized compressor that hardly runs at all to an undersized compres-sor that runs constantly. Without an Adaptive Algorithm, a 33% cycling strategy would askeach of these compressors to turn off for 10 of 30 minutes which may not affect the oversizedunit at all, while considerably affecting undersized unit.


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The Adaptive Algorithm records the compressors run time on an hour by hour basis, so thatthe compressor will be cycled back 33% from its run time of the previous hour when an eventis called.

For example, if a compressor ran 15 minutes on and 15 minutes off over the past hour, theusage would change to 12 minutes on and 18 minutes off during an event.

This allows for equitable cycling across the population and provides greater load shed andhigher comfort levels for participants. Data from across the country has shown that this trans-lates into an average indoor temperature change of 1-3 degrees over an event – unnoticeableby many people.

Austin’s customer survey response data is evidence of the program’s non-intrusive design.Even with 12 events in 2005 and 13 in 2006, all survey respondents said that they would rec-ommend the program to another person, with over 80% responding “Definitely.” Over 75% ofrespondents identified their experience with the program as “Excellent.”

4.6 Exelon (Commonwealth Edison) and The Community EnergyCooperative (RTP)

Rate RHEP, Residential Hourly Energy Pricing/Energy-Smart Pricing PlanSM.

This description is extracted from the US survey conducted by the Lawrence Berkeley Na-tional Laboratory in 2003 and updated from the 2005 Evaluation of the Energy-Smart PricingPlanSM [17].

Tariff Description

Rate RHEP is a pilot program, based on one-part, bundled tariff design and offered to Co-mEd’s residential customers. Participants in the program are provided with a range of supportservices through the associated Energy-Smart Pricing PlanSM (ESPP), offered by the Com-munity Energy Cooperative, a local non-profit organization that helps small energy consum-ers reduce their energy costs. To be eligible for the program, a residential customer must be aCooperative member (requiring a $5 membership fee).

Charges on participants’ energy use include three components: hourly energy prices, an ac-cess charge, and a participation incentive. Hourly energy prices are calculated from Platts’day-ahead peak period (16-hour) market price into ComEd, which is converted into hourlyprices using an algorithm based on the historical hourly PJM West Price shapes. The hourlyenergy prices are made available to participants by 5 p.m., the day prior. The access charge isa volumetric charge assessed on participants’ total usage in each billing period. It is based onthe difference between the revenues that would be generated through standard tariff chargesand the projected revenues from hourly energy charges, as applied to the class average loadprofile. Finally, customers receive a participation credit of $0.014/kWh, which is applied totheir total energy consumption in each billing period.


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Tariff History: Utility Motivation and Goals

This tariff, launched as a pilot in 2003, is an evolution of ComEd’s previous pay-for perform-ance type demand response programs, and thus is very much motivated by an interest in loadmanagement and peak demand reduction. It is also viewed, by the Cooperative in particular,as a way to provide residential customers with opportunities to reduce their energy costs. As apilot, the tariff is serving primarily as an experiment to investigate how residential customerswill respond to hourly prices, in terms of both short-term price response and more persistentconservation or energy efficiency effects, and also to see what types of supporting servicesand tools are most valuable to residential customers receiving RTP service. Rate RHEP isscheduled to expire at the end of 2005, but ComEd and the Cooperative are both interested incontinuing the program if the pilot results are encouraging.

Participation

Enrollment for the pilot was capped at 1,000 customers for 2003; this cap will be raised to5,000 in 2004 and 10,000 in 2005. Marketing for the program was the responsibility of theCooperative, who solicited participation through mailers, advertising, and community meet-ings. A group of 1,800 prospective participants returned interest forms during the first fewmonths of the program’s availability. Of these, 750 eventually enrolled (the remaining portionof prospective participants either were not eligible or did not return enrollment agreements).In 2005, the number of participants grew to almost 1500 customers.

Rate RHEP and the Cooperative’s ESPP were designed with the intent of providing residen-tial customers with an acceptable combination of expected benefits, costs, and risks. Someamount of passive bill savings was deemed appropriate to reflect the transfer of price risk tothe customer and the level of risk aversion characteristic of residential customers. Thus, the$0.014/kWh participation incentive was added to the tariff, providing an expected 10-12%passive bill savings. Interval meters are provided to the customers at no charge, and the costsare borne by the Cooperative. Participants are also provided with a range of support servicesthrough ESPP. The Cooperative provides general information to participants about energyprices and strategies they can employ to respond to prices. In addition, they issue price alerts,notifying customers whenever hourly energy prices for the following day will rise above$0.10/kWh. The Cooperative also purchased a price hedge on the participants’ behalf, to en-sure that they are not exposed to prices exceeding $0.50/kWh.

Load Response

Summer 2003 was relatively mild, with ten days of price alerts (i.e., hourly energy prices ex-ceeding $0.10/kWh) and a maximum hourly energy price of $0.12/kWh. An analysis of par-ticipants’ price response was conducted, which found that the maximum load reduction wasapproximately 330 kW (or 22% of the participants’ aggregate peak demand). Participants’average price elasticity was measured to be -0.042, with a particularly strong response duringprice alert periods (Summit Blue Consulting 2004). Some evidence of customer fatigue wasrevealed, as participants’ response was found to taper off over the duration of high price peri-ods and as the number of successive days of high prices increased.

In 2005, the summer was hotter and prices increased (with 57 high price notifications, someof them lasting as much as 13 hours in the day). Their elasticity was then estimated to be -


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0.047, but once again, the notification of high-price by phone or email increases the custom-ers' response, particularly if the high prices occurred during the late afternoon or during theevening.

Out of the 750 customers participating during summer 2003, 10% were consistently high re-sponders, more than 50% responded significantly, and most of the remainder responded tosome degree. Participants who live in multi-family dwellings and have central air condition-ing exhibited the largest response to high hourly energy prices. Such participants reducedtheir electric use by almost 30% during periods when prices exceeded $0.10/kWh. Othergroups of participants reduced their demand by 16-20% on average during these periods.These values and characteristics were also observed in 2005.

4.7 California Statewide Pricing Pilot (ToU, CPP & DLC)

The California Energy Commission and the California Public Utilities Commission ran aStatewide Pricing Pilot (SPP). The full pilot exposed 2500 residential and small commercialcustomers to ToU and two CPP tariffs during 15 months starting in July 2003. The customerswere randomly selected across 4 different zones related to climate conditions and 3 buildingtypes. Subsequent analyses show that the sample would be representative of the Californiansituation.

Each of the CPP tariff was based on ToU, but differed on the minimum delay for the advancenotice. The simple ToU tariff as well as the fixed-rate CPP were applicable statewide, but thevariable CPP could only be targeted to specific consumers. The fixed-rate CPP (CPP-F) couldbe called up to 15 times during a year and imposed a 1-day advance notice. The fixed rate wasadded to the normal ToU tariff. The price in the variable CPP (CPP-V) could adapted and wassent to the consumers 4 hours before the event. The notices would be made by email and/orby message on a mobile phone.

