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State of the Art and Trends Review of Smart Metering in Electricity Grids

Centre for the Development of Renewable Energy Sources (CEDER)—Research Centre for Energy, Environment and Technology (CIEMAT), Autovía de Navarra A15, sal. 56, Lubia, Soria 42290, Spain
Department of Agricultural Engineering and Forestry, University of Valladolid (UVA), Campus Universitario Duques de Soria, Soria 42004, Spain
Department of Communications Engineering, ETSI Bilbao, University of the Basque Country (UPV/EHU), Alda Urkijo s/n, Bilbao 48013, Spain
Author to whom correspondence should be addressed.
Appl. Sci. 2016, 6(3), 68;
Submission received: 29 October 2015 / Revised: 9 January 2016 / Accepted: 22 January 2016 / Published: 29 February 2016
(This article belongs to the Special Issue Smart Grid: Convergence and Interoperability)


Climate change, awareness of energy efficiency, new trends in electricity markets, the obsolescence of the actual electricity model, and the gradual conversion of consumers to prosumer profiles are the main agents of progressive change in electricity systems towards the Smart Grid paradigm. The introduction of multiple distributed generation and storage resources, with a strong involvement of renewable energies, exposes the necessity of advanced metering or Smart Metering systems, able to manage and control those distributed resources. Due to the heterogeneity of the Smart Metering systems and the specific features of each grid, it is easy to find in the related literature a wide range of solutions with different features. This work describes the key elements in a Smart Metering system and compiles the most employed technologies and standards as well as their main features. Since Smart Metering systems can perform jointly with other activities, these growing initiatives are also addressed. Finally, a revision of the main trends in Smart Metering uses and deployments worldwide is included.

1. Introduction

The need to address metering issues arises practically at the same time as the development of distribution electricity grids. There is a remarkable evolution from the first known electricity meter, patented by Samuel Gardiner in 1872 [1], which only provided information about the length of the electricity current flow, to the up-to-date systems, which are able to provide a wide range of applications rather than just metering. The first automatic and commercialized remote meter is attributed to T. Paraskevakos in 1977 [2]. However, the remote metering concept was not realized in the expected electricity context for many years. Climate change, awareness of energy efficiency, new trends in electricity markets, and the gradual conversion of consumers towards more active agents are promoting not only the use of Renewable Energy Resources (RES), but also the Distributed Generation (DG) and Distributed Storage (DS), which urge a dramatic evolution of the actual electricity model. Evolution towards an electricity grid model able to manage numerous generation and storage devices in an efficient and decentralized manner determines the core of the Smart Grid (SG) concept, making the deployment of advanced metering systems or Smart Metering one of the basic techniques to reach this goal. The European Parliament, in the 2012/27/EC directive, defined a Smart Metering or intelligent metering system as “an electronic system that can measure energy consumption, providing more information than a conventional meter, and can transmit and receive data using a form of electronic communication” [3]. Regarding communication, Machine-to-Machine (M2M) communications happen in devices with capabilities to communicate among them without the need of human intervention. The captured event-driven data is sent through the communication channel (wired or wireless) to the servers in charge of extracting and processing the data and generating responses [4]. Therefore, M2M capabilities are key for Smart Metering performance, since they allow the required bidirectional communication between consuming points and monitoring and control centers [5].
Besides the control and management capabilities provided by the implementation of the Smart Metering, the obtained metering data together with additional information can be used by automatized systems to lead new applications, such as predictive and load management systems.

2. Trends of the Smart Metering Systems

The metering side of the distribution system has been the focus of most recent infrastructure investments. The first attempts at metering automatization, or Automated Meter Reading (AMR), allowed utilities to remotely read the consumption records and basic status information from customers’ premises [6]. Due to its one-way communication system, AMR is limited to remote reading and cannot run additional applications, which prompted utilities to move towards the Smart Metering or Advanced Metering Infrastructure (AMI). Smart Metering provides utilities with bidirectional communication to the meter but also the ability of evaluating the status of the grid. Recent Smart Metering systems, equipped with an improved architecture, and working together with smart sensors and more sophisticated distributed control technology, allow utilities to perform grid control and management [7]. Figure 1 shows the evolution from AMR to AMI with lists of stakeholders and benefactors for each step.

2.1. Architecture of a Smart Metering System

A Smart Metering system implies the deployment of a heterogeneous infrastructure, including metering devices, communication networks, and data gathering and processing systems, as well as the associated management and installation duties. A Smart Metering system is based on four main pillars:
  • A Smart Metering device, Smart Meter (SM);
  • A data gathering device, Data Concentrator (DC);
  • A communication system used for data flow;
  • A centralized management and control system, Control Center (CC).
Smart Metering systems are heterogeneous deployments with different requirements and features since they highly depend on the intended use. In addition, different types of measurement can be found in the same Smart Metering system. Three main measurement groups can be differentiated: (i) on-demand: measured data flows from the consuming points to the CCs upon specific request of the utility when needed; (ii) scheduled: measured data flows from the consuming points to the CCs by pre-programmed tasks and between four and six times a day per meter; and (iii) bulk: the utility collects metering information from all devices several times per day [9].

2.1.1. Smart Meter

The most recent evolution of the Smart Meter (SM) is based on the introduction of bidirectional capabilities and the progressive appearance of new applications. Bidirectional capabilities must be understood from two different points of view: energy (energy flows towards/from consumption/generation points, mainly due to the DG, DS, and prosumers figures) and communication (data travels from the SMs to the CC, but the CC can also communicate with them, as the SM includes an embedded communication node, within a configurable and multifunctional network).
An SM can present a wide range of features. Although there is not a directive or norm that defines them in terms of quantity or functionality, different bodies have established some guidelines. The European Smart Meters Industry Group (ESMIG) has reduced the minimum features of an SM to the following four:
  • Remote reading
  • Bidirectional communication
  • Support of advanced tariff systems and billing applications
  • Remote energy supply control.
On the other hand, the European Union extends the minimum desirable requirements for an electricity SM as published in 2012/148/EU recommendation, described in Table 1.

2.1.2. Data Concentrator

The main function of the DC is to gather metering data from the SMs. In addition, DCs are usually the master node of a communication subnetwork formed by itself and a set of SMs, which implies that they also include an embedded communication node. DCs are usually located inside Power Transformers (PTs) and substations. Modern DCs also include additional features such as low-voltage (LV) supervision, since they include an embedded SM.

2.1.3. Communication System

The transmission of data must be guaranteed in terms of quality, time, and security. Therefore, the communication technologies play a key role, as they have to be cost-efficient and should provide good coverage, security features, bandwidth, and power quality with the least possible number of repetitions [10]. Section 5 addresses the main challenges that the Smart Metering communication system must face. Communications in power grids have evolved from one-way communication systems and radial topology to bidirectional systems with network topology. A wide review of communication features, requirements, and technologies for SG and Smart Metering communication networks can be consulted in [11].

2.1.4. Control Centre

The CC or Data Management System (DMS) is in charge of receiving and storing the metering data for processing purposes. The CC can be seen as a modular system formed by the Meter Data Management System (MDMS), which manages the metering data, and additional secondary modules in charge of end-users applications, weather forecasting systems, geographical information systems, control applications, and load management, among others. The MDMS includes the tools that enable communication among different modules, as well as being in charge of validating, processing, and editing the metering data for a suitable information interchange among the different parts of the Smart Metering system [12]. CCs have evolved with the progressive increase of Smart Metering systems’ capabilities from mere data compilers and storage devices, typical of AMR systems, to more sophisticated systems able to take decisions and manage the entire system in real time. Generated data from measurements is a very valuable resource for utilities, since they are able to make a wide range of forecasts (available energy, probability of power failures, customers’ consumption predictions) by using predictive analysis, which enables utilities to take proactive action rather than simply reacting to events after they happen [13]. Making the most of information from SMs and SGs increasingly requires dealing with what is called Big Data. Diamantoulakis et al. present a roadmap of Big Data analytics in Demand Energy Management that includes, among other strategies, load patterns categorization, predictive analytics, distributed data mining, and cloud computing, to assess different aspects of the SGs that cannot be solved with conventional data processing techniques [14].

2.2. Considerations for a Smart Metering System

A Smart Metering system can be seen as three differentiated phases: planning, rollout, and operation. The widely ranging requirements and characteristics of each specific application, technology, and deployment scenario make the planning of a Smart Metering system a nontrivial task [15]. Table 2 summarizes some of the most important consideration to take into account when designing a Smart Metering system. The rollout phase refers to the actions involved in replacing all the meters included in the initial scope of the project. This phase also includes deploying the communication infrastructure, including all components and devices. Finally, the operation phase refers to actions carried out on the infrastructure after the rollout, that is, after the scheduled replacement, initial configuration of devices, and initial setup of the central system [16].

