Appraising the Economics of Smart Meters

Costs and Benefits

Jacopo Torriti

• Publisher: Routledge
• Year: 2020
• ISBN:
  9780429533983
• Edition: 1
• Topic: Economics
• Subtopic: Comparative Economics
• Index: Economics

This book focuses on the economics of smart meters and is one of the first to present comprehensive evidence on the impacts, cost-benefits and risks associated with smart metering.

Throughout this volume, Jacopo Torriti integrates his findings from institutional cost-benefit analyses and smart metering trials in a range of European countries with key economic and social concepts and policy insights derived from almost ten years of research in this area. He explores the extent to which the benefits of smart meters outweigh the cost, and poses key questions including: which energy savings can be expected from the roll out of smart meters in households? Is Cost-Benefit Analysis an appropriate economic tool for assessing the impacts of smart metering rollouts? Can smart meters play a significant role in research on people's activities and the timing of energy demand? Torriti concludes by providing a much-needed survey of recent changes and expected future developments in this growing field.

This book will be of great interest to students and scholars of energy policy and demand and smart metering infrastructure.

1 Are smart meters worth the cost?

Waiting for meter data

My second son has just re-discovered it. It has been away in a drawer in the kitchen along with other objects we use very seldom (knife sharpener, birthday candles, party cups, etc.). It had been lying there for many months, maybe even a whole year. My first son once played with it for 20 minutes or so and then returned it to that drawer. Now, this rarely used object is getting someone’s attention once again – the attention of a four-year old.

• – What is it papà?
• – It’s a smart meter. Well, an in-home display.
• – What does it do?
• – It’s supposed to let us know how much electricity we are using. For instance, when the dishwasher is on, I look here and see some numbers.
• – Wowww! Shall we do it?
• – It doesn’t really work, but you can press this button and see some zeros here.

I forgot that when we switch it on, we do not see the zeros, but a very standard message: ‘waiting for meter data’. This was the first disappointment I had with my smart meter. There is nothing smart about having this in-home display at home and not being able to know in real-time how much electricity we are using and how much money we are spending because we live on the third floor of an apartment block and the in-home display cannot receive information from the smart meter. While my son starts pressing all the buttons the device can offer, I am thinking of other uses this might have. Years of research in this area prompted me to think that after all the benefits of the smart meter are not just about direct feedback on energy usage. Smart meters are also about opportunities to get involved in demand-side flexibility and participating in residential demand-side response, on which I wrote another book (Torriti, 2015). On the one hand, this sparked further frustration as I came to realise that in the future I will be cut out of opportunities to change retailers in real time, move across time of use tariffs, benefit from dynamic tariffs and one day – who knows – even have the smart meter communicating with a controller which minimises the costs of my electrical appliances as it selects when they are on and off based on the cheapest (and greenest) available tariffs. On the other hand, these unmaterialised opportunities make me hope that regardless of that ‘waiting for meter data’ message, progress is under way and the future might be brighter for others. For now, when it comes to meter readings, I can take my in-home display out of the drawer, out to the corridor, down the lift and – once on the ground floor – finally after a couple of minutes my ‘not anymore in-home’ display starts connecting to the smart meter. Basically, it is a substitute to the key of the communal door behind which all the meters of our block of apartments are.

My son finished playing with the ‘smart meter’. The smartest thing he did was to put it back in the drawer. I start thinking that smart meters got a lot of bad press for different reasons but there is progress in what they set out to achieve. Writing a book on the economics of smart meters may not be the smartest thing to do, but it is what I decide to embark on.

Context

Over the past decade climate change imperatives have led governments of several countries around the world to move away from fossil fuel-based power generation and to increase shares of cleaner power generation technologies into power systems. This means that the generation of electricity is becoming less dependent on a few centralised power stations as these are being gradually replaced by a multitude of smaller plants. The highest level of decentralisation of power generation consists of industrial, commercial and residential buildings producing electricity from smaller units of renewable generation (Hanna et al., 2018). Concerns over security of supply feature among the explanations leading to policy decisions around the decentralisation of the power systems (Allen et al., 2008). Distributed power generation assets can improve the utilisation of local energy resources, offer greater resilience and potentially be more cost-effective (Chmutina & Goodier, 2014). The reduction in costs compared with more centralised systems is justified by the fact that generating power locally reduces some of the costs of transmission and distribution system upgrades, and the additional generation resources can contribute to grid reliability as the risk of technical failures is spread across a wider portfolio of generation.

Policies which have steered the way towards a higher integration of renewable energy are generally paired with the vision of a model where the power system is connected by a two-way grid and where resources such as physical storage, active demand management and the output of hundreds (if not thousands) of small power generation units will be balanced in real time with the aid of intercommunication links.

The integration of decentralised renewable sources of electricity also presents challenges as these are associated with an increase in the rigidity of power supply. The intermittent nature of their supply along with the lack of control over their outputs and their limited system inertia poses new challenges with regard to the balancing of demand and supply. Flexibility provision has historically been a responsibility of the supply side (Grünewald & Torriti, 2013). The transition to a net zero or low-carbon energy system will depend not only on the decarbonisation of power generation through an increased uptake of intermittent renewables, but also – and to a great extent – on the ability to find alternative ways of providing the flexibility needed to maintain the system balance (Barton et al., 2013).

It is against this background that smart meters are introduced as part of demand-side device to be integrated with the changing needs of electricity supply. In a nutshell and as way of introduction, smart meters are expected to provide a means of collecting high-resolution energy demand data at end-use point.