As a result, the residential consumption could be reduced by up to 14% on critical peak peri-ods and held steady through the duration of the pilot as well as through successive CPPevents. Small (<20kW) and medium (<200kW) commercial customers showed respectively6% to 9% and 8% to 10% of load reduction during CPP periods. Although, they are less re-sponsive than residential consumers, they show a larger absolute load potential. Overall, about70% of the consumers experienced savings on their electricity bill with CPP or ToU tariffs(about 60% for commercial consumers with ToU tariffs) compared to flat tariffs.

The pilot showed that:

- Residential and commercial consumers show strong support for these programs.- The participants had a good understanding of the rates but misunderstood some of the

specifics.- The participants' motive for a behavioural change is the perspective of saving money- Some participants stated that they used energy management strategies also out of the CPP

periods in order to reduce their consumption.- Only very few participants chose not to respond to the events.- Over 70% of the participants have initially chosen to remain on their CPP rate even if it

includes an additional monthly meter charge


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California Automated Demand Response System

In addition to the pilot tariffs, some households were equipped with automated demand re-sponse systems (ADRS). The ADRS could be programmed and monitored by the consumerthrough an Internet interface. It in turn controlled some appliances such as water heaters,thermostats or pool pumps. The ADRS is programmed so that those appliances react auto-matically to price signals.

This program showed that consumers with automated response consumed respectively 34%and 18% on-peak electricity per day than other consumers on flat rates and on CPP-F rate ondays without a critical peak event. Those percentages increased to 50% and 26% on days witha critical peak event.

4.8 Demand Turndown Trials (Balancing market participation)

The source of this description is the report on the Demand Turndown Trials [18] by NationalGrid.

During the summer 2004 and the winter 2004/05, the Demand Side Working Group (GSWG)and National Grid agreed to run pilots to offer the opportunity to the demand side to more eas-ily participate in balancing mechanisms. However, the structure was modified to allow earliernotice to the consumers.

Both trials offered an availability payment, an additional stand-by payment for stand-by in-structions (with a minimum of 8 hours ahead warning time) and an utilization payment whenthe service was actually utilized (with a minimum 2-hour warning time). The load reductioncould be called during fixed delivery windows. In the Summer pilot, there were two windows,one between 09.30 and 11.30 or one between 11.30 and 13.30. In the Winter pilot, it has beenreduced to a single window per day, between 09.00 and 11.00.

For both pilots, a minimum availability of 100MW was necessary to be allowed to offer loadreductions. However, the participation was below expectation (two participating aggregatorwith a maximum theoretical volume of 99.6MW between them) and that constraint has beenrelaxed for the Summer pilot.

These pilots showed that aggregators can provide a single point of dispatch for a demandturndown service. They have however highlighted a number of issues and barriers.

None of the providers were able to provide the original 100MW requirement during theSummer trial. Some of the identified reasons are the following:

- Timing of the scheme -coinciding with negotiation of supply contracts.

- Operational difficulties for providers of having back to back 2 hour windows (easier toprovide a service on a more flexible basis to fit around operational schedules)

- Infancy of the scheme

- Short contracting process- Lack of awareness of the scheme

- Limited choice of aggregators


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- Adoption of a ‘wait and see’ approach and subsequently evaluating whether to participatein any future opportunities

- A utilization payment formula which potentially underestimated the volume of DemandTurndown that had been delivered

During the winter trial, the 100MW limit has been more strict. Only one aggregator partici-pated and availability over 100MW could be offered 30 days out of 89. There have been twostand-by calls and only one was followed by an actual call for reduction. On that day, the de-clared availability was 134.2MW, but the volume delivered was only 65.9MW. This differ-ence leads to the following barrier.

During the trial actual availabilities and volumes delivered during utilizations were measuredto be significantly lower than the declared availability. For system security reasons NationalGrid requires confidence that on instruction of any service the volume declared available canbe relied on to be delivered.

During the trial, Demand Turndown Utilization prices could only economically competeagainst a small proportion of the BM synchronization actions taken. Based on the SummerPilot and factoring in Standby and Availability payments made, Demand Turndown did notappear to be an economic way of creating contingency reserve.

Post trial analysis has identified that the size of the reserve requirements in contingency time-scales experienced during the trial, meant that a service of limited volume (even 100MW)would not have been sufficient to be able to displace larger, more expensive alternative BMactions. This suggests that in order to have any chance of being competitive in contingencyreserve, much larger volumes are required.

4.9 Ontario Energy Board smart price pilot (ToU & CPP)

The Government of Ontario committed to install smart electricity meters in 800,000 homesand small businesses by 2007 (and throughout Ontario by 20101). The continued installationof smart meters has been aimed at ultimately enabling the application of TOU pricing, as setby the Board, to all electricity consumers on the Regulated Price Plan (RPP), i.e., those con-sumers not on a retailer contract. Virtually all RPP consumers in Ontario had been payingtwo-tiered threshold (non-TOU) prices.

Since the RPP was introduced in April 2005, Ontario distributors were permitted to makeTOU pricing mandatory for their customers with smart meters. Milton Hydro was the onlyOntario utility that opted from the very beginning to implement RPP TOU pricing on a rela-tively large scale for its customers with smart meters. Milton Hydro first implemented TOUpricing in October 2005 and the plan was to have over 15,000 customers on RPP TOU pricingby the end of the 2007. Chatham-Kent Hydro implemented TOU pricing on a small scale. OnMarch 23, 2007, the first TOU bills were issued to 215 customers for the January 2, 2007 toMarch 6, 2007 read dates.

1 Energy Conservation Responsibility Act (2005)


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Implementation of TOU pricing on a mandatory, Province-wide basis for consumers withsmart meters has been deferred pending the further deployment of smart meters. The installa-tion of smart meters and their enrolment into the provincial meter data management and re-pository (the “MDM/R”) is being done on a phased basis. The MDM/R is currently under de-velopment by the Independent Electricity System Operator (IESO) and will be eventually op-erated by the Smart Metering Entity (SME).

Pilot experience motivation

Taking advantage of the situation described, the OEB (Ontario Energy Board) in collaborationwith some distribution companies launched several pilot programs2. They were all aimed notonly at assessing the demand response to TOU, but also to other possible tariff designs.

In this context, the OSPP (Ontario Energy Board Smart Price Pilot) was launched in June2006. The pilot recruited participants that were placed on the TOU prices starting on August1, 2006. Originally the pilot was intended to end on December 31, 2006, but the Board subse-quently decided to extend the pilot period until February 28, 2007 to capture the coldest win-ter months.