2.3. Smart Metering Applications

Beyond management and control, the implementation of a Smart Metering system allows several applications that join the metering data together with additional information and other devices from which both utilities and end-users should benefit. Most of them are currently under development and are experiencing a remarkable growth since 2006 [17]. A summary of the main Smart Metering applications is described below.
  • Electricity signal quality:
In the traditional power distribution networks, the control devices are solely located in the substations; however, with the progressive introduction of the SG, the complexity and number of required controlled assets increase and more detailed, distributed, and frequent control information is required. SMs′ capabilities of real-time voltage measurement and communication between the consumers and network controllers are potential key players in voltage control [18]. Several projects implementing voltage control techniques include SMs in their solutions [19].
  • DG and DS control:
The control and management of DG, especially regarding RES, is more complicated than conventional sources due to its less predictable behavior and varying availability. These uncertainties hinder CCs′ operations and represent a barrier for distributed resources in general. SMs can help in those issues by providing accurate, frequently-updated, and real-time generation and charge/discharge metering data from DG and DS, respectively, which may facilitate CCs′ duties and foster RES′ introduction in electricity grids.
  • Billing:
Smart Metering systems are necessary in billing applications. The SMs get the tariff costs in real time, in advance or through pre-programmed tariffs and then the cost of the supplied energy is calculated. In addition, the SMs can remotely cut or restore the power supply if needed. The most common billing techniques are pricing depending on the time of use, real-time pricing, and peak consumption-dependent pricing [9].
  • Demand Response:
The dynamic coordination of the power consumption curve of end-users within existing supplying conditions or Demand Response (DR) contributes to the efficiency of the system. Additionally, DR provides an opportunity for consumers to play a significant role in the operation of the electric grid by reducing or shifting their electricity usage during peak periods in response to time-based rates or other forms of financial incentives. Such programs can lower the cost of electricity in wholesale markets, and, in turn, lead to lower retail rates [20].
  • HAN applications:
The role of Smart Metering in the end-user′s premises is very promising. From metering data consumers can know and control their electricity consumption. Additionally, a wide range of services is emerging, such as consuming profiles, load control, remote switching of home devices, and remote consumption monitoring, among others. For instance, in [21] the data from domestic energy consumption is used together with an algorithm to establish categories of energy consumers, while [22] contains an analysis of generated energy savings after the installation of SMs in Korean homes. Nevertheless, some energy managers are expected to play an important role in the progressive deployment of the triple play (confluence of audio, video, and Internet access).
  • Anti-fraud techniques:
Bypassing or disrupting the internal performance of a SM and using methods to avoid electric bill payment are considered as electrical frauds. Several countries are developing anti-fraud techniques through Smart Metering systems. For instance, Depuru et al. present in [23] a complex system formed by SMs, harmonic generators, and filters that detect and warn users who commit fraud.

3. Smart Metering Technologies

The successful implementation of a Smart Metering system highly relies on the choice of communication technology. Different aspects such as the final application, the features of the location, and the topology electricity grid, among others, highly influence the choice of the most suitable technology. There is a wide range of available technologies for the communication network of a Smart Metering system; however, there is currently no communications technology that fits all needs and sometimes more than one technology is used in the same deployment [11,24,25]. Figure 2 shows a worldwide tendency for communication technologies from 2011 to 2020.
Two main groups can be distinguished in Smart Metering technologies: wireless and wired. Wireless technologies usually entail less deployment costs and quicker installation than wired options. Additionally, they are more suitable for remote or hardly accessible locations [26]. However, wired alternatives for Smart Metering do not present interference problems from other sensors of the network that may occur in wireless technologies. Table 3 summarizes the main technologies and their features for Smart Metering systems.
Radio Frequency (RF) technologies for Smart Metering deployments are specially spread in the United States. In RF technology, measurements and other data are transmitted by wireless radio from the SMs to a collection point. The data is then delivered to the CC for processing. The best-known topology is RF mesh, in which the SMs talk to each other and form a Local Access Network (LAN) cloud to a collector [8]. RF mesh has an acceptable latency and large bandwidth and generally operates at free license bands. In addition, the self-healing characteristic of the network enables the communication signals to find another route via the active nodes, if any node should drop out of the network [28]. However, this tends to be a proprietary offering and the terrain and long distances typical of rural areas are a challenge for its deployment.
It is common to find RF-cellular technologies used in Smart Metering deployments in the United States. Their strengths are the wide coverage and low maintenance costs that they offer. In addition, cellular technology has experienced a rapid growth, resulting in better bit rates and more potential applications.
However, individual connections are still expensive. Several U.S. carriers such as T-Mobile and Verizon have adopted 4G Long Term Evolution (LTE) since the cost of upgrading the existing 3G network is lower [11].
Despite the fact that most European countries use wired alternatives, cellular networks, especially GPRS, can also be found in some deployments [29]. GPRS is an open standard technology and an effective and reliable technology. Several trials performed in Cork (Ireland) with SMs using GPRS reported a good performance of this technology (success rate of 97.89% for first-time reads) and easy deployment [30]. However, the data rate is moderate.
Other wireless technologies such as ZigBee, 6LoWPAN, and Bluetooth are based on IEEE 802.15 standard [31]. These technologies are characterized by low bit rates, low power consumption, and low cost. ZigBee is a widely-known technology and the most used in domestic networks so far. It is considered a good option for Smart Metering and energy management due to its simplicity, mobility, robustness, low bandwidth requirements, and low cost of deployment [32]. However, the limited size of the devices that implement ZigBee restrict the battery life, the internal memory, and the processing capabilities. On the other hand, 6LoWPAN uses the Internet Protocol (IP) over WPAN (IPv6 over Low Power Wireless Personal Area Networks). Since it is based on the same features as ZigBee, they compete with each other in the same market. The main advantage of 6LoWPAN is that it identifies every node by means of an IP address, which allows ubiquity, versatility, and resilience [33]. As an example, Lu et al. present in [34] both a ZigBee-based and a 6LoWPAN-based SM network architecture. Finally, Bluetooth is a low-power and short-range option, mostly used in local applications. It allows both point-to-point and point-to-multi-point configurations. Despite being less used, Bluetooth technology can be a possible option for communication of control signals and transmitting energy consumption data. Koay et al. proposed in [35] a Bluetooth based energy meter that can collect and transmit the energy consumption data wirelessly to a central base station. However, this provides a lower degree of security in comparison with other technologies [36].
Another family of standards is IEEE 802.11 (see Table 3) or Wireless Neighborhood Access Network (WNAN), also known as wireless Ethernet [37]. They are technologies with a high degree of reliability and availability (although lower than wired options). However, the electromagnetic interferences affect their data rate and the radiofrequency that they emit may influence surrounding devices.
Finally, Worldwide inter-operability for Microwave Access, WiMAX, comes from IEEE 802.16 standard for Wireless Metropolitan Area Networks (WMAN) and is a complementary technology to IEEE 802.11 standard. WiMAX is able to supply to thousands of end-users at larger distances and with better QoS systems [36]. Some U.S. companies are proposing WiMAX for SG solutions and WiMAX has also been used as a backhaul in a wide Smart Metering deployment in Australia [38]. However, it is still an expensive technology.
Among the existing wired technologies for Smart Metering systems, Power Line Communication (PLC) is one of the most widespread technologies and the most used in Europe and China [39]. A great advantage of PLC is that the communication channel is part of the electricity grid, and therefore it is already deployed. Additionally, transmitter devices do not depend on batteries since they use the power supply directly [40]. However, as the electricity grid was not conceived for data transmission, it is a harsh medium and communications are subject to disturbances due to spurious emissions and supra-harmonics from the devices connected to the grid (inverters, turbines, lamps, and appliance engines, among others) [36]. The PLC frequency bands differ from one region to another. In Europe, PLC is regulated by CENELEC and specifies four different bands: energy providers (standard and proprietary protocol), users (standard and proprietary protocol), users (CSMA access), and users (standard protocol) from 3 to 148.5 kHz. FCC regulates the ranges in the United States (10–490 kHz), ARIB in Japan (10–450 kHz), and EPRI in China (two bands from 3 to 500 kHz). Two main groups can be distinguished among PLC technologies: (i) Broadband PLC (BB-PLC), which uses frequencies up to 30 MHz and enables high data rates; and (ii) Narrowband PLC (NB-PLC), which uses frequencies up to 500 kHz and provides moderate data rates. NB-PLC is currently experiencing an expansion due to its good performance, a consequence of adapting advanced modulation techniques such as OFDM. Although its data rates are moderate, it is sufficient for Smart Metering applications. NB-PLC is especially popular in Europe, where nearly all countries have performed at least a pilot, and a wide range of deployments use this technology. Among NB-PLC standards it is worth mentioning G3, PRIME, and IEEE 1901.2. Poland and Spain have performed massive deployments using PRIME while Japan, France, and Luxembourg have used G3. Both IEEE 1901.2 and G3 offer “phase detection,” a popular feature that allows the node coordinator of the network to determine on which phase a single-phase SM is connected. Then, the utility can balance the power demand across the three phases and improve the quality of the supply [41].
Digital Subscriber Line (DSL) is also a popular wired technology that uses the wires of the voice telephone network. Its main advantage is that in most cases the medium is already deployed and the data rates are quite high. Hence, some companies have chosen DSL technology for their Smart Metering projects, such as Stadtwerke Emden in Germany by Deutsche Telekom, where DSL is used to transmit the consumption information from customers’ premises to the municipal utilities [42]. However, the maintenance cost of DSL is high and its efficiency decreases with distance.
It is worth mentioning Euridis, a low-cost solution, well known (it was first introduced in the early 1990s) and with a long history of deployment (approximately 6 million SMs worldwide use this technology). Euridis allows simultaneous access to up to 100 SMs connected in the same bus and it is considered the unique existing standardized interface for Smart Metering applications over twisted pair cable. It is part of the IEC 62056-31 standard [43]. A considerable number of SMs in France are equipped with a Euridis interface [44].
Finally, the fiber optic, well known for its very high data rates and noise immunity over several kilometers, has experienced a moderate expansion due the cost of deployment, especially if it is only used in the SG context. For this reason, its use in Smart Metering systems is limited to the Medium Voltage network and as a communication backbone in the transmission network by connecting DCs and CCs. Passive Optical Networks (PONs) are the most suitable option for Smart Metering, since they use optical splitters and one single fiber can serve several end-users.
Within the standardization process, it is worth noting the work conducted by CENELEC, which has developed more than 60 standards and has 40 more underway. Additionally, CENELEC has joined forces with CEN and ETSI (European Telecommunications Standards Institute), coming into the Smart Meters Coordination Group (SM-CG). In North America, it is worth mentioning the work developed by ANSI (American National Standards Institute) and NIST (National Institute of Standards and Technology), as well as IEC (International Electrotechnical Commission), IEEE (Institute of Electrical and Electronics Engineers), and ISO (International Organization for Standardization) on an international level.