Decisions around large public investments in smart-metering infrastructure are very difficult for policy-makers without the support of strong empirical evidence. This book presents research on economic analysis underpinning decisions to invest in smart-metering infrastructure. Smart meters are extremely interesting because they are part of a larger plan to transform electricity systems, making them smarter, greener and richer in terms of data exchange. Smart meters are the first and/or last items of very large infrastructure and are also very close to the people. They are supposed to capture the rhythms of everyday life (at least with regard to electricity demand), measure levels of consumption which may change depending on price and time of day, and send signals to users warning about higher tariffs or peaks due to weather conditions, nudging customers to make them ‘change behaviour’. The smart meters, with different degrees of human intervention, are also supposed to interact with the grid, sending data about demand which are of use for those who manage distribution networks, offering market opportunities for rewards based on temporary reductions in energy consumption. The information which is captured, measured and transmitted by smart meters is of interest not only to energy organisations (suppliers, aggregators, distribution system operators, transmission system operators), but also to non-energy organisations, which can derive from them useful information in terms of understanding occupancy patterns, consumption trends and market segmentation.

Overview of smart-metering roll-outs

For the past two decades there have been programmes and projects in place in various countries for the roll-out of smart meters. In 2009 the European Commission’s Third Package for the liberalisation of energy markets marked a monumental change in smart–metering history as tens of countries commenced their roll-out plans in its aftermath. For this reason, two time periods are presented here: pre-2009 and post-2009.

Pre-2009: pioneering countries

Prior to 2009 smart meter projects had already taken place in Italy, Sweden, the Netherlands, Canada, Australia, California (USA) and Northern Ireland. The Italian utility ENEL introduced smart meters in 2001 as a result of an in-company investment decision. The rationale for this decision was based on expected savings or revenues in the areas of purchasing and logistics, field operations, customer services and revenue protection, which relates to a better understanding of where fraud occurs within low-voltage distribution networks. Over the years, I have been told by people working for ENEL that an economic business case existed, and this was not in the form of a traditional cost–benefit analysis (CBA). In fact, neither the Italian energy regulator nor government had any significant influence on requirements ENEL had to fulfil. This means that ENEL could choose the type of meter and the communication infrastructure independently and opted for a smart electricity meter that communicates through power-line communication (PLC) to the nearest substation (Torriti, 2012). By the end of 2005, ENEL had 27 million smart meters installed, of which 24 million meters being remotely managed and bimonthly read (Alberini et al., 2019). The early move by ENEL meant that the Italian regulator was confronted with challenges such as providing smart meters to the minority of consumers not covered by the ENEL and ripping the benefits of the investment made, which was estimated at about 2.1 billion Euros (Meeus & Saguan, 2011).

As a response to these challenges, the Italian regulator issued a mandatory roll-out of smart meters in 2006 and gradually increased operating costs in metering activities reaching the level of 7.1% at the end of the mandatory roll-out period (Lo Schiavo et al., 2013). As of today, more than 95% of low voltage customers, also those located outside ENEL areas, are provided with smart meters.

In Sweden some utility companies developed smart-metering pilot projects in the early 2000s and the government expected economic benefits in terms of energy savings. In 2003 the Swedish government issued a law which contained an obligation for monthly meter readings for all electricity users by 2009, hence creating the conditions for the introduction of smart meters. Since then, investments in smart metering have developed in a faster rate than required by law (Van Gerwen et al., 2006).

In the Netherlands the smart meter roll-out was planned since 2004 as a way to improve demand response at the level of small consumers. However, the regulated roll-out could only start eight years later due to unanticipated resistance from the public in terms of privacy rights infringements (Hoenkamp et al., 2011). An independent cost-benefit analysis was carried out as part of the decision-making process (see Chapter 3). This also followed the development of pilot projects (Van Gerwen et al., 2010).

In Ontario in Canada, increasing electricity demand peaks were the main factor for smart metering. The Ontario Energy Board installed about one million smart meters up to 2008 with plans to cover all 4.3 million Ontario customers by the end of 2010 (Torriti et al., 2010).

In Victoria in Australia, smart-metering installation started in 2006. The rationale consisted of increasing summer electricity demand peaks by air conditioning causing extra investments in low use plants and the linking of wholesale and retail markets.

Smart meters in California were introduced with the aim to increase the reliability of electricity supply in this state, through the reduction of consumer peak demand. California has a summer peak demand for power during approximately 50–100 hours per year. This peak is mainly due to the increasing use of air conditioners. The main energy agencies of California saw demand response as an important mechanism to decrease this peak.

2009: the EU directive common rules for the internal market in electricity directive (2009/72/EC)

The European Commission’s Third Package for the liberalisation of energy markets recommended that member states should implement smart-metering roll-out plans which should achieve 80% penetration by 2020, if an economic assessment proves the implementation as feasible.

A European Commission interpretive note (pp. 8–9) for the Directive of 2009 states that:

Where an economic assessment of the long-term costs and benefits has been made, at least 80% of those consumers who have been assessed positively, have to be equipped with intelligent metering systems for electricity by 2020 … where no economic assessment of the long-term costs and benefits is made, at least 80% of all consumers have to be equipped with intelligent metering systems by ...

Table of contents

• Cover
• Half Title
• Series Page
• Title Page
• Copyright Page
• Table of Contents
• List of figures
• List of tables
• Preface and acknowledgements
• 1 Are smart meters worth the cost?
• 2 The economics of smart meters
• 3 Cost–benefit analyses of smart meters in European countries
• 4 Cost–benefit analysis of smart meters in Romania
• 5 Cost–benefit analysis for energy policies
• 6 Meta-analysis of smart-metering trials and conservation effects
• 7 Beyond economics and system needs: theoretical approaches to understand smart meters energy demand
• 8 A smart future?
• Appendix – policy options in regulatory impact assessments on smart meter roll-outs
• Index