Pilot Objectives

The Ontario Energy Board Smart Price Pilot was intended to assess:

- The extent to which various time-sensitive pricing structures cause a shift of electricityconsumption to Off-Peak periods as measured by the reduction in peak demand

- The extent to which each price structure causes a change in total monthly electricity con-sumption

- The understandability of and acceptability by residential consumers of each pricing struc-ture and the communications associated with each

Price design

Three different commodity price structures were tested during the pilot:

- RPP TOU prices- RPP TOU prices with a critical peak price

- RPP TOU prices with a critical peak rebate

2 The updated list with the projects approved so far can be found at:http://www.oeb.gov.on.ca/html/en/industryrelations/ongoingprojects_regulatedpriceplan_smartpricepilot.htm

http://www.oeb.gov.on.ca/html/en/industryrelations/ongoingprojects_regulatedpriceplan_smartpricepilot.htm


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Participant usage on these three price plans was compared with the usage of customers in afourth “control” group who also have smart meters but remained on the two-tiered RPPprices. The three price structures are designed to be as revenue neutral as possible relative toeach other. This is defined such that a participant whose electrical usage is distributed acrossthe hours in the same way as the provincial average for all RPP consumers will pay approxi-mately the same bill on all three options in the absence of any change in usage. This revenueneutral approach is the same design used in the California Statewide Pricing Pilot and thePowerCentsDC pilot in Washington D.C. By controlling for total bill amounts prior to de-mand response to the prices, the revenue neutral design allows for a more accurate compari-son of the demand response effects associated with the three price designs tested.

All RPP TOU prices were adjusted during this pilot for all three groups to reflect changes tothe RPP prices applied across the province on November 1, 2006. This change in RPP priceswas relatively minor. As such, the critical peak price and rebate amount remained the samethroughout the pilot. This change is important to continue a valid comparison against theprices charged to the control group. All prices on the pilot are related solely to the commodityportion of a customer’s electricity bill; delivery, debt retirement, and other charges were notchanged as a result of the pilot.

All three price structures tested in the pilot are described next in more detail:

- The existing RPP TOU prices and hours alone (without any critical peak adjustments)were used for one of the treatment groups in the pilot. This tariff differentiates prices foroff-peak, mid-peak and peak hours in each of the seasons considered: summer (Aug 1 -Oct 31) and winter (Nov 1 - Feb 28).

- TOU with CPP (Critical Peak Pricing): as with RPP TOU prices, the Critical PeakPrice was designed to be as revenue neutral as possible. The critical peak price was de-termined to be the average price of the highest 93 hours between June 2005 and June2006, based on the hourly Ontario electricity prices (the HOEP). The applicable RPPTOU prices and hours were used for all non-critical hours during the pilot; however, theOff-Peak price was reduced to offset the increase in the Critical Peak Price.

The CPP represents about a three-fold increase over the On-Peak price. The reason for thedifferent percentage amounts (in terms of the reduction in the Off-Peak price versus theincrease from the On-Peak price to the Critical Peak Price) is that critical peak prices arein effect during the few hours when critical events are declared, while Off-Peak prices arein effect for over 4,700 hours (or over half of all hours). Critical peak pricing only occursfor 3 or 4 hours during the On-Peak period, on critical peak days only. The maximumnumber of critical peak days planned for the pilot was 9.

Two approaches were considered for triggering critical peak events. The first was to dis-patch in parallel with the Independent Electricity System Operator’s (IESO) voluntaryEmergency Load Reduction Program, for which only large wholesale market consumersare eligible. For this program, the IESO forecasts day-ahead supply and demand and callsan event when forecast supply margins are very low. However, because this is designed tobe an emergency program, it is intended to be triggered relatively infrequently (i.e., only ahandful of days per year are expected).


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While this may be appropriate for the long term (perhaps if and when CPP is implementedprovince-wide), the short pilot schedule made it necessary to consider a weather trigger toincrease the likelihood that a sufficient number of events would be called during the pilotperiod to provide the necessary data for analysis. A weather trigger is commonly used incritical peak programs. The trigger is calculated based on historical data to determine howmany times a particular temperature was exceeded (on the high side in summer, low sidein winter). The team reviewed historical data for the past five years and selected tempera-tures which would have provided an appropriate number of critical peak events in at leastfour of the past five years. A conservative approach was taken in selecting the triggertemperatures because, if the threshold is exceeded too many times, events need not becalled (whereas if not enough events occur, insufficient data will be available for analy-sis). The trigger temperatures selected were 28°C in summer and -14°C in winter. In addi-tion, events would be called when the Humidex exceeds 30°C during On-Peak times ofthe day, regardless of the temperature.

- Critical Peak Rebate (CPR) pricing structure. In contrast to the CPP, the CPR provides arefund to participants for reductions below their “baseline” usage during the critical peakhours. To strive for revenue neutrality, the rebate amount was set to be the same as theCritical Peak Price during critical peak hours. Also, since the incentive during the criticalpeak hours is a rebate, there is no adjustment in the Off-Peak price. A participant makingno change in response to the critical peak events will pay the same bill on TOU plus CPRas they would if they were a participant on TOU-only prices. The existing RPP TOUprices and hours were used during the pilot. As for CPP above, Critical Peak rebates werein effect only when critical events were declared, a maximum of nine events were plannedduring the pilot and only for three or four hours during On-Peak hours.

Baseline Determination

For a participant to receive a rebate, their consumption had to be below a baseline. Thismeans that the higher the baseline, the easier it is for a participant to earn a rebate (i.e. use anamount of electricity less than the baseline amount).The baseline methodology was developedby reviewing other baseline methodologies used for other residential CPR programs, as wellas baselines used for large commercial consumer curtailable programs. Baseline methods con-sidered were the following:

- PJM Interconnections: Usage for the same hours in the three highest of the ten previousnon-event, non-holiday weekdays

- New York Independent System Operator: Five highest of the ten previous non-event, non-holiday weekdays

- Anaheim Public Utilities: Three highest non-event, non-holiday weekdays in the first halfof summer

- PowerCentsDC pilot in Washington D.C.: Three highest non-event, non-holiday week-days in the previous month 6 - See Appendix A, Analysis of Critical Peak Rebate ProgramConcept.


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- San Diego Gas & Electric (SDG&E): Average of previous five non-event, non-holidayweekdays The SDG&E approach is the most recently developed and was based on a de-tailed analysis of residential consumer data. Its advantage is its computational simplicity.However, because critical days are, by definition, the most extreme, SDG&E’s baselineapproach understates what the consumer would have otherwise used on critical days. Thisartificially low baseline means that a customer would have to reduce peak consumption oncritical days just to reach the baseline level — then further reduce consumption to earn arebate (and certainly resulting in consumer frustration). The team analyzed data for 2005from a similar Anaheim TOU pilot and determined that, on average, usage of controlgroup consumers during critical peak periods was 23% higher than their average usageduring the same hours of the five previous non-event, non-holiday weekdays. In otherwords, this data showed that the starting point for determining a load reduction should be23% above the five-day average, giving the customer a greater (and appropriate) opportu-nity to earn a rebate. Based on this analysis, a rounded-off adjustment factor of 25% wasused for the OSPP. The OSPP baseline approach gains the benefits of the San Diegomethod while using the adjustment factor to remove the inherent customer penalty. Theresult is a baseline that is calculated as the average usage for the same hours of the fiveprevious non-event, non-holiday weekdays, multiplied by 125%. The difference betweenthe consumer’s consumption during the Critical Event and the baseline would be subjectto the CPR, creating a rebate of 30 ¢/kWh times the amount by which the participant’s us-age was reduced.