4. Development of Smart Metering Worldwide

The deployment of SMs is on the rise worldwide: around 1000 million SMs are expected to be installed worldwide by 2022 [45]. Figure 3 represents the evolution of SM deployment worldwide from present to 2023. As discussed in Section 4, there is a wide range of available technologies and the most suitable one depends on a number of factors.
The architecture of the electricity system highly influences the adopted approach for a Smart Metering solution. Hence, the topology of the network defines the topology of the Smart Metering system and may determine the equipment and the technology to be used. For example, while in the United States a single transformer serves a few end-users, in Europe it can easily reach several hundred. Then, PLC technology is more profitable in Europe than in the United States, where wireless solutions are more desirable. The drivers of the deployments also vary. While in some regions, especially in Europe, SG and Smart Metering projects have been driven by governmental initiatives, funding, or mandates, other regions seek to improve the efficiency of the energy supply system and eliminate electricity theft, as with emerging countries [46,47]. Additionally, it is worth mentioning the differences in development approaches. For instance, in the U.S. the goal is the security and stability of the electricity network, with a clear objective towards self-healing. By contrast, in European countries the trend is towards reduction of greenhouse gases and the promotion of DG, DS, and RES [48]. In addition, the regulation of public band frequencies use in the U.S. is more flexible than in Europe, which has reinforced wireless options in the U.S. Australia, Canada, and Japan have also largely adopted wireless Smart Metering solutions, while China relies on either PLC or BPL. In Europe, the strict regulation of public and unlicensed bands initially encouraged early adoption of PLC solutions. Despite recent concerns about PLC reliability, which have prompted European consideration of wireless options, NB-PLC technology is still the most widespread technology for Smart Metering systems in Europe with a wide range of existing pilot projects and massive deployments [41,46]. The early adoption of PLC-enabled SMs in Italy, Spain, and China has given this technology its current momentum. Meanwhile, cellular connectivity is witnessing a growing adoption, especially in cases where meter implementations are dispersed. It is also gaining wider acceptance as a feasible, primary connectivity technology, with subscription costs decreasing and utilities becoming more open to using public networks for their SM deployments [49].
There are also differences in the application approach of the Smart Metering systems. Among the European member states, the technical design of Smart Metering systems varies from one country to another. Generally, there is a common understanding of what capabilities a SM should have but often a subset of these capabilities is chosen for their rollout. A recent report from the CEER (Council of European Energy Regulators) groups the most common functionalities of the Smart Metering system developed by European countries into five main categories: injected and consumed energy; energy interruptions; exceptional energy consumption; connection to open gateway; and possibility of software update [50]. In general, countries are more likely to have remote upgrade and the measurement of injected and consumed electricity than they are to have interruption alerts, exceptional usage alarms, or an open gateway for access and control of consumption. Apart from that, according to a recent survey from the FERC (Federal Energy Regulatory Commission), the uses of Smart Metering in the U.S. are more numerous: enhanced customer service; outage detection; theft detection and other line losses; outage restoration; remote connection/disconnection; power quality; asset management; outage mapping; load forecasting; remote change metering parameters; remotely upgraded firmware; price-responsive demand response; interface pre-pay; pricing/event notification; and HAN applications [17]. Enhanced customer service is the most commonly used service and there is an increased use of newer types of advanced metering functionality, especially the use of advanced metering to perform remote outage management and to remotely upgrade firmware on the advanced meters. The report also highlights the significant increase of Smart Metering penetration from 2006 in the United States.
The following subsections describe the aforementioned features by countries in the most remarkable projects and deployments worldwide.

4.1. Europe

Despite its relatively low starting point, Smart Metering deployments are currently especially successful in Europe, largely due to the legislation of many countries promoting, or even forcing, the replacement of old metering devices with SMs. In fact, legislation for electricity SMs is in place in the majority of the member states of the European Union, providing a legal framework for deployment and/or regulating specific matters such as a timeline of the rollout or setting technical specifications for the meters [51]. According to the European Commission, member states have committed to deploy 200 million SMs by 2020 (Electric Directive 2009/72/EC). This implies that more than 70% of end-users will be covered by Smart Grid technology [52]. Figure 4 shows the evolution of SM rollouts in European countries. In 2013, the total number of installed SMs was estimated at 61 million [53]. Figure 5 depicts an estimation of the total number of installed SMs in Europe by 2020. By mid-2012, there were about 90 Smart Metering pilot projects and national rollouts catalogued in Europe, the most important of which are listed below.
Italy was one of the forerunners of Smart Metering in Europe, as the utility ENEL started deploying SMs in 2001 under the scope of the “Telegestore” project, which employs a combination of PLC (for communication between SMs and substations) and GSM (data gathering of CCs in the backbone). By the end of 2013 its rollout was almost complete (95% of costumers). It is also worth mentioning the “Insernia” project, with approximately 8000 installed SMs implementing PLC, which offers a new approach to demand response and aims at promoting distributed generation [54].
Also by 2013, Sweden was the only member state whose rollout was completed. However, there was no legal decision on the rollout of SMs itself; on the contrary, a legal decision was made to make monthly meter reading available to customers, which in turn led to a decision by distribution companies to roll out SMs in order to meet this requirement [50]. Sweden was a member of the “EnergyWatch” project together with Finland, whose purpose was to help utility consumers to gain awareness, change behavior, and reduce energy consumption and bills [54].
In the Netherlands, from 2012 until 2014 there was a small-scale rollout for experienced purposes. The Dutch parliament evaluated this pilot project and approved additional implementing regulation for the large-scale rollout of SMs from 2015, aiming to have an SM fitted in at least 80% of households and small businesses by 2020 [54]. Additionally, the utility Continuon started in 2006 a pilot project with the installation of 50,000 SMs implementing PLC technology, for both electricity and gas metering, while the company Oxxio started a similar project with SMs implementing GSM/GPRS [56].
The United Kingdom took its first steps towards Smart Metering in 2007 with the project “Energy Demand Research Project” (EDRP), with around 58,000 installed SMs, showing that the combination of an SM and in-home display made a real difference to the level of energy savings that people were able to make [57]. Later, in 2011, the U.K. government announced a mandate consisting on a full rollout of SMs by 2014 and running through 2019 to install 53 million SMs in 30 million homes and businesses. However, in 2013 the government announced that the SM rollout phase would be delayed until 2015 since the communication infrastructure needed further trial and testing [46].
France started a pilot smart meter program for a widespread deployment of 35 million SMs by 2020 [54]. The “Linky” project, led by ERDF, which employs around 250,000 SMs and 4600 DCs, aimed at improving knowledge of residential consumption through the combined effects of an appropriate customer panel and a modeling method adapted to more frequent reading of consumer indices [58].
Spain has also participated in the wide deployment of SMs: almost 2 million SMs by 2013 and a rollout of 100% by 2018, in compliance with a Royal Decree in 2007. A group of Spanish utility companies formed the “Spanish Utility Consortium” to establish the foundation of Spain’s SMs rollout project in 2009 [59]. Two main technologies are present in the rollout: PRIME and Meters and More. While PRIME only can perform over power lines, Meters and More is able to work on power lines, public communication networks, and local optical links.
Although in Germany the installation of SMs has been mandatory after major renovations and in new buildings since 2010, there has not yet been an explicit commitment made to a national rollout. In fact, the rollout to existing homes (up to 500,000 SMs by mid-2012) has remained in a pilot phase. After a report of the Federal Ministry of Economics indicating the lack of economic benefits of a full rollout of SMs for German consumers, Germany has delayed it until at least 2020 [60]. To date, much of the focus has been on pilot projects and small-scale trials, of which five major projects were still ongoing in 2014 [54].
By 2014 Finnish utilities had completed their SM rollouts, covering 98% of all consumers, who now have access to their hourly consumption data through utility online information. In addition, utilities and other market players have introduced further new Smart Metering-based services and products, such as in-home displays, real-time feedback systems, demand response, and smart home products [54].

