RESIDENTIAL ELECTRICITY DEMAND: A ROADMAP OF MAIN FACTORS

RESIDENTIAL ELECTRICITY DEMAND: A ROADMAP OF MAIN FACTORS INFLUENCING CUSTOMERS CONSUMPTION

Brzakowski F., Entem M.,Saplacan R.

September 2009

Summary1. Introduction

2. From Price Elasticity studies to Demand Response (DR) programs: general contextualisation

1. Price elasticity literature and application in the actual context: from tariffs to DR programs

2. Definition and classification of DR programs

3. DR benefits and costs: analysis

1. DR Benefits

2. DR Costs

3. Customer Behaviour: a key element for the success of DR programs

1. Pilot experiences

2. Analysing consumer’s behaviour

4. Conclusions: a critical assessment1. DR: two different approaches, two types of customer behaviour

Introduction

With the restructuring and deregulation of the electricity supply industry, the philosophy of operating the system was also changed. The traditional approach was to supply all power demands whenever they occurred, however, the new philosophy states that the system will be most efficient if fluctuations in demand are kept as small as possible…. This paper presents an overview of new flexible resources for operating a reliable system.

The paper starts with an overview of price elasticity studies, continues by defining the Demand Response (DR) programs, analysing their expected benefits, but also highlighting their actual costs

The paper next discusses how electricity consumers can be responsive. The focus is on residential electricity demand, examining several pilot experiences

We conclude by assessing the results of the studied pilot experiences with DR programs

2. From Price Elasticity studies to Demand Response (DR) programs: general contextualisation

2.1 Price elasticity literature and application in the actual context: from tariffs to DR programs

Economic studies traditionally point out socioeconomic determinants of electricity demand considered in the framework of a utility-maximising household (Engsted and Bentzen, 1993; Espey and Espey, 2004; Salies, 2008)

Estimates of the short run electricity price elasticity of demand reported in the literature range from –2.01 to 0.076, which is recognised as a confusing range of empirical estimates of price and income elasticities

Any price change would require accurate values of consumer response to it � estimation of the energy conservation amount of newly introduced electricity rates � estimating the demand response to changes in price, income, etc.

2.2 Definition and classification of DR programs

Definition:All intentional electricity

consumption pattern modifications by end-use customers, that are intended to alter the timing, level of instantaneous demand, or total electricity consumption (IAE, 2003)

DR Programs1. Incentive Based Programs (IBP)1. Classical (control & penalties)

1. Direct Control

2. Interruptible/Curtailable Program

2. Market Based (rewards)

1. Demand Bidding (< market px)

2. Emergency DR

3. Capacity Market (day-ahead commitment)

4. Ancillary Service Market (spot market commitment as operating reserves)

2.Price Based Programs (PBP) = dynamic pricing rates following the real time cost of electricity

1. Time of Use (TOU)

2. Critical Peak Pricing (CPP)

3. Extreme Day CPP (ED-CPP)

4. Extreme Day Pricing (EDP)

5. Real Time Pricing (RTP)

2.3 DR benefits and costs: an analysis (1/2)DR expected benefits1. – Consumer

1. 1. Incentive payments

2. 2. Bill savings

3. 3. Possibility to choose

2. – Retailer (Program owner)

1. 1. New market segments

2. 2. Reduced Sourcing Cash

3. – Market wide

1. 1. Short-term price reduction

2. 2. Short-term capacity increase

3. 3. Customer participation

4. 4. Diversified resources

5. 5. Reduced risk of market abuse

6. 6. Reduced price volatility (only in the short-term)

4. – Producer

1. 1. Avoided/Deferred infrastructure costs

5. – TSO/DSO

1. 1. Avoided/Deferred infrastructure costs

2. 2. Reduced outages risk

DR incurred costs- Consumer

- Initial

- a. Enabling technology- b. Response plan

- Running

- a. Inconvenience

- b. Lost business- c. Rescheduling- d. Onsite generation

- Program owner

- Initial

- a. Metering and communication- b. Billing system

- c. Customer education- Running

- a. Administration- b. Marketing- c. Incentive payments

- d. Evaluation - e. Increased demand uncertainty

- Market wide- Non standard DR products

- Producer

- Risk of lower prices on the market due to increased competition

- DSO

- Infrastructure costs for adapting to and benefiting from new DR technologies

2.3 DR benefits and costs: an analysis (2/2)

Factors influencing the level of demand-side participation in wholesale markets:External factors in Demand Response Availability :

Electricity Supply and Demand Conditions - The value of demand response depends on the cost of supply. Demand response is particularly critical in regions with scarce supply, and it has less value in markets with surplus capacity

Economic and Geographic Factors - underlying weather patterns, the relative level of residential load

Etc.