Control group

The conventional meter RPP has prices in two tiers, one price for monthly consumption undera tier threshold and a higher price for consumption over the threshold. The thresholds for resi-dential consumers vary by season:

- 600 kWh per month during the summer season (May 1 to October 31).

- 1000 kWh per month during the winter season (November 1 to April 30).

The two-tiered RPP prices in effect during the pilot period were applied to all control groupcustomers.

Customer participation

Candidate participants were randomly selected from the population that would have smartmeters installed in Hydro Ottawa’s territory by August 1, 2006. The experimental design wasa classic side-by-side comparison of control group versus treatment groups. Participants wererecruited for the three treatment options:

- Time-of-use (TOU) only

- TOU plus Critical Peak Pricing (CPP)


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- TOU plus Critical Peak Rebate (CPR)

Participants were segregated by price structure. The participants were recruited independentlyand had no knowledge of the price structures offered to other customers.

Participants were recruited using a stratified random sample to ensure that a sufficient numberof participants were in each of the low, medium, and high monthly consumption groups. Re-cruitment was undertaken via direct mail, using a letter co-branded by Hydro Ottawa and theOEB. (Subsequent pilot communications were branded as OEB communications.) The initialletter notified customers that they “have been selected as a participant.” However, customerswere not included in the pilot unless they returned the confirmation form included in the re-cruitment mailing. One reason confirmation was needed was to provide the correct telephonenumber or email address for critical peak event notifications.

The control group was a sample of 125 customers selected randomly from the population ofHydro Ottawa residential customers who had smart meters installed prior to the August 1,2006 start of the pilot but continued to pay tiered (non-TOU) prices.

All treatment and control participants were RPP consumers (i.e., not on a retailer contract).

Operational details of the pilot

The recruitment packages consisted of the following:

- Cover Letter: Provides a brief introduction to the pilot, describes key features, and informseligible participants how to confirm participation.

- Fact Sheet: Provides an explanation of all the key features of the pilot, shows the specificTOU prices, provides a sample of the monthly electricity usage statement to be receivedby participants, and provides a sample of the final settlement that will be provided to par-ticipants.

- Confirmation Form: When signed, this form confirms the customer’s participation andprovides needed authorization for pilot data handling and analysis. There are three ver-sions of the Letter and Fact Sheet; one per price design group. All materials are providedin both English and French.

Initial participant education

Beyond the material in the recruitment package, focused on a package mailed to each eligibleparticipant following receipt of their enrolment form. This confirmation mailing included thefollowing:


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- Cover Letter: Confirms that the participant is enrolled.

- Refrigerator magnet: Provides a table of the prices, times, and seasons for the participant’sprice plan. The magnet to be sent is an adaptation of a design that was preferred by cus-tomers in focus groups conducted for a different pilot program by Hydro Ottawa

- Electricity conservation brochure: This PowerWise brochure provides a variety of conser-vation tips for electricity consumers that may be used during peak times or anytime.

Incentive Approach

As an incentive to enrol, participants received a “thank you payment” of $75 at the end of thepilot. Specifically, $50 was provided as an incentive for remaining on the pilot for the full pe-riod and $25 was provided for completing the pilot survey. Such an incentive is consistentwith incentive payments of $75 to $100 made in similar pilots. Numerous researchers haveconcluded that the incentive does not present an issue when analyzing the effect of prices onpilot participants. The reason is that the incentive payment is a fixed externality; participantsreceive credit for the $75 simply by participating. Any savings or losses on their time-basedpilot prices do not change the fact that they will receive the incentive payment, beyond reduc-ing or increasing it.

Demand Response Results

The analysis of demand response or peak shifting as a result of the pilot prices was performedby Professor Frank Wolak of the Economics Department of Stanford University.

The analysis was performed to assess the following:

- Demand response via load shifting away from critical peak hours to either Mid-Peak orOff-Peak hours on critical peak days

- Demand response via load shifting away from On-Peak hours to either Mid-Peak or Off-Peak hours on all non-holiday weekdays

These effects were determined by comparing the electricity consumption behaviour of cus-tomers receiving the experimental prices (TOU, CPP, and CPR) and the behaviour of custom-ers remaining on their existing two-tier RPP prices. These customer groups are the treatmentand control groups respectively.


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There was clear evidence of load shifting on individual critical peak days for CPP and CPRprice groups. The statistical significance of the results shows less evidence in the case of TOUprice groups.

Load shifting away from the On-Peak period for all days in the pilot, not just critical peakdays, was also analyzed. These results showed no applicable statistically significant loadshifting from On-Peak periods as a result of the TOU price structure alone.

The analysis compared the usage of the treatment and control groups before the pilot, thenafter going on the pilot. These results show a 6.0% average conservation effect across all cus-tomers. All of the results are statistically significant.

Total Load Shift Impacts The impacts on bills were determined by calculating each individualparticipant’s bills during the pilot under the TOU prices versus the two-tiered RPP prices.Thus, any bill savings is entirely a result of load shifting. Conservation effects which lower aparticipant’s usage compared to what it would have been without TOU prices are not consid-ered in these results. Over the course of the entire pilot period, on average, participants shiftedload and paid 3.0% lower bills on the TOU pilot prices than they would have on regular tieredRPP price. Savings were spread across participants with three quarters of participants payingless on the TOU prices. Since only seven critical peak days were declared against a target ofnine, CPP participants realized savings that were somewhat overstated. Conversely, CPR par-ticipants realized lower rebates during the pilot for the same reason.

Participant feedback was gained from two primary methods:

- Three focus groups with 44 participants were conducted in Ottawa during the secondweek of October; one group each for CPP, CPR, and TOU participants.

- A survey of the program participants was conducted. A total of 298 surveys were returnedby the survey cut-off date of December 14, 2006, for an overall response rate of 79%. Themargin of error (at 95% confidence) for the overall results is ± 5.7% for the 298 surveysreceived.

The majority (78%) of survey respondents would recommend the time-of-use pricing plan totheir friends, while only 6% would definitely not. These results are consistent regardless ofwhich pricing plan the participants were enrolled in for the pilot.

Respondents most frequently cited more awareness of how to reduce their bill, giving greatercontrol over their electricity costs and environmental benefits as the top three reasons behindthe satisfaction. Those not sure or who would not recommend the program cited insufficientpotential savings and too much effort as the reasons why. Pricing preferences Regardless ofthe pricing plan in which they were enrolled, the majority of participants (74%) preferredTOU-only pricing out of the four options. While interest in the CPP and CPR plans was onlymoderate, less than 20% prefer the existing two-tier threshold pricing used by Hydro Ottawabefore the pilot. Most would not want to go back to two-tier pricing.