4.2. America

The Unites States leads the SM rollout in America, with a strong presence of RF-mesh technologies, followed by Canada, while deployments in most countries of Latin America have not started yet. Figure 6 depicts an estimation of the total number of SMs installed in North America by 2020.

4.2.1. The United States

The largest driver of the rollout of SMs in the United States has been the American Reinvestment and Recovery Act (ARRA) program. With the end of ARRA funding, the installation of SMs is moving much more slowly than it did in 2009–2011 [46]. However, the deployment of Smart Metering solutions is still increasing: the Institute for Electric Innovation reported a total of 50.1 million SMs installed in 2014, which implies a penetration rate of 36.3% [61]. Most of the installed SMs are for residential use (43% of U.S. homes have an SM), since many U.S. commercial customers have long had SMs to monitor facility electricity usage more accurately. Applied technologies vary from 2G and 3G for end-users and BB-PLC for HANs. The evolution of installed SMs in the last five years can be seen in Figure 7.
By 2014, more than 43 million out of the 50.1 million SMs were installed by investor-owned utilities, while almost 7 million were installed by municipal and cooperative-owned utilities. Among the Smart Metering systems performed by investor-owned utilities, 16 of them deployed more than 1 million SMs, according to a report published by the Institute for Electric Innovation [62]. The largest deployment was performed by Pacific Gas & Electric utility, with 5.14 million SMs equipped with RF mesh technology in 2013 as part of its SmartMeter Project. The main objectives of the deployment are: (i) customer service (customers with SMs can participate in a voluntary critical peak pricing rate plan that will help manage system load during hot summer days and receive notifications of when they are moving into higher-priced electricity tiers); (ii) demand response, focusing on energy efficiency and renewable energies; and (iii) setting a platform for future innovative solutions such as HAN services and EV appliances [63]. According to the project development report, the most challenging issue has been the coordination and integration with other enterprise initiatives that are part of the project [64]. Another large deployment started in 2007 and finished in 2012, consisting of almost 5 million installed SMs equipped with ZigBee, was performed in California under the SmartConnect program by the Southern California Edison utility. At present, the project offers different tariff rates to consumers. Several appliances and services such as energy storage, distributed control, and artificial intelligence are currently being developed and are expected to be ready by 2020. Specifically, the key roles of SMs in this project are: (i) enabling customers to actively participate in grid operations; (ii) allowing maximum access by third parties to the electric grid; (iii) promoting demand response, energy efficiency, and DG and DS into energy markets; and (iv) lowering the carbon footprint of the electric distribution system. The project reported some disgruntled responses from customers regarding remote supply disconnections and magnetic radiation emissions from SMs [65]. Two more SM deployments are over and above the 4 million installed SMs: the Florida Power and Light Company installed 4.6 million RF mesh-based SMs as part of its Smart Meter program to residential consumers in 2014. In addition to providing several services (such as monitoring their energy use by hour, day, and month as well as the energy they delivered to and received from the company) and reliable supply to customers, FPL plans involve the prediction and prevention of outages through the SMs and the deployment of monitors, sensors, and controls on their transmission and distribution grid [66]. On the other hand, the Southern Company utility installed 4.2 million SMs equipped with RF mesh technology in 2014. The objective of the deployment integrates advanced metering, communications, and other appliances to provide customer service at reduced operating costs [62]. Other remarkable deployments are: Oncor utility with 3.3 million installed RF-based SMs and focused on customer services, power quality monitoring, reliability, and outage prevention [67]; and CenterPoint Energy utility, with 2.2 million RF-based SMs in 2012, with the aim of improving customer service and remote connections/disconnections and enhancing system reliability [68]. Additional Smart Metering deployments in the U.S. are discussed in [62].
U.S. utilities are now focused on integrating and optimizing information gathered by SMs to provide benefits and new capabilities to customers and system operators. Four main areas can be distinguished [62]:
  • Systems integration: the introduction of outage and distribution management systems provides enhanced outage management and restoration services as well as improved distribution system and device monitoring.
  • Integration of new resources: SMs position the grid as platform for the integration of distributed energy resources (DG, DS, EVs, microgrids, etc.).
  • Operational savings: remote activities (reading, connection/disconnection) and the reduction of energy theft are some financial benefits of SMs.
  • New customer services: SMs have enabled services to end-users such as automated budget assistance and bill management tools, energy use notifications, smart pricing, and demand response programs.

4.2.2. Canada

In contrast to other countries, whose Smart Metering initiatives have been highly promoted by governments and laws, in Canada they have also been driven by necessity: there are vast distances and hostile terrains separating power resources from consumers. In fact, Canada’s SG technology is more advanced than that of most other nations [25]. As of June 2014 there were more than 6 million installed SMs and it is expected that two thirds of Canadian households will be equipped with SMs by 2016 [69]. Several provinces (Ontario, British Columbia, Saskatchewan, and Quebec) have already implemented or intend to implement a SM rollout [46]. To date, the Ontario Smart Metering initiative has been identified as one of the most successful deployments of Canada, with almost 4.5 million installed SMs. Initial SM testing involved GSM technology. Then, the utility decided to use radio mesh technology for most customers. The utility also deployed a ZigBee HAN within the SMs to communicate consumption data to market daily; however, they do not have remote connection and disconnection capability [38]. Along with SMs, the government introduced mandatory time-of-use pricing, making Ontario the largest electricity market in the world with mandated time-of-use rates and pilot programs at the start of the implementation showing peak savings of around 5%–8% [70]. However, a recent audit outlines some weaknesses of the deployment such as: (i) lack of cost-benefit study to support the deployment (as done in other provinces and also in Germany, Australia, and the U.K.); (ii) up to 73 distributed companies were in charge of the deployment, with the subsequent difficulty of ensuring a cost-effective implementation of Smart Metering. This situation also led to varied electricity billing amounts; (iii) the time-of-use pricing model has not had the expected impact on reducing peak demand since targets set by the Ministry of Energy have not been met; and (iv) complaints regarding time-of-use rates and billing errors have been reported [71].
Full rollouts of SMs are also taking place in British Columbia and Quebec. In 2011 BC Hydro initiated the Smart Metering Program in British Columbia as a first step towards modernizing BC’s electricity grid, with approximately 1.8 million SMs equipped with RF technology installed in 2012. According to the utility, the SM deployment will detect and reduce energy theft, with subsequent energy savings, and will also enhance power outage control and provide new customer applications such as lower rates and customer money-saving tools [72]. On the other hand, Hydro-Quebec has already installed more than 2.7 million RF-based SMs and continues the rollout throughout Quebec, with an expected total number of 3.8 million SMs by 2017 [73]. The Canadian experience provides a great benchmark from which to learn, as it has already implemented SMs and time-of-use rates for millions of customers [70].

4.2.3. Latin America

The deployment of Smart Metering solutions in Latin America is still poor. Brazil and Mexico are currently the first potential markets and Argentina and Chile are also firm candidates for introducing Smart Metering solutions in the coming years [45].
The energy regulator in Brazil, ANEEL, replaced its ambitious goal of replacing all electricity meters with SMs in 2009 with a revised target of replacing 63 million by 2021 [74]. In 2012, ANEEL scaled down the Smart Metering rollout, making SMs mandatory only for new customers starting in 2014 and optional for existing consumers [46]. According to Brazilian utility companies, 4.5 million SMs are expected to be installed by 2017. The approach of Brazilian Smart Metering deployments is to help reduce fraud, electricity theft, and inefficiency, as occurs in other emerging countries, which cost the country close to $4 billion per year [47].
Mexico is the second-largest potential market for SMs in Latin America after Brazil, and is expected to have 21 million SMs installed by 2020 [74]. Many SG and Smart Metering pilot programs in Mexico are being boosted in an effort to respond to high rates of electricity theft, power outages, and poor energy infrastructure [46].

