REQUISITOS GENERALES:

Alongside changes in electricity generation technologies (e.g. more nuc- lear generation), a focus on the way that the generated electricity is used is going to be an important factor in reaching the legal requirements. Un- derstanding and influencing domestic usage will be a significant part of the solution.

When considering the need to reduce carbon emissions in electricity gen- eration the fourth carbon budget report [24] notes that there is “power system flexibility on the supply side (e.g. fossil fuel plant can be oper- ated flexibly), but limited demand-side flexibility (e.g. only the largest customers are able to respond to high prices when the system is operat- ing at capacity)”. New low carbon generation plants are likely to be less flexible than traditional fossil fuel generation and the need for demand side flexibility will increase to cope with weather variabilities (e.g. lack of wind) and to reduce the need for high levels of backup generating capacity previously needed to avoid power cuts.

The Committee for Climate Change commissioned a report on possible ways of ensuring power generation flexibility [20] which makes the point that “Facilitating demand-side response through the roll-out of smart technologies and tariffs could provide a key source of within-day flexib- ility”. This will be particularly important as increasing amounts of trans- port energy usage (e.g. electric vehicles) and space heating (e.g. house- hold heating by electricity in preference to gas) is put in place.

The massive increase in data provided by the roll-out of smart meters allows for much better understanding of current domestic electricity us- age and provides the basis for implementing programmes to change the

behaviour for a more effective overall network.

In particular, the change of sampling of electricity usage from a three monthly billing cycle to a 30 minute sampling period using smart meters, alters the degree of understanding of households’ behaviour that is pos- sible [3]. DECC [38] provides the technical specifications for smart meters in the UK which defines a sampling frequency for reporting from the household to the utility company of 30 minutes while specifying an in- house reporting of usage of ten seconds. The selection of a sampling period of 30 minutes has been made on political and economic grounds and a more frequent sampling rate is technically possible and may allow enhanced analysis.

An important factor influencing the UK electricity market is that the as- sumption by consumers of the availability of a practically infinite supply of electricity (albeit at a cost) is no longer valid and domestic users will have to adapt to changing ways of using electricity or suffer from increas- ing unreliability of the electricity supply.

2.3.3

Demand Side Management and Demand Response

Research in the area of demand side responses has been ongoing for a number of years. For example, Newborough and Augood [39], in 1999, demonstrated the ability to reduce UK household peak usage of electri- city by up to 60% by an assortment of interventions including the replace- ment of some appliances by gas powered equivalents. Chamberlin [40] also showed that demand side management was being seriously invest- igated over 20 years ago.

Prior to the roll-out of smart meters, electricity suppliers were reliant on a meter reading on a three monthly cycle for feedback on usage by a given household. This provided a single reading (or possibly two readings for households with Economy7 meters) for total usage for the three monthly period and hence gave no feedback on time or day of usage (beyond the Economy7 period). Electricity suppliers were therefore unable to offer tariffs to change behaviour as there was no way of knowing the detailed prior behaviour, or the subsequent behaviour, resulting from introduction

of the new tariff.

Ofgem [17] estimates that the Electricity industry in the UK will need to invest an estimated £32bn by 2020 to deliver the networks required for the low carbon economy and to maintain secure, reliable supplies. This is a near doubling of the expenditure seen over the last twenty years. Ofgem also considers shortfalls in the current UK infrastructure which will impact on addressing the challenges of the next 10-15 years. Partic- ularly of interest is the fact that all the proposed possible packages of changes (except for the particular package suggesting a central energy buyer) include the need for an increased ability for the demand side to respond to supply signals.

Historically, electricity supply in the UK has been driven by a desire to provide sufficient supply to match the predicted demand and to avoid shortages and blackouts. The restrictions on supply due to cost, changing political opinions regarding generation technologies, and international obligations to meet carbon reduction targets, means that, in the future, the emphasis will need to change to demand more closely matching the available supply. One approach to addressing this issue is the application of demand side management (DSM) techniques to achieve changes in consumer behaviour. River [4] defines DSM as “systematic utility and government activities designed to change the amount and/or timing of the customer’s use of electricity” for the collective benefit of society, the utility company, and its customers.

Tata Power provide a summary of how they define demand side manage- ment2 including Figure2.2which details the steps needed in a typical DSM program. Figure2.3provides a summary of the varying objectives for a DSM program. For example, it might be the goal of the program to reduce the peak demand (to reduce standby generation capacity) and a “peak clipping” program may be instituted.