The impact on individual bills seemed to be less than many focus group participants hadhoped. Few of the focus group participants felt they had realized “large” savings on their elec-tricity bills. In fact, many focus group participants expressed disappointment that their effortsdid not result in greater savings


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Participants in the focus groups and survey respondents particularly valued the monthly usagestatement and refrigerator magnet as the most useful resources to help understand the TOUprices, overshadowing the fact sheet, brochure, or any other pilot communications materials.

There was a consensus among focus group participants that bi-monthly billing frequency wasnot adequate within the context of smart meters and TOU pricing. Nearly 70% of survey re-sponses did indicate that they anticipate accessing an online statement at least monthly.

4.10 ISO-New England demand response programs

4.10.1 Real-Time Demand Response program (Capacity market)

This program is included in the capacity market mechanism.

Program Feature Description

Eligible RetailCustomers

Individual or Groups (Minimum 100 kW Reduction).

Program Activa-tion

Respond to ISO Control Room Request.

Required Re-sponse

Time Within 30-Minutes or 2-Hours of ISO request.

Energy Payment Greater of Real-Time LMP or Guaranteed Minimum $0.50/kWh for 30-MinuteResponse and $0.35/kWh for 2-Hour Response.

Capacity Payment Monthly payment ($/kW) based on the ICAP Supply Auction and/or SupplementalCapacity Agreement.

Minimum EventDuration

Minimum 2-Hour guaranteed interruption.

Metering Re- 5-Minute Usage data sent to ISO-NE via the Internet (open architecture system,


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quirement IBCS OS) or customized monitoring and verification plan.

On average, the size of consumers participating in this program is 2MW.

On average, the customers actually curtailed 90% of the announced curtailment for the 2-hours response program and 82% or 71% for the 30-minute response program depending ifthey had some emergency generation installed or not.

4.10.2 Real-Time Price Response Program (CPP)

Program Feature Description

Eligible RetailCustomers

Individual or Groups (Minimum 100 kW Reduction).

Program Activa-tion

Notified by ISO-NE that wholesale prices are forecasted to exceed $0.10/kWheither the night before or morning of the event day (by email).

Required Re-sponse Time

The program is 100% voluntary. Participating retail customers decide when andfor how long they participate.

Energy Payment Greater of Real-Time LMP or Guaranteed Minimum of $0.10/kWh.

Capacity Pay-ment

None

Minimum EventDuration

Price response “window” can open as early as 7AM and remains open until 6PM.

Metering Re-quirement

The minimum requirement is a meter capable of recording a retail customer’shourly usage. Customized Monitoring and Verification plans can also be consid-ered.

On average, the size of consumers participating in this program is 300kW.

On average, the customers actually curtailed 30% of their announced capacity.


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ISO-NE estimates that the benefits of this program exceed the costs by about 80%. They es-timated the costs based on how much total bill savings are obtained on the wholesale marketdue to the price change as well as on how much savings commodity suppliers can make bydemanding lower rates on their hedging contracts.

4.10.3 Day-Ahead Load Response Program (Demand side bidding)

Demand Side Bidding into the day-ahead wholesale market for participants already enrolledin the Real-Time Demand Response Program. The minimum bet size is 100kW. Participantswhose offer is accepted is not required to participate to the Real-Time DR program for thevolume of energy accepted in the day-ahead market. This is done to avoid paying the sameenergy twice.

4.11 PJM Interconnection demand response programs

PJM Interconnection operates a large part of the North-East of the USA, serving nearly 20%of the US economy. After pilot projects in 2000, they decided to implement an EmergencyLoad Response Program while a temporary Economic Load Response Program was set. In2008, this Economic program became permanent. In 2006, PJM offered the possibility toLoad Serving Entities (LSE) to place bids on the synchronized reserve market and on theregulation market.

Qualified PJM market participants who act as agents, called Curtailment Service Providers(CSPs), work with retail customers who wish to participate in demand response. CSPs aggre-gate the demand of retail customers, register that demand with PJM, submit the verification ofdemand reductions for payment by PJM and receive the payment from PJM. The allocation ofthe payment from PJM to the CSP and the retail customer is a matter of private agreement be-tween them.

In the end of 2007, 4898 sites (2944MW) were registered in the economic load response pro-gram and 705 sites (2144MW) were in the emergency load response program. During a heatwave in early August 2006, PJM estimates that the use of demand response produced a pricereduction of about $650 million.

4.11.1 Economic Load Response program (RTP)

This program is a typical real-time pricing program as described in this report. The consum-ers, through their CSP, can decide to reduce their consumption at times of high LocationalMarket Price (LMP). They can either announce the reduction on a day-ahead basis or they canreact in real-time. For those reductions, they received a payment based on the day-ahead orreal-time LMP respectively. The real-time option allows consumers who would have placed abit on the day-ahead market to bid their reduction again.

There was an additional incentive for demand participation. On 22nd October 2007, the capfor the incentive has been reached and load reductions after that day do not receive incentivesanymore. The price paid to the participants. The issues arising when the incentives were de-signed were to determine how they should be distributed among the participants and whenshould the incentives be stopped. The choices made by PJM were to distribute the incentives


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in the same way if consumers reduce their load on the day-ahead or real-time markets and tostop the incentive system after $17,5 million have been paid.

4.11.2 Emergency Load Response program (Capacity market)

Loads can register as interruptible load for reliability. In that case, they place bids on the for-ward (months ahead) capacity market. Such loads must accept to be called in cases of limitedcapacity. The size of a bid has a minimum of 1MW and the load must be available during 5hours given a day-ahead notification. The accepted bids will be paid at the highest of the av-erage LMP and the value specified in the bid. In addition, a premium is also paid for the re-source to be on stand-by.

4.11.3 Ancillary services market

PJM allows loads to participate in the synchronized reserve market as well as in the regulationmarket. Demand resources willing to participate in these markets must fulfill all the require-ments that other resources have. That includes the need of one-minute interval metering andreal-time telemetry.

4.12 ERCOT Demand response programs (Balancing and ancillaryservices)

The Electric Reliability Council of Texas (ERCOT) is the Independent System Operator forthe State of Texas. It is a non-profit corporation regulated by the Public Utility Commissionof Texas. The energy in Texas is contracted bilaterally, thus ERCOT doesn't operate anywholesale power market. It is however in charge of the ancillary services and balancing mar-kets.

Balancing up loads

The Balancing Up Loads (BUL) are contacted by ERCOT, although the BUL contract is donewith their retailer or their QSE (equivalent of a balance responsible party), in association withthe Balancing Energy market.

A BUL must be dispatchable within 10 minutes and have real-time telemetry in place.