4.3. Asia-Pacific

China is by far the country with the largest number of installed SMs in the Asia-Pacific region and it is expected to almost double those figures by 2020. Japan has also performed several SM rollouts. The rest of the analyzed countries have also performed some deployments, but less numerous. SM rollouts in India are expected to increase in the coming years. Figure 8 depicts an estimation of the total number of SMs in installed Asia-Pacific countries by 2020.

4.3.1. China

Electricity companies in China continue with an extensive deployment of SMs as part of a national plan that aims to improve the national electricity infrastructure and shift towards green energy supply. This situation has led China to become the largest market for SMs in the world [46]. The installed base of SMs is expected to grow from more than 139 million units in 2012 to 377 million units by 2020, reaching 74% market penetration [75]. The Smart Grid Corporation of China (SGCC) is China’s sole state-owned electric utility company and the largest utility company in the world, covering power supply to 88% of China [76].
The most important SM deployment in China corresponds to the SGCC’s Smart Grid Plan, which aims at developing a modern power grid based on a strong information and communication platform, with an Ultra High Voltage (UHV) grid backbone and subordinate grids coordinated at all levels [76]. By the end of 2011, SGCC had implemented 238 SG pilot projects ranging from connecting wind power plants to automating distribution networks to metering households. Regarding Smart Metering, there were three remarkable deployments: (i) 26 provinces and 2.2 million users in 2009; (ii) 33 million SMs installed in 2010; and (iii) 33 million SMs installed in 2011 [77]. Most of the installed SMs employ PLC; however, SGCC is also running an SG project with 86,000 premises connected to the grid using PON technology [78]. Additionally, under the Smart Grid Plan, SGCC has developed three standards related to Smart Metering: (i) Q/GDW 376.1 (communication protocol between master station and terminals); (ii) Q/GDW 376.2 (interface for local communication module of concentrators); and (iii) Q/GDW 377 (technical specification for security and protection).

4.3.2. Japan

Japan is betting on Smart Metering solutions, especially after the Fukushima earthquake disaster, and they expect to deploy a total of 80 million SMs [46]. The Japanese government has set a target for about 80% of the nationwide electricity consumption to be monitored using SMs, phased from 2015 to 2020. By 2024, virtually all of Japan’s roughly 80 million residential customers are expected to have an SM installed in their homes. The Smart Metering plan deployment has been set with the aim of letting utilities see the demand in real time and adjust pricing accordingly, all without dispatching meter readers. The devices are also expected to encourage customers to save more energy [78]. One of the two main power utilities of Japan, TEPCO, announced that it was expanding its rollout program from 7 million to 27 million SMs—essentially, all the meters of their household customers. Installations began in the first half of 2014 and are to be completed by March 2021 [79]. On the other hand, KEPCO utility has already deployed about 2 million SMs. Smart Metering deployments in Japan employ wireless technologies.
Unlike most other nations, reliability is not considered to be an issue in Japan. The country has already undertaken significant generation and transmission infrastructure improvements as a result of investments beginning in the 1990s. A key focus area for Japan is the introduction of advanced integrated controls for demand side management and connectivity to the end-user [80].

4.3.3. Australia

Australian SG and Smart Metering initiatives are focused on demand management, energy security, and energy efficiency and have been mainly propelled by governmental programs. Additionally, severe energy problems caused by energy shortages suffered in 2006 and 2007 have contributed to the attempt to improve the energy supply system [70]. In fact, in response to those energy shortages, there was a government committed to a national SM rollout as part of the National Smart Metering Program. The rollout areas were chosen from a cost-benefit analysis and the State of Victoria was the first to commence a mandatory rollout of Smart Metering infrastructure, which started in 2009 and finished in 2013 with 2.8 million installed SMs equipped with RF mesh technology and WiMAX. As happened with the Ontario deployment, a ZigBee HAN network was also implemented. The government determined minimum functionality and services to be conformed to by the distributors, specified in terms of four key services: (i) recording of energy imported or exported from a metering point by half-hour trading interval; (ii) remote reading of the SMs; (iii) remote power supply disconnection; and (iv) remote power supply connection [38]. All costs associated with this deployment were passed along to consumers, including the cost of the SM itself, which generated cost concerns from customers. This, together with customer implications and engagement, were identified as the two main problems of the deployment [75]. The Ausgrid utility has also performed several Smart Metering pilots. In 2010 a consortium led by Ausgrid won the tender for the Australian Government's “Smart Grid Smart City” project, consisting of the rollout of up to 50,000 SMs to homes across the trial sites. Residents are able to see a real-time analysis of electricity usage for their households, as well as for individual appliances. The deployment also improves the grid performance by controlling the efficiency and network operations for energy transmission. The project employs LTE for its 4G communications network [39]. Additionally, the “Essential Energy” project, from 2004, consisting of the deployment of SMs for predominately residential customers, started with a size of approximately 2500 SMs equipped with mesh radio and 3G. The pilot assesses demand management trial including in-home displays and critical peak pricing tariffs. The trial confirmed the importance of real-time consumption data in driving energy efficiency since customers involved in the trial achieved an overall reduction in energy consumption and up to 30% reduction in their peak demand [38]. Additional Smart Metering pilots and trials performed in Australia are discussed in [39,81].

4.3.4. India

Although India is one of the fastest-growing economies in the world, its industrial growth has been limited by inadequate energy availability, especially electricity transmission, distribution losses, and a mismatch of supply and demand in electricity [50]. This issue, along with theft, are the major concerns regarding power in India. Consequently, the Indian Ministry of Power is advocating for SG investment to solve those issues and in 2012 unveiled eight SG pilot projects that use a combination of Smart Metering and various technologies to improve the efficiency and reliability of the power system for sustainable growth. Initial steps towards Smart Metering in India have been encouraging, with the market for electricity meters both for static and electromagnetic witnessing a rapid expansion of 32% between 2008–2009 and 2010–2011. Under the India Smart Grid Task Force (ISGTF), an inter-ministerial group initiated by the Ministry of Power, a Smart Meter Task Group was formed to discuss the development of cost-effective metering solutions that can be applied within the Indian context [76]. Some remarkable Smart Metering pilots are the “Puducherry Smart Grid Project,” with more than 1400 SMs equipped with different technologies; the “Bangalore Pilot Project,” which will reach 2000 residential and commercial customers; and the deployment started in 2008 in New Delhi (with 500,000 SMs installed in 2011), where SMs include automated meter reading and a prepaid system utilizing PLC technology [80]. Industry reports estimate that India will install 130 million SMs equipped with both PLC and wireless technologies by 2021 [82].
However, despite the progress in Smart Metering across utilities at pilot level, there are still infrastructural development and capacity building issues that need to be addressed before a large-scale implementation. A considerable percentage of existing SMs are still being read manually; there is an absence of associated infrastructure for meter data analysis and also an insufficient regulatory focus and policy on Smart Metering [76].

4.4. Other Regions

Other regions of the Middle East, such as Libya and the United Arab Emirates, are also starting their path into Smart Metering; Dubai Smart City can be cited as a model. Regarding Africa, utilities from South Africa and Zimbabwe lead the Smart Metering introduction initiative, which is still very poor.