Internal factors influencing the level of demand-side participation in markets :

Regulatory environment

Market design - business rules which shape the ease with which demand response can participate in the markets and set or not the price (activation of emergency demand response may dampen market prices despite the fact that the system is in an emergency. If emergency demand response cannot set the market price, energy price signals may be distorted during emergencies)

Measurement and verification tools – the type and quality of communications between utility and customer will have an impact on overall consumption, on load management and on customer retention (Darby, 2008)

Etc.

Key factor for DR Programs to work: customer response � studying customer behaviour = an essential first step through DR large scale implementation

Crucial to distinguish between:

-short-run demand behaviour� utilisation

behaviour taking a household’s existing appliance stock as given

-long-run demand behaviour�incorporates both changes in utilisation behaviour & any adjustments to the stock of appliances owned by the household

3. Customer Behaviour: a key element for the success of DR programs

3.1 Pilot experiences (1/2)

US caseCategories of Household Behaviours that impact Energy Use: Frequency of action / Consumer Cost chart (Source:Laitner et al., 2009)

Range of Savings and Participation Rates by End Use Category (Source: Laitner et al., 2009)

� possible efficiency gains within a given end use category

3.1 Pilot experiences (2/2)

France caseStructure of electricity prices during the experiment (Source: Aubin et al., 1995)

� welfare improvement for majority of participants

� no observation on the effect of prices on equipment choice of participant households

After 1995, Tempo was generalized

� gradually 300,000 residential customers and more than 100,000 small business customers have chosen tempo

� the main negative point is the fact of having consecutive red days

- On average the daily consumption has been reduced

by 15 % on white days compared to blue days

by 45% on red days compared to blue days

- Concerning customer satisfaction level:

84% were quite or very satisfied with tempo

59% told us that they had made savings

53% considered the option as slightly unrestrictive or entirely unrestrictive

87% have understood the tariff principle very well

3.2 Analysing consumer’s behaviour (1/2)

Electricity customers are = economically “rational” (their decisions = taken so as to maximise their welfare) but an individual customer’s welfare = hard to define because the “preferred goods vector” has an infinite variation (a single customer can have x vectors, where x=undefined)

Industrial customers = minimising their production input’s costs (in our case = minimising the electricity invoice)

Technology and programs already implemented

Professional customer’s behaviour can be characterised as “rational” and their response can be anticipated

Residential customers welfare = depending on many factorsMain factors influencing their behaviour � response to the DR programs

Short Term Response is different from Long Term Response �which solutions for which result ?

Learning costs (customer and Program owner)

Open debate between two different views in the US:while behaviour-oriented programs provide a useful way to help deploy smart technologies, they can only round out a technology-based deployment of more energy-productive investments.

on the contrary: changed patterns of behaviours might reduce household use of energy by 22 percent within the United States

3.2 Analysing consumer’s behaviour (2/2)

�Two types of DR Programs are actually tested, both function of customer behaviour�Long Term and demand forecasts : Reducing peak consumption programs�Short Term and flexibility : Active Demand

Problems in estimating consumers’ responses to the electricity crisislength of the experiment

price information unknown price that each consumer expected to pay & perceptions of whatthe floating price would be each billing period (surely) differ across consumers

the ability of consumers to adjust consumption quickly to varying electricity prices requires a significant investment in new pricing programs, metering hardware, systems to communicate priceinformation, and the like

4. Concluding remarks: a critical assessment

� Consumers have considerable control over the short-run energy use of their household appliances, and will modify that use substantially in response to pecuniary incentives

� Successful DR programs depend heavily on customer education � Continuous marketing is important to attract new participants � Continuous evaluation and assessment of DR programs is important to develop a

better approach for reaching the ultimate objectives of the programs

� Advantages of DR programs� The most common utility motivation behind US DR programs = customer satisfaction by providing opportunities

for bill savings. Encouraging peak demand reduction and load growth comes after the prime motivation and complying with new regulations comes third

� The potential impact of demand response is large and significant, varying between 5% - 22.9%

� Unsolved problems� Calculating one “standard” residential consumers’ utility of consuming/reducing their electricity consumption� Low penetration rates in most pilot experiences on DR programs - attributed to poor marketing and limited

technical assistance provided to help participants managing price volatility� Big portions of required information about price responsiveness not available in most programs (some RTP

participants are not price responsive at all but hard to determine which segments respond best)