If dispatched BULs receive both an energy payment, based on the Market Clearing Price forEnergy, and a capacity payment, based on the Market Clearing Price for Capacity. The pay-ment is made to the QSE who may flow it through to the retailer who may, in turn, share itwith the consumer.

Voluntary Load Response

ERCOT includes in these all the loads responding to price signals defined by the different re-tailers.

Load Acting as a Resource


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This program allows loads to provide various ancillary services in the same way as other re-sources can. The services that can be offered, along with their main characteristics are showedin the following table.

1OOMC and OOME were emergency response services offered in 2004

4.13 The Olympic Peninsula project (Aggregator, RTP, DLC)

The Olympic Peninsula was suggested by BPA as an ideal location for the field demonstrationof the Gridwise concept. The Peninsula is served by a capacity-constrained, radial transmis-sion system. The area is experiencing significant population growth, and it already has beenprojected that power-transmission capacity in the region may be inadequate to supply demandduring extremely cold winter conditions.

The Olympic Peninsula Project was undertaken to demonstrate steps in realizing the value oftransforming passive end-use loads and distributed generation into active, market-driven re-sources for power-grid management as well as the practicality of reducing the market clearingtime of this process to intervals as short as 5 minutes.

The project’s market was operated at a 5-minute interval to allow the cycling behaviour ofload to contribute to load reduction and load recovery. The duty cycle of most appliances,even on peak, is usually sufficiently diverse to allow a load-control signal, such as price, totake advantage of the fact that turn on and off anyway. By adjusting when and how long loadsturn on or off, a great deal of flexibility can be achieved to the benefit of the entire system.

Project resources

Three electric power providers, Public Utility District (PUD) of Clallam County, the City ofPort Angeles, and Portland General Electric, provided the Olympic Peninsula Project withresidential, commercial, and municipal test sites. Several other collaborators, specificallyIBM’s Watson Research Laboratory and Invesys Control provided equipment, software, andvaluable in-kind project support. Whirlpool Corporation participated by augmenting the con-


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trols on project clothes dryers so they would announce high price conditions on their frontpanels.

Planning for the field demonstration began in late 2004. Equipment was being placed in thefield by late 2005, and data were collected from early 2006 through March 2007.

The project included the following controllable assets that were enabled to respond to the pro-ject’s energy price signals:

- Five 40-HP water pumps, distributed between two municipal water-pumping stations, rep-resenting a nameplate total load of about 150 kW – The electrical load these pumps placedon the grid was bid into the market incrementally when water-reservoir levels were abovea designated height.

- Two distributed diesel generator – These two generators (175 and 600 kW) serve the facil-ity’s electrical load when feeder supply was insufficient. The biddable resource capacityin this case was the removal of the building electric load (170 kW) removed from the gridby transferring it to these units. In addition, a small 30-kW microturbine was set up to re-spond to the two-way market. Unlike the larger generators, the microturbine ran in parallelwith the power grid. The market prices offered for the supply of these generators unitswere based on the actual fixed and variable expenses incurred.

- Residential demand response for electric water and space heating provided by 112 homesusing gateways that supported two-way communication –This residential demand-response system allowed current market prices to be presented to consumers and allowedusers to preprogram their automatic demand-response preferences. The residential partici-pants were evenly divided among three types of utility price contracts (fixed, time of use,and real time) and a control group.

While all residential electricity was metered, only the appliances in price responsive homes(75kW) were controlled by the project.

Automation was provided by the project to monitor, and in some cases control, each of theseresources. Consistent with GridWise principles, all participants and resource operators wereprovided means to temporarily disable or override project control of their loads or generators.In the cases of residential thermostats and water heaters, appliance owners were providedmeans to assign a degree of price responsiveness to their appliances from among lists of 5 to15 intuitively named comfort settings. In the cases of commercial and municipal resources,the degree of automated price-responsiveness was negotiated with each resource owner.

While not all resources could be co-located on one feeder for this demonstration, the meas-urement and control of these resources were conducted as if all resided on a common virtualfeeder. Throughout the project, these project resources were monitored online at PNNL usingdistributed energy resource (DER) dashboards as shown in the figure below. This examplewould show a grid operator how much of a resource is available and how much has alreadybeen dispatched. These dashboards allowed project staff to quickly assess the status of thesystem and its individual resource components. Visualization tools of this type will be criticalfor grid operators to achieve the widespread adoption of distribution resources.


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Figure 6. Example Utility Dashboard

The central organizing element of the Project was a shadow market to provide the incentivesignal that encouraged operation of the project’s distributed generation (DG) and demand-response resources to manage local distribution congestion. The project created debit accountswith balances of actual money that were used to cover the shadow market electricity shavingsearned by the residential customers. The amount of cash they earned and received dependedon whether they were operating their household loads in collaboration with the needs of thegrid each month. As these customers responded to price signals sent from the shadow market,the cash balances in their debit accounts were reduced at a rate commensurate with theshadow market’s current energy prices for the given market interval. The participants got tokeep any money left in the account at the end of each quarter. The project received guidancefrom BPA to recommend reasonable values for these incentives with limited project budget inmind. Participating homes’ energy consumption histories were also studied before the ex-periment to establish baseline expectations.

Project results

Distribution Constraint Managed. Seasonally, the project imposed a new constraint on theenergy that could be imported into the feeder from an external wholesale electricity source.The project then controlled the imported capacity below this constraint for all but one 5-minute interval during the entire project year. The duration of feeder capacity was success-fully limited to 750 kW. Distributed generators provided additional supply (up to about 350kW at its peak) when needed.


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Market-Based Control Demonstrated. The project controlled both heating and cooling loads.Observation of the project’s residential thermostatically controlled loads for those homes onreal-time price contracts revealed a significant shift in energy consumption. Space-conditioning loads served by the real-time price contracts effectively used energy in the veryearly morning hours when electricity is least expensive. This effect occurred during both con-strained and unconstrained feeder condition; however, it was more pronounced when thefeeder was constrained. This result is remarkably similar to what one would expect for pre-heating or pre-cooling, but these project thermostats had no explicit prediction capability. It isthe diurnal shape of the price signal itself that caused this outcome.

Peak Load Reduce. The project’s market also deferred and shifted peak load. Unlike time-of-use control, the project’s real-time control operated exactly when needed and with the precisemagnitude needed. The magnitude of load reduction under real-time price control increaseswith the peak itself and with the degree to which the feeder import is constrained. The projectconservatively estimated that a 5 percent reduction in peak load was achieved under a 750 kWconstraint, 20 percent peak load reduction was easily obtained under a 500 kW feeder con-straint.

Internet-Based Control Tested. The project implemented Internet control of its distributedresources through the efforts of project collaborators Invensys Controls and IBM Watson Re-search Laboratory. Bid and control interactions were communicated via the Internet. Residen-tial thermostats, for example, modified their effective temperature setbacks through a combi-nation of local and central controls communicated over the internet. The project market itselfwas cleared centrally every 5 minutes. While average project connectivity to these resourceswas at times sporadic, the resources almost always performed well in default modes unitcommunications could become re-established.