5. Challenges to be Addressed in the Near Future

With the exception of China, the pace of installation of SMs will reportedly slow in the short term, due in large part to a decline in the rate of meter rollouts in the United States and delayed implementation of large projects planned for Europe and Brazil [46]. Additionally, as stated by CEER, despite the many years of assessing European standards, Europe still faces a difficult situation because of the lack of a common standard for SMs and an absence of interoperability. This leads to a lack of economies of scale and innovation in customer services since Smart Metering should act as an enabler of additional services [50]. This situation complicates the penetration of multinational SM suppliers in certain foreign markets due to the imposition of local manufacturing standards that may require significant product modifications [46]. Although most of the countries have followed at least some of the recommendations listed in Table 2, a common approach should be envisaged for defining SMs and their functional requirements. According to the European Commission, the most challenging functionality to deliver relates to the frequency of consumption data update and its availability to consumers and third parties on their behalf [51]. Also data protection and security issues must be addressed. Not all technologies offer the same security levels and this needs to be faced. It is advisable to assess a specific framework and personal data protection must remain a central concern in the development of standards. In addition, most of the Smart Metering communication networks use a low/medium bandwidth, which generates high traffic and limits the quantity of data to be transmitted. Then, more modulation/demodulation devices and additional memory for storing the data logs will be required, with a corresponding increase of costs [83]. In addition, high levels of data traffic may lead to an inefficient system. Techniques such as reduction of data retransmissions and the introduction of hierarchy levels (priorities according to the type of data: measure, control, management, alarm, etc.) can help to improve efficiency in Smart Metering communications.
Additionally, communication systems may also face disturbances: wireless communications suffer interference from surrounding emitting devices and also PLC is affected by the inherent noise from the power cable and the devices connected to it. Those issues can be overcome by using more robust protection codes, redesigning emitting devices, and legislating on electromagnetic interferences [84].
At present, government investments have propelled a large proportion of Smart Metering deployments, especially in Europe. Most utilities are reluctant to invest in new systems and technology without a government mandate or incentive, despite the savings resulting from Smart Metering systems [46]. The European Commission has listed the advised next steps in the deployment of Smart Metering systems as follows:
  • Gain the trust and confidence of consumers. An intensive communication effort is required to convince customers about three key aspects: understanding their rights as consumers, the benefits of installing SMs, and their participation in demand response programs.
  • Achieve an innovative energy services market. Synergies with the ICT sector will be fundamental for promoting an innovative energy services market.
  • Protection of sensitive data. The European Commission and the member states will have to assess the need for specific data privacy and security framework legislation.
  • Management of data. Utilities and the ICT sector will have to work together and explore the possibilities of data management.
  • Functions of SMs. Technical and commercial interoperability in Smart Metering will enable member states to identify common means of achieving cost efficiencies and ensure fit-for-purpose in their rollout.
  • Long-term economic assessment of costs and benefits. A review of the critical parameters used and assumptions made in national rollouts will help to refine technology choices.
In the United States, Smart Metering is still a developing industry. The FERC highlights the lack of integration of HANs with Smart Metering systems, as well as existing uncertainty over the development and evolution of standards and their effect on networking technology, especially regarding HAN integration [17]. Utilities are also concerned about obsolescence, which may be addressed by adopting the most adequate technology for every particular case. Another subject under discussion, barely seen in Europe, refers to the impact of Smart Metering deployment on residential customers and its translation into real bill savings [10]. This issue can be addressed by allowing access to metering data in real time to end-consumers and by offering peak-time rebates. Additionally, most Smart Metering projects in the U.S. have had to deal with a lack of confidence among customers regarding magnetic radiation emissions, remote supply disconnections, and privacy issues [61].


This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (project TEC2015-67868-C3-1-R), the University of the Basque Country (UPV/EHU) within the program for the specialization of the postdoctoral researcher staff, and Microgrids with Renewable Distributed Generation (MIGEDIR) (project 713RT0468), funded by the Science and Technology for Development Iberoamerican Program (CYTED).

Conflicts of Interest

The authors declare no conflict of interest.


