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Energies
  • Review
  • Open Access

7 May 2016

A Review of Systems and Technologies for Smart Homes and Smart Grids

,
and
1
Department of Architectural Design, History and Technology, Norwegian University of Science and Technology (NTNU), Trondheim NO-7491, Norway
2
Department of Civil and Transport Engineering Norwegian University of Science and Technology (NTNU), Trondheim NO-7491, Norway
3
Department of Computer and Information Science, Norwegian University of Science and Technology (NTNU), Trondheim NO-7491, Norway
*
Author to whom correspondence should be addressed.
This article belongs to the Special Issue Energy Efficient Building Design 2016

Abstract

In the actual era of smart homes and smart grids, advanced technological systems that allow the automation of domestic tasks are developing rapidly. There are numerous technologies and applications that can be installed in smart homes today. They enable communication between home appliances and users, and enhance home appliances’ automation, monitoring and remote control capabilities. This review article, by introducing the concept of the smart home and the advent of the smart grid, investigates technologies for smart homes. The technical descriptions of the systems are presented and point out advantages and disadvantages of each technology and product today available on the market. Barriers, challenges, benefits and future trends regarding the technologies and the role of users have also been discussed.

1. Introduction

The European Standard EN 15232 [1] and the Energy Performance of Building Directive 2010/31/EU [2], which is in line with Directive 2009/72/EC as well as the Energy Road Map 2050 [3], promote the adoption of smart home technologies to reduce energy usage in the residential sector. In the current era of Internet of Things, their development has been recognized as having significant potential to create an interactive energy management system for homes [4]. The new information and communication technologies (ICTs) are, therefore, becoming increasingly embedded in the society by allowing faster and more efficient interaction between users and both public and private environments. They are making people’s lives simpler and better especially in their home environments.

2. State of the Art

In the near future, all homes will have the dedicated artificial intelligence, computational power, communication skills, monitoring and controlling abilities needed to improve everyday activities. A more efficient interaction between people and home appliances will be devoted to improve comfort, healthcare, safety, security and energy savings [5,6]. Homes will hence become smart homes.

2.1. The Advent of Smart Homes

The interaction between humans and their surroundings can take place in different ways. People usually do everyday activities at home and numerous advantages would be gained if the environment could react to humans’ behavior and gestures. The smart home is an intelligent space that is able to respond accordingly to the behavior of residents [7].
The concept of smart homes has been developed since the 1990s. According to one of the most recent definitions provided by Satpathy, “a home which is smart enough to assist the inhabitants to live independently and comfortably with the help of technology is termed as smart home. In a smart home, all the mechanical and digital devices are interconnected to form a network, which can communicate with each other and with the user to create an interactive space” [8]. Alam and Ali [5] define the smart home as an application that is able to automatize or assist the users through different forms such as ambient intelligence, remote home control or home automation systems. These descriptions confirm that, the primary objective of a smart home is to increase occupants’ comfort and make daily life easier [9]. This goal might be achieved, in two ways: (i) by identifying the relevant human activities and increasing their automation in home environments, or (ii) by using remote home control in order to provide high comfort levels, improve security, facilitate energy management, reduce environmental emissions and save energy [10,11]. Smart homes aim to establish a better quality of living by deploying fully-automated control of appliances and providing assistive support [5]. They allow energy efficiency to be enhanced by adapting the operation of devices to occupancy. In a smart home, users and appliances are (inter)connected by an enhanced communication network comprising twisted-pair power lines or fiber optics, which transfer digital signals according to a given communication protocol. Most smart homes have a central communication device, which enables occupants to control home appliances remotely [12]. According to Le et al. [13], smart homes have the following five fundamental characteristics:
  • Automation: the ability to accommodate automatic devices or perform automatic functions;
  • Multi-functionality: the ability to perform various duties or generate different outcomes;
  • Adaptability: the ability to learn, predict and meet the needs of users;
  • Interactivity: the ability to allow the interaction among users;
  • Efficiency: the ability to perform functions in a convenient manner that saves time and costs.
However, despite their features, smart homes do not automatically become components of the smart grid [14,15,16].