Distributed Generation Served as a Valuable Resource. The project was particularly suc-cessful obtaining useful supply form distributed diesel generators. The project elected to con-trol the generators at their existing emergency-transfer switches. The generators and their pro-tected facilities therefore ran separated, or islanded, from the grid. These generators bid thecapacity of the commercial building loads they served; the price they offered was based onactual fixed and variable expenses they would incur by turning on and running. These re-sources were called upon and used many times during the project. The diesel generators wererestricted by their environmental licensing to operate no more than about 100 hours per year.This constraint was easily managed by imposing and managing a price premium applied toevery market offer made by these resources. Note that many such emergency backup genera-tors lie unused in the United States.

4.14 US survey of utility experience with RTP

This chapter is a short overview of a survey, conducted by the Lawrence Berkeley NationalLaboratory, of 43 voluntary RTP tariffs offered in the USA in 2003 [16]. Most of them, andthus the conclusions hereunder, concern programs offered to large consumers.

Motivation of the utilities

The first result regards the motivation for utilities behind proposing RTP tariffs. According tointerview with the utilities' managers, the main driver is to build customer satisfaction and


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loyalty by offering lower bills. The other drivers are to encourage load shifting, load growthand to comply with a statutory or regulatory obligation.

Evolution of the tariffs

The second result is an observation of the evolution of the RTP tariffs offer through time. Theoffer progressed from day-ahead to two-part RTP systems where the tariffs are based on abase load profile and only the deviations from it are charged at the retail market price. Thebase load is charged at a predetermined price. In this way, the consumer can mitigate the riskdue to price volatility, but still value its load reduction fully.

Participation

The participation in the surveyed programs was quite low. Only three programs actually hadcontracted more than 500MW in 2003. Some of the identified reasons are a lack of proactiveadvertising, little assistance or insurance against exposure to high volatility and a limited pro-gram access for large loads. In addition, the participation has declined in the years preceding2003. The interviewed utilities attribute this to the fact that some consumers were wishing tomake savings without having to react actively to the price signals and that the increase involatility prices made it impossible.

The programs registering a good participation rate were proposing fixed tariffs for a baseload, but they also offered other risk protections such as a price cap or a price collar. It seemsimportant, in order to keep the consumers into an RTP program, to offer risk managementtools.

Georgia Power

The Georgia Power RTP programs are among the few studies in this US survey that managedto attract and keep customers successfully. It offers four different RTP options as well as threeprice protection products.

- RTP-DA-2: Two-part real time pricing with day-ahead notification. The base load is de-veloped from one complete calendar year of either customer-specific hourly firm load dataor monthly billing determinant data that represents the electricity consumption pattern andlevel agreed to by the customer and Georgia Power. Any deviation from this base load isbilled at the RTP-DA-2 hourly price. For customers with New Load, the CBL will initiallybe based on 100% of a Commercial customer’s total projected load or 60% or greater ofan Industrial customer’s total projected load. A new Commercial or Industrial customercan establish a CBL less than its projected level provided that the customer can Demon-strate its desired CBL level or the CBL is based on a Footprint.

- RTP-HA-2: The same as the RTP-DA-2, but the price notification takes place one hourbefore the power delivery. However, a day-ahead forecast of the prices is sent to the cus-tomers beforehand.

- RTP-DAA-2 and RTP-HAA-2: Similar to the two first products, but the base load can beadjusted by the consumer for a period of time. The customer’s original baseline load(CBL) is developed under the terms and conditions of the RTP-DA or RTP-HA tariff.Once the customer switches to RTP-HAA, the customer may select to raise or lower the


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original CBL for a contract period specified by the Company. Forecasted RTP prices willapply to the difference between the original CBL and the adjusted CBL. Actual RTPprices will then apply to differences between the customer’s actual load and the adjustedCBL. RTP credits will be given for load reductions below the customer’s adjusted CBL.

While being in any of these programs, the consumers can also contract some price protectionproducts. They are risk management tools that allow the consumer to protect himself from theRTP volatility.

- Price cap: The consumers are guaranteed that the average price over a specific time periodwill not exceed a certain price cap. Customers pay an upfront payment for the guarantee.

- Contract for Differences (CfD): The average RTP price over a determined period of timeis here fixed. No upfront payment is required.

- Price collar: The RTP price is limited by a cap and a floor price. Customers are guaranteedthat the prices will not exceed the price cap. No upfront payment is required.

4.15 US survey of household response to dynamic pricing of electric-ity

Ahmad Faruqui and Sanem Sergici of the Brattle group realized a survey of 14 pricing ex-periments [25] throughout the US (some of which are presented in this document). We don'tgo through the detail of the survey, but we present here the main conclusions.The first result is a table showing the realized reductions of peak consumption depending onthe type of tariff. There are considered Time of Use tariffs and Critical Peak Pricing with orwithout enabling technology. Peak Time Rebate are here showed as a separate category.

Rate DesignNumber of obser-

vations Mean95% Lower

Bound95% Upper

Bound Min Max

TOU 5 4 % 3 % 6 % 2 % 6 %

TOU w/ Technology 4 26 % 21 % 30 % 21 % 32 %

PTR 3 13 % 8 % 18 % 9 % 18 %

CPP 8 17 % 13 % 20 % 12 % 25 %

CPP w/ Technology 8 36 % 27 % 44 % 16 % 51 %

The second interesting result is an extrapolation of how much the load reduction varies ac-cording to the peak price. the extrapolation is based on the California SPP experiment (seechapter 3.8) and a price impact simulation model that was developed in that experiment. Thefollowing figure shows that the reduction is not linear, but also that very high prices are notnecessary to encourage demand response. The distinction is made here between consumerswith or without Central Air Conditioning (CAC)


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5 Conclusions

Power producers

The main reason why producers make use of demand response is to improve their balance.This aspect is covered hereafter in the Balance Responsible Party (BRP) chapter. Indeed, pro-ducers are often also BRPs and when they are not, their BRP typically imposes them somebalancing requirements.

Retailers

Retailers are most often directly related to active demand. They often also take the role ofBRP described further. The retailing activity has however an interest in demand response inthe sense that it offers them to diversify their portfolio with new services, to reduce theirprices and to hedge the risks. Active demand can be used to replace to some extent costlycombustion units and can thus reduce the costs and make their business more attractive.

A retailer strictly limited to retailing activities would be more interested in price-based DSI,sometimes with some degree of direct-load control. The other options would involve thembeing between the consumers and another actor and would make of them demand aggregators,discussed later.

Network operators

Network operators are regulated participants in charge of the good operation of the distribu-tion and/or transmission networks. The main reasons why network operators use active de-mand are either to reduce the network management or network upgrade costs, to follow someregulatory obligations or, in the case of system operators, to maintain the balance and the se-curity of the whole system. They can offer price based tariffs on the network charges and canalso encourage active demand to participate to emergency, capacity and ancillary servicesmarkets.