  1. The History of Making the Grid Smart. Available online: (accessed on 1 June 2015).
  2. Sensor Monitoring Device, Patent US 3842208 A. Available online: (accessed on 3 June 2015).
  3. Directive 2012/27/EU of the European Parliament and of the Council of 25 October on energy efficiency, amending Directives 2009/125/EC and 2010/30/EU and repealing Directives 2004/8/EC and 2006/32/EC, 2012/27/EU. Official Journal of the European Union. L315/1. 2012. Available online: (accessed on 10 June 2015).
  4. Jaewoo, K.; Jaiyong, L.; Jaeho, K.; Jaeseok, Y. M2M service platforms: Survey, issues, and enabling technologies. IEEE Commun. Surv. Tutor. 2014, 16, 61–76. [Google Scholar]
  5. López, G.; Moreno, J.; Amarís, H.; Salazar, F. Paving the road toward Smart Grids through large-scale advanced metering infrastructures. Electr. Power Syst. Res. 2015, 120, 194–205. [Google Scholar] [CrossRef]
  6. Hossain, M.R.; Oo, A.M.T.; Ali, A.B.M.S. Evolution of smart grid and some pertinent issues. In Proceedings of the 20th Australasian Universities Power Engineering Conference (AUPEC), Christchurch, New Zealand, 5–8 December 2010; Volume 6, pp. 5–8.
  7. Farhangi, H. The path of the smart grid. IEEE Power Energy Mag. 2010, 8, 18–28. [Google Scholar] [CrossRef]
  8. Edison Electric Institute. Smart Meters and Smart Meter Systems: A Metering Industry Perspective. 2011. Available online: (accessed on 6 January 2016).
  9. Murat, K.; Pipattanasomporn, M.; Rahman, S. Communication network requirements for major smart grid applications in HAN, NAN and WAN. Comput. Netw. 2014, 67, 74–88. [Google Scholar]
  10. Depuru, S.S.S.R.; Wang, L.; Devabhaktuni, V. Smart meters for power grid: Challenges, issues, advantages and status. Renew. Sustain. Energy Rev. 2011, 15, 2736–2742. [Google Scholar] [CrossRef]
  11. Chun-Hao, L.; Ansari, N. The progressive Smart Grid System from both power and communications aspects. IEEE Commun. Surv. Tutor. 2012, 14, 799–821. [Google Scholar]
  12. Mohassel, R.; Fung, A.; Mohammadi, A.F.; Raahemifar, K. A survey on advanced metering infrastructure. Int. J. Electr. Power Energy Syst. 2014, 63, 473–484. [Google Scholar] [CrossRef]
  13. IBM Software. Managing Big Data for Smart Grids and Smart Meters. White Paper. 2012. Available online: (accessed on 3 January 2016).
  14. Diamantoulakis, P.D.; Kapinas, V.M.; Karagiannidis, G.K. Big data analytics for dynamic energy management in smart grids. Big Data Res. 2015, 2, 94–101. [Google Scholar] [CrossRef]
  15. Patel, A.; Aparicio, J.; Tas, N.; Loiacono, M.; Rosca, J. Assessing communications technology options for smart grid applications. In Proceedings of the 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm), Brussels, Belgium, 17–20 October 2011; pp. 126–131.
  16. Tortolero, A. The Three Pillars for an Efficient AMI Operation. Schneider Electric White Paper. 2014. Available online: (accessed on 4 January 2016).
  17. Assessment of Demand Response and Advanced Metering. Federal Energy Regulatory Commission (FERC), 2008. Available online: (accessed on 15 October 2015).
  18. Gao, C.; Redfern, M.A. A Review of Voltage Control in Smart Grid and Smart Metering Technologies on Distribution Networks. In Proceedings of the Universities′ 46th International Power Engineering Conference (UPEC), Soest, Germany, 5–8 September 2011.
  19. U.S. Department of Energy. Application of Automated Controls for Voltage and Reactive Power Management. Smart Grid Investment Grant Program; 2012. Available online: (accessed on 4 January 2016). [Google Scholar]
  20. U.S. Department of Energy. Regulators: What the Smart Grid Means to You and the People You Represent. Available online: (accessed on 26 September 2015).
  21. Grigoras, G.; Scarlatache, F. Use of data from smart meters in optimal operation of distribution systems. In Proceedings of the International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), Suceava, Romania, 22–24 May 2014.
  22. Dong, X.; Hongxing, W.; Tianmiao, W.; Suibing, Z. A Smart Metering system for monitoring electricity of building based on wireless network. In Proceedings of the 10th IEEE International Conference on Industrial Informatics (INDIN), Hangzhou, China, 25–27 May 2012.
  23. Depuru, S.; Lingfeng, W.; Devabhaktuni, V. A conceptual design using harmonics to reduce pilfering of electricity. In Proceedings of the Power and Energy Society General Meeting, Minneapolis, MN, USA, 25–29 July 2010.
  24. Xiang, W.; St-Hilaire, M.; Kunz, T. Roadmap of Future Smart Grid, Smart Home, and Smart Appliances. Carleton University: Canada, 2011. Available online: (accessed on 14 December 2015).
  25. Lipošcak, Z.; Boškovic, M. Survey of Smart Metering Communication Technologies. In Proceedings of the EUROCON, Zagreb, Croatia, 1–4 July 2013.
  26. Parikh, P.P.; Kanabar, M.G.; Sidhu, T.S. Opportunities and challenges of wireless communication technologies for smart grid applications. In Proceedings of the Power and Energy Society General Meeting, Minneapolis, MN, USA, 25–29 July 2010; pp. 1–7.
  27. Kirkpatrick, K.; Gohn, B. Smart Grid Networking and Communications; Research Report; Pike Research: Boulder, CO, USA, 2012. [Google Scholar]
  28. Gungor, V.; Sahin, D.; Kocak, T.; Ergüt, S.; Buccella, C.; Cecati, C.; Hancke, G. Smart Grid Technologies: Communications Technologies and Standards. 2011. Available online: (accessed on 4 January 2016).
  29. Accenture. The Role of Communication Technology in Europe′s Advanced Metering Infrastructure. Technical Paper. 2014. Available online: (accessed on 26 December 2015).
  30. The Commission for Energy Regulation. Electricity Smart Metering Technology Trials Findings Report. 2011. Available online: (accessed on 27 December 2015).
  31. IEEE 802.15 Wireless Personal Area Networks. Available online: (accessed on 27 September 2015).
  32. Lu, B.; Gungor, V.C. Online and remote energy monitoring and fault diagnostics for industrial motor systems using wireless sensor networks. IEEE Trans. Ind. Electr. 2009, 56. [Google Scholar] [CrossRef]
  33. Cisco. A Standardized and Flexible IPv6 Architecture for Field Area Networks. White Paper. 2014. Available online: (accessed on 7 January 2016).
  34. Lu, S.C.; Wu, Q.; Seah, W.K. Quality of Service Provisioning for Smart Meter Networks Using Stream Control Transport Protocol; School of Engineering and Computer Science, Victoria University of Wellington: Wellington, New Zealand, 2012. [Google Scholar]
  35. Koay, B.S.; Cheah, S.; Sng, Y.; Chong, P.; Shum, P.; Tong, Y. Design and implementation of bluetooth energy meter. In Proceedings of the Fourth International Conference on Information, Communications & Signal Processing, Singapore, Singapore, 15–18 December 2003; pp. 1474–1477.
  36. Ancillotti, E.; Bruno, R.; Conti, M. The role of communication systems in smart grids: Architectures, technical solutions and research challenges. Comput. Commun. 2013, 36, 1665–1697. [Google Scholar] [CrossRef]
  37. IEEE 802.11™ Wireless LANs. Available online: (accessed on 15 August 2015).
  38. Victorian AMI Rollout-Legislative and Regulatory Framework. 2008. Available online: (accessed on 26 December 2015).
  39. Energy Networks Association. Pilots and Trials Report on Smart Metering and Related Matters. 2012. Available online: (accessed on 6 January 2016). [Google Scholar]
  40. Gungor, V.C.; Sahin, D.; Kocak, T.; Ergut, S.; Buccella, C.; Cecati, C.; Hancke, G.P. Smart grid technologies: Communication technologies and standards. IEEE Trans. Ind. Inform. 2011, 7, 529–539. [Google Scholar] [CrossRef]
  41. Galli, S.; Lys, T. Next generation Narrowband (under 500 kHz) Power Line Communications (PLC) standards. Communications 2015, 12, 1–8. [Google Scholar] [CrossRef]
  42. Gungor, V.C.; Sahin, D.; Kocak, T.; Ergüt, S. Smart Grid Communications and Networking; Türk Telekom Technical Report-11316-01; Türk Telekom: Altındağ, Turkey, 2011. [Google Scholar]
  43. IEC 62056-31:1999 Withdrawn. (accessed on 9 September 2015).
  44. Electa. Study on Smart Meters from the Angles of the Consumer Protection and the Public Service Obligations. 2010. Available online: (accessed on 4 January 2016). [Google Scholar]
  45. Strother, N.; Lockhart, B. Smart Meters. Smart Electric Meters, Advanced Metering Infrastructure, and Meter Communications: Global Market Analysis and Forecasts; Navigant Research: Boulder, CO, USA, 2014. [Google Scholar]
  46. Alejandro, L.; Blair, C.; Bloodgood, L.; Khan, M.; Lawless, M.; Meehan, D.; Schneider, P.; Tsuji, K. Global Market for Smart Electricity Meters: Government Policies Driving Strong Growth. Working Paper; US International Trade Commission, 2014. Available online: (accessed on 28 December 2015). [Google Scholar]
  47. Northeast Group, LLC. Brazil Smart Grid: Market Forecast (2012–2022). 2012. Available online: (accessed on 28 December 2015).
  48. Li, D.; Hu, B. Advanced metering standard infrastructure for smart grid. In Proceedings of the 2012 China International Conference on Electricity Distribution (CICED), Shanghai, China, 10–14 September 2012; pp. 1–4.
  49. ABI Research. Smart Electricity Meters to Total 780 Million in 2020. 2015. Available online: (accessed on 3 January 2016).
  50. Status Review of Regulatory Aspects of Smart Metering. Council for European Energy Regulators (CEER), 2013. Available online: (accessed on 27 October 2015).
  51. Benchmarking Smart Metering Deployment in the EU-27 with a Focus on Electricity. European Commission, 2014. Available online: (accessed on 15 October 2015).
  52. Commission Staff Working Document, “Cost-benefit analyses & state of play of Smart Metering deployment in the EU-27”, COM(2014) 356 final. 2014. Available online: (accessed on 16 October 2015).
  53. Executive Summary; Berg Insight: Göteborg, Sweden, 2013.
  54. USmart Consumer Project. European Smart Metering Landscape Report. 2014. Available online: (accessed on 28 December 2015).
  55. Realizing the Full Potential of Smart Metering. Accenture′s Digitally Enabled Grid Program. Available online: (accessed on 20 September 2015).
  56. Gerwen, R.; Jaarsma, S.; Wilhite, R. Smart Metering; KEMA: Arnhem, The Netherlands, 2006. [Google Scholar]
  57. House of Commons-Energy and Climate Change Committee. Smart meter roll-out-Fourth Report of Session 2013–2014. 2013. Available online: (accessed on 18 November 2015).
  58. Duplex, J.; Gosswiller, S.; Fagnoni, S. A better knowledge of electricity consumption for residential customers through the Linky smart meter. In Proceedings of the 22nd International Conference and Exhibition on Electricity Distribution (CIRED 2013), Stockholm, Sweden, 10–13 June 2013; pp. 1–4.
  59. DNV GL. Smart Grid Data Communication: Accelerating Results in Spain. 2014. Available online: (Accessed on 4 January 2016).
  60. Bayar, T. Will Germany Reject Smart Meters? Available online: (accessed on 26 December 2015).
  61. Federal Energy Regulatory Commission. Assessment of Demand Response and Advanced Metering. 2015. Available online: (accessed on 28 December 2015). [Google Scholar]
  62. Institute for Electric Innovation. Edison Foundation. Utility-Scale Smart Meter Deployments: Building Block of the Evolving Power Grid. Report. 2014. Available online: (accessed on 26 December 2015).
  63. PG & E SmartMeter Program Overview. 2008. Available online: (accessed on 28 December 2015).
  64. Park, E.; Callahan, S. PG & E SmartMeter Project (AMI)—The Intelligent Network. 2006. Available online: (accessed on 26 December 2015).