River [4] provides a good explanation of what is meant by demand side management as well as detailing various US-based trials of variable pri- cing. It provides a good historical perspective on DSM and makes the point that the current focus is on real time pricing (or dynamic pricing)

Figure 2.2:Stages of Demand Side Management (from Tata Power)

rather than Time of Use (TOU) pricing. Dynamic pricing allows utilities to change prices in real time based on the current load on the electricity network and requires consumers (previously industrial customers but increasingly also domestic customers) to sense the changing price and make changes to their electricity usage automatically (e.g. by using smart appliances).

The report also states that “it is important to note that the demand-side of the market has typically been neglected. This has been true in developed as well as developing countries.”

Figure 2.3:Load shape objectives (from Tata Power)

Hamidi et al. [41] has investigated the amount of the total domestic de- mand that could be responsive to demand side management interven- tions by examining a small number of households in the UK. This ana-

lysis was done by considering different classes of appliances (e.g. “wet” such as washing machines, “cold” such as fridges) and examining at which periods of the day they are used as well as considering how their usage could be varied. This work is useful as it can be applied to activ- ities derived using motif detection and could give utility companies a measure of how responsive a particular activity may be to interventions. Zachary et al. [42] provides a mathematical approach to assessing the value of wind generation capacity and how the ability to move peak demand can be measured in terms on impact on the cost of wind gener- ation capabilities. This approach could be used to give a financial value to DSM programmes but is based on many assumptions and is currently only applicable to wind generation.

Darby and McKenna [43] reviews the social aspects of demand response programmes with a particular emphasis on distinguishing the UK (as a country with a temperate climate) from other countries with different cli- mates. The study identifies short term (up to 2020) approaches to demand response and longer term (after 2020) changes. Darby and McKenna [43] makes the useful point that “From the user perspective, the extent to which people shift their consumption patterns will depend on factors such as perception of the need to do so, trust in the utility or energy service provider, incentives, and transaction costs (including cognitive costs).”

While many DSM programs have been tested, there have generally been poor results from the research with improvements in electricity usage typ- ically being only a few per cent. Some reasons for demand side response programmes not being taken up in the UK are suggested by Torriti et al. [44]:

• Utilities are measured by the government on achieving a net reduc- tion in electricity usage and many DSM programs do not clearly generate a net conservation (while they may usefully shift the time of peak usage).

• Demand side response technology has been available but only at a high cost relative to the electricity savings expected.

• A large electricity demand targeted in some countries is the use of air conditioning (AC) units with consumers encouraged to change the times of usage. However, as there is little domestic AC deploy- ment in the UK, this area of behaviour modification is not available. • Government regulation and industry oversight does not currently

encourage utilities to implement DSM programs.

As well as the above points, the history of energy usage in the UK (in- cluding little air conditioning, a temperate climate, and the previous high deployment of storage heaters) makes the UK a special case. In addition, the availability of North Sea gas and cheap coal led to expectations of low energy costs and thus poor thermal qualities of a lot of the UK housing stock. Thus, a lot of research from around the world may not apply to the special circumstances of the UK situation.

Various studies have investigated the type of feedback that is most ef- fective in changing individual’s usage of electricity to meet peak shift- ing or overall reduction goals (for example Fischer [45]). These studies provide some useful information although it is possible that other, more fundamental, interventions (for example, by altering local travel condi- tions such as bus timetables) will be more successful in meeting the goals of demand side management. Neenan [46] provides a comprehensive review of various feedback studies relating to energy usage and distin- guishes between six levels of feedback varying from standard monthly or quarterly billing to “real time plus” feedback (which includes real time details on usage of individual appliances).

An interesting study in Australia extended the deployment of monitors to the use of water (in addition to electricity) with the monitors providing alarms to the household occupants when usage hit certain levels. A sav- ing of 3% of water and 2.4% of electricity was reported [47]. This shows how the need for demand side management can be extended to other resources requiring management. However, while important in some parts of the world, the need to manage water efficiently is less import- ant in the UK and may be better addressed by improving water supply management (e.g. fixing leaks) before the need to deploy water demand management programmes. As the predicted changes in climate come to

pass, the importance of water management may increase in the UK as droughts become more likely.