Price-based DSI can offer them constant peak shaving throughout the year or an increasedeffect in critical situations. When network operators call on other active demand resources,these resources have to fulfil the requirements imposed to the other participants and an impor-tant issue is that the demand reduction must be reliable. It is seen in the existing experiencesthat demand response at small consumers' premises is often unreliable or overestimated andthat the realized load reduction is smaller than what was planned and contracted.

Balancing Responsible Parties

BRPs are responsible for maintaining their balance. They can be interested in using demandresponse as a mean to reduce their imbalances. The two main options for them are to installdirect load control at the consumers' premises or to include an aggregator's operation to a bal-ancing energy market.

BRPs also need quickly reacting and reliable resources and, as discussed above, active de-mand at small consumers' premises is often viewed as unreliable.


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Consumers

From the experiences, small consumers are ready and willing to participate to active demand.What they need is it to be easy to manage, with as little loss of comfort as possible and with aclear feedback on their savings.

ToU tariffs are very well accepted where they are used and consumers have been seen tochange their electricity usage due to them. Typical responses are the shifting of "white goods"use or the use of water or space heating or cooling systems with heat storing capabilities inoff-peak times.

Real-time pricing is often used in the same way as ToU tariffs if no automation is installed,but consumers change their electricity utilization in situations of high prices. This effect ishowever seen mainly when they receive an active signal (by phone, email or a clear signal attheir home) that a high price situation is coming. Small consumers shouldn't be expected tocheck the prices every day for the morrow.

In the other cases, when a faster response is expected, small consumers are most often directlycontrolled. In this situation, they need to have an overriding option.

Aggregators

The aggregator is a relay between a large number of consumers and one or several other ac-tors. It can also be a retailer or a BRP using active demand to offer services to other actorssuch as network operators or other BRPs.

In order to fulfil the needs of network operators and BRPs, an aggregator should be able tooffer fast responding and reliable demand reductions. The fast response can most easily beobtained by direct load control of some consumers' appliances, but the reliability is jeopard-ized by the fact that not all the controllable loads are consuming and controllable at the sametime and by the overriding option that the consumers need. A solution for this can be for theaggregator to better estimate its available power.

Another obstacle for the development of the aggregator concept is that the actors requiring theconsumption change want a reliable verification that the service has been provided. The refer-ence load without active demand actions should be defined in a clear way so that the actualconsumption can be compared to it to determine the delivery of the service.

We have found some examples of working aggregators but most often, because they are com-petitive actors, very little information is publicly available about them.


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6 References

[1] C.W. Gellings, J.H. Chamberlin, “Demand-Side Management: Concepts and Meth-ods”, (Fairmont Press, Liburn, USA, 1993, pp. 238-240)

[2] S. Talukdar, C.W. Gellings, "Load Management" (IEEE Press, New York, 1987)

[3] C.W. Gellings, J.H. Chamberlin, "Demand-side Management Planning" (FairmontPress, 1993)

[4] A. Baitch, A. Chuang, G. Mauri, C. Schwaegerl, “International Perspectives onDemand-side Integration” (Proceedings of the 19th International Conference onElectricity Distribution. (CIRED), Vienna, May 21-24, 2007)

[5] Chuang A. Gellings C. W., Demand-Side Integration in a Restructured ElectricPower Industry", CIGRE Session 2008, Paris Paper C6-105.

[6] "Benefits of Demand Response in Electricity Markets and Recommendations forachieving them". A report to the United States Congress. February 2006, 122 p.

[7] "The Power to Choose. Demand Response in Liberalised Electricity Market".OECD/IEA books 2003. 151 p.

[8] Federal Energy Regulatory Commission, “Assessment of Demand Response & Ad-vanced Metering”, Staff Report Docket Number: AD-06-2-000, August 2006, 228p.

[9] Federal Energy Regulatory Commission, “2008 Assessment of Demand Response& Advanced Metering”, Staff Report, December 2008, 139 p.

[10] IEA DSM, Task VIII. Market participants’ views towards and experiences withDemand Side Bidding, January 2002

[11] IEA DSM, Task VIII. Evaluation of existing Demand Side Bidding Schemes, Stage2 Final report, February 2003

[12] IEA DSM, Task VIII. The consumer potential for DSB: National Reports forFinland, Greece, Netherlands, Norway, Spain, Sweden and the UK, June 2002

[13] IEA DSM, Task VIII. Sub-task 4 Report,Technologies for Demand Side Bidding,October 2001

[14] IEA DSM, Task VIII. A Practical Guide to Demand Side Bidding, 2003

[15] O.S. Grande, H. Saele, I. Graabak, Market Based Demand Response Research Pro-ject summary, December 2008

[16] A Survey of Utility Experience with Real Time Pricinghttp://repositories.cdlib.org/lbnl/LBNL-54238/

http://repositories.cdlib.org/lbnl/LBNL-54238/


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[17] CNT Energy, 2005 Evaluation of the Energy-Smart Pricing PlanSMhttp://www.cntenergy.org/real-time-electricity-pricing.php

[18] National Grid, Report on the Demand Turndown Trials, March 2006http://www.nationalgrid.com/uk/Electricity/Balancing/demandside/supportingactivities/

[19] G. Heffner, A Critical Examination of ISO-Sponsored Demand Response Programs,August 2005. http://www.fscgroup.com/news/FSC_DRWhitePaperHeffner.pdf

[20] K. Herter, Residential implementation of critical-peak pricing of electricity, Sep-tember 2006 http://ideas.repec.org/a/eee/enepol/v35y2007i4p2121-2130.html

[21] Ontario Energy Board. Ontario Energy Board Smart Price Pilot Final Report. July2007.

[22] Price Waterhouse Coopers. Review of Phase One of the Demand Response Pro-gram. March 30th, 2007.

[23] Hammerstrom, D. J. et al. 2007 Pacific Northwest GridWise Testbed. Demonstra-tion projects. Part I. The Olympic Peninsula project. October 2007.

[24] M.A. Piette et al., Automated Critical Peak Pricing Field Tests: Program Descrip-tion and Results, April 2006. http://drrc.lbl.gov/pubs/59351.pdf

[25] A. Faruqui and S. Sergici, Household Response to Dynamic Pricing of Electricity –A Survey of the Experimental Evidence, January 2009http://papers.ssrn.com/sol3/papers.cfm?abstract_id=11341

http://www.cntenergy.org/real-time-electricity-pricing.php

http://www.nationalgrid.com/uk/Electricity/Balancing/demandside/supportingactivi

http://www.fscgroup.com/news/FSC_DRWhitePaperHeffner.pdf

http://ideas.repec.org/a/eee/enepol/v35y2007i4p2121-2130.html

http://drrc.lbl.gov/pubs/59351.pdf

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=11341

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