  65. Nanne, Y. Southern California Edison Smart Meter Deployment. 2014. Available online: (accessed on 27 December 2015).
  66. U.S. Department of Energy. Case Study-Florida Power & Light. 2012. Available online: (accessed on 27 December 2015). [Google Scholar]
  67. Greer, J. Oncor Smart Texas-Focus on Smart Meters. Available online: (accessed on 29 December 2015).
  68. U.S. Department of Energy. Case Study—Center Point. 2013. Available online: (accessed on 29 December 2015). [Google Scholar]
  69. Monitoring Report Smart Meter Deployment and TOU Pricing. 2011. Available online: (accessed on 4January 2016).
  70. The Global Smart Grid Federation Report. 2012. Available online: (accessed on 26 December 2015).
  71. Auditor General of Ontario, Smart Metering Initiative. 2015. Available online: (accessed on 3 January 2016).
  72. BC Hydro. Smart Metering & Infrastructure Program. Business Case. 2014. Available online: (accessed on 2 January 2016).
  73. Hydro-Québec. Next-Generation Meters Project. 2013. Available online: (accessed on 6 January 2016).
  74. PR Newswire. Mexico Smart Grid Market to Reach $8.3 Billion. 2011. Available online: (accessed on 27 December 2015).
  75. PV Magazine. Smart Meter Market Is Hotting Up in China. 2013. Available online: (accessed on 26 December 2015).
  76. Asian Power. Metering India Smartly. 2012. Available online: (accessed on 7 January 2016).
  77. China′s Power Sector, Smart Grid Strategy and Investment Climate. 2011. Available online: (accessed on 7 January 2016).
  78. China Tests a Small Smart Electric Grid. MIT Technology Review. 2013. Available online: (accessed on 7 January 2016).
  79. Global Smart Meter Unit Shipments Will Peak; Navigant Research: Boulder, CO, USA, 2013.
  80. SAIC. Smart Grid around the World-Selected Country Overviews. 2011. Available online: (accessed on 4 January 2016). [Google Scholar]
  81. Moore, K. Overview of the Victorian Smart Meter Program. 2015. Available online: (accessed on 26 December 2015). [Google Scholar]
  82. Goswami. Smart Metering: Energizing India. 2012. Available online: (accessed on 22 December 2015).
  83. Alexander, B. Smart Meters, Demand Response and “Real Time” Pricing: Too Many Questions and Not Many Answers. 2007. Available online: (accessed on 16 October 2015).
  84. Bartak, G.F.; Abart, A. EMI of Emissions in the Frequency Range 2 kHz–150 kHz. In Proceedings of the 22nd International Conference on Electricity Distribution (CIRED), Stockholm, Sweden, 10–13 June 2013.
Figure 1. Evolution of Smart Metering [8]. Reprinted with the permission of the Edison Electric Institute, “Smart Meters and Smart Meter Systems: A Metering Industry Perspective”, published by the Edison Electric Institute, 2011.
Figure 1. Evolution of Smart Metering [8]. Reprinted with the permission of the Edison Electric Institute, “Smart Meters and Smart Meter Systems: A Metering Industry Perspective”, published by the Edison Electric Institute, 2011.
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Figure 2. Communications node segmentation by technology, world markets, 2011–2020 (Source: Navigant Research [27]). Reprinted with the permission of Navigant Research, “Smart Grid Networking and Communications”, published by Navigant Research, 2012.
Figure 2. Communications node segmentation by technology, world markets, 2011–2020 (Source: Navigant Research [27]). Reprinted with the permission of Navigant Research, “Smart Grid Networking and Communications”, published by Navigant Research, 2012.
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Figure 3. Evolution of SM deployment worldwide (Source: Navigant Research [45]). Reprinted with the permission of Navigant Research, “Smart Electric Meters, Advanced Metering Infrastructure, and Meter Communications: Global Market Analysis and Forecasts” published by Navigant Research, 2014.
Figure 3. Evolution of SM deployment worldwide (Source: Navigant Research [45]). Reprinted with the permission of Navigant Research, “Smart Electric Meters, Advanced Metering Infrastructure, and Meter Communications: Global Market Analysis and Forecasts” published by Navigant Research, 2014.
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Figure 4. SM rollout status in Europe by country (Source: European Commission [52]). Reprinted with the permission of the European Commission, “Cost-benefit analyses & state of play of Smart Metering deployment in the EU-27”, published by the European Commission, 2014. © European Union, 1998–2016.
Figure 4. SM rollout status in Europe by country (Source: European Commission [52]). Reprinted with the permission of the European Commission, “Cost-benefit analyses & state of play of Smart Metering deployment in the EU-27”, published by the European Commission, 2014. © European Union, 1998–2016.
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Figure 5. Estimation of the total number of SMs installed in Europe by 2020 (Source: Accenture [55]). Reprinted with the permission of Accenture, “Realizing the Full Potential of Smart Metering”, published by Accenture, 2015.
Figure 5. Estimation of the total number of SMs installed in Europe by 2020 (Source: Accenture [55]). Reprinted with the permission of Accenture, “Realizing the Full Potential of Smart Metering”, published by Accenture, 2015.
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Figure 6. Estimation of the total number of SMs installed in North America by 2020 (Source: Accenture [55]). Reprinted with the permission of Accenture, “Realizing the Full Potential of Smart Metering”, published by Accenture, 2015.
Figure 6. Estimation of the total number of SMs installed in North America by 2020 (Source: Accenture [55]). Reprinted with the permission of Accenture, “Realizing the Full Potential of Smart Metering”, published by Accenture, 2015.
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Figure 7. Evolution of SMs installed in recent years in the U.S. [62]. Reproduced with the permission of A. Cooper, “Utility-Scale Smart Meter Deployments: Building Block of the Evolving Power Grid”; published by Edison Foundation, 2014.
Figure 7. Evolution of SMs installed in recent years in the U.S. [62]. Reproduced with the permission of A. Cooper, “Utility-Scale Smart Meter Deployments: Building Block of the Evolving Power Grid”; published by Edison Foundation, 2014.
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Figure 8. Estimation of the total number of SMs in installed Asia-Pacific countries by 2020 (Source: Accenture [55]). Reprinted with the permission of Accenture, “Realizing the Full Potential of Smart Metering”, published by Accenture, 2015.
Figure 8. Estimation of the total number of SMs in installed Asia-Pacific countries by 2020 (Source: Accenture [55]). Reprinted with the permission of Accenture, “Realizing the Full Potential of Smart Metering”, published by Accenture, 2015.
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Table 1. Minimum requirements for electricity SMs according to 2012/148/EU recommendations.
Table 1. Minimum requirements for electricity SMs according to 2012/148/EU recommendations.
2012/148/EU Recommendation
  Provide readings directly to the consumer and/or any third party.
  Update the readings frequently enough to use energy saving schemes.
Metering Service Operator
  Allow remote reading by the operator.
  Provide bidirectional communication for maintenance and control.
  Allow frequent enough readings to be used for networking planning.
Commercial Service Issues
  Support advanced tariff system.
  Allow remote ON/OFF control supply and/or flow or power limitation.
Security and Data Protection
  Provide secure data communications.
  Fraud prevention and detection.
Distributed Generation
  Provide consumed, generated, and reactive metering data.
Table 2. Planning considerations for a Smart Metering system.
Table 2. Planning considerations for a Smart Metering system.
Planning Aspects
TechnologicalElection of the most suitable technology according the final end
Implementation of software
Physical aspectsResilience and strength
CommunicationType of network (wired, wireless, hybrid)
Range of network
Quality of signal
Security & privacy
CostsCosts of devices
Costs of communication network infrastructure
CustomersService providing
Access to personal data
Table 3. Main technologies and features for Smart Metering systems.
Table 3. Main technologies and features for Smart Metering systems.
WirelessData RateFrequency BandsDistanceAdvantagesDrawbacksDeployments/Projects
RF- Mesh-902–928 MHzDepends on hopsCoverage can be increased with multiple hops. Ad hoc communication links formed dynamically.Tends to be a proprietary offering. Performance decreases over long distances.Most rollouts in USA
Cellular3G–4G60–240 kbps824–894 MHz
1900 MHz
Up to 50 kmWide-range coverage Low maintenance Low power consumption High flexibilityIndividual connections are expensive. Moderate bit ratesChina Southern Power Grid (CHN) Smart Grid Smart City (AUS) Essential Energy (AUS)
GSM14.4 kbps max.900–1800 MHz1–10 kmTelegestore (IT)
GPRS170 kbps max.900–1800 MHz1–10 kmPRICE-GEN (ES) Eandis and Infrax (BE) Linky (FR)
IEEE 802.15 GroupZigBee20–250 kbps868 MHz/915 MHz/2.4 GHz10–1000 mLow cost Low power consumptionLow bit rates Security issues (specially Bluetooth)Energy Demand Research Project, EDRP (UK) National Smart Metering Programme, NSMP (IRL)
Bluetooth721 kbps2.4–2.4835 GHz1–100 m
IEEE 802.11 GroupWi-Fi54 Mbps max.2.4 GHz/5.8 GHzUp to 100 mHigh degree of reliability and availabilityAffected by surrounding emitting devicesCMP AMI (US) National Smart Metering Programme, NSMP (IRL)
Enhanced Wi-Fi54 Mbps max.2.4 GHz
IEEE 802.11 n600 Mbps max.2.4 GHz
IEEE 802.16WiMAX70 Mbps1.8–3.65 GHz50 kmGood performance over larger distances Able to supply thousands of end-usersHigher costs than similar technologiesVictorian Smart Meter Rollout (AUS)
WiredData RateFrequency BandsDistanceAdvantagesDrawbacksDeployments/Projects
NB-PLCup to 500 kbps3–500 kHzSeveral kmMedium already deployed Devices do not depend on batteries.Power cables are a harsh medium for communications.Most rollouts in Europe and China Telegestore (IT) Woodruff Electric Cooperative (USA) Pacific Northwest Boulder SmartCityGrid (US) PRICE-GEN (ES) Eandis and Infrax (BE) Linky (FR) Energy Demand Research Project, EDRP (UK)
BB-PLCUp to several hundred of Mbps1.8–250 MHzSeveral km
xDSLADSL800 kbps upstream 8 Mbps downstreamFrom 25 kHz to 1 MHz5 kmMedium already deployed Quite high data ratesHigh maintenance costs Efficiency decreases with distancePRICE-GEN (ES) Eandis and Infrax (BE)
HDSL2 Mbps3.6 km
VHDSL15–100 Mbps1.5 km
EuridisIEC 62056-319.6 kbps80 MHz–1 GHzHundreds mLow cost Known technologyLow data ratesWide rollout of SMs in France
PON155–2.5 Gbps500 MHz-km60 kmHigh data rates Noise immunity Good performance over kmHigh costBoulder SmartCityGrid (US) PRICE-GEN (ES) Austin (US)

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Uribe-Pérez, N.; Hernández, L.; De la Vega, D.; Angulo, I. State of the Art and Trends Review of Smart Metering in Electricity Grids. Appl. Sci. 2016, 6, 68.

AMA Style

Uribe-Pérez N, Hernández L, De la Vega D, Angulo I. State of the Art and Trends Review of Smart Metering in Electricity Grids. Applied Sciences. 2016; 6(3):68.

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Uribe-Pérez, Noelia, Luis Hernández, David De la Vega, and Itziar Angulo. 2016. "State of the Art and Trends Review of Smart Metering in Electricity Grids" Applied Sciences 6, no. 3: 68.

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