2.2. The Advent of the Smart Grid: A Communication Method for Smart Homes to Overcome Traditional Power Grids

Given the rapidly rising electricity usage in private households and the increasing of environmental and regulatory restraints, the need to improve the overall efficiency of electrical grids has never been greater. Energy efficiency is hence one of the central issues that smart homes and smart grids have to face. Smart technologies monitor household energy usage, and users can control home electricity usage through a direct and bidirectional communication with home appliances. It is also expected a lower fluctuation in the load and a subsequent reduction of network dynamics, higher stability, fewer line losses, and lower operational costs in terms of matching the energy demand with the offer [17]. This is one of the strategies that appears promising to cover the performance gap created by the predicted energy performance of a building and its actual energy usage. Considering that primary energy used in buildings worldwide accounts for approximately 40% of global primary energy usage [18], the improvement of energy efficiency in buildings constitutes a critical issue concerning primary energy saving and a corresponding carbon footprint reduction [19]. This has been the motivation for the development of smart homes, in which almost all the appliances are locally manageable and controlled in real-time [17]. Several studies discuss the effect of providing feedback on energy usage to users employing different technologies [20]. It was found that, displaying real-time information on electricity usage to users, they effectively modify their behavior achieving energy saving of up to 30% [20]. In that regard, smart grids enable communication among buildings, as well as among energy generation systems.
Although the traditional power grid has been serving humanity for about the last 100 years, it is now inadequate to face the increased demand for electricity and the deployment of sensors, active automation tools and bidirectional communication [21]. This last aspect is the most relevant feature that promotes the advent of smart grids. The traditional vision of energy production and consumption is changing because users are starting to generate and use their own energy locally, even if they are not always the only or final consumers of their generated energy. The surpluses are exported to the grid, which means that electricity transfer has to be bidirectional, i.e., energy has to flow in the two directions. In this sense, a smart grid differs from a traditional power grid through its ability to predict, monitor and manage the bidirectional energy flows. It collects information on users’ behavior and actions of the various connected items in order to ensure that energy demand and supply are well balanced as well as energy is efficiently used. Smart homes hence represent the main element of the smart grid where the monitoring of real time energy and environmental data allows energy control and electricity price forecasting at transmission and distribution levels [22].

2.3. The Role of the ICTs in Smart Homes and the Smart Grid

As confirmed by recent studies [23,24], some of the most important advantages provided by the smart grid derive from its capability of improving performance reliability and customers’ responsiveness [22]. The rapid advancements in ICT solutions and smart metering are well suited to tackling the aforementioned limitations of existing power grids. The conversion of traditional electricity grids into smart grids ensures productive interactions among energy providers, users and other stakeholders [25]. The advent of smart grids has fostered the deployment of smart meters, low-cost sensors and smart load devices, and the integration of ICTs in residential energy management programs [19,26]. The integration of advanced ICTs increases the efficiency of the traditional grid by providing more automation, a reliable forecast of electrical loads, and a safer operation of electrical appliances, resulting in a rise in the quality of the energy delivery service and a higher overall user satisfaction [27].
New ICT infrastructures supporting a more efficient smart grid will also include frequent price updates to follow the evolution of the balance between supply and demand in near real-time [22]. They can be set to follow load-shifting programs that offer customers a more effectively way to manage the cost of their electricity bill. They work by storing relatively inexpensive electricity during off-peak demand periods and using this stored energy during peak periods, when electricity energy prices are high. These actions allow users to reduce the cost of their electricity bill and save energy [28].
Another possibility that can consistently contribute to energy saving in buildings is to use more efficient appliances. A study conducted by Berardi’s [29] estimated how much energy can be saved using highly efficient appliances in households: up to 20% in China [30], by 30% in India [31] and by 27% in Brazil [32]. The same strategy is being adopted in the US where, during the last few years, electricity consumed in buildings has slightly increased because the use of appliances, electronics, and electric lighting has risen from 24% in 1993 to more than 34% in 2009 [29].
The new method of energy distribution made possible by the advent of the smart grid has contributed to improving energy savings in the building sector. In recent years, several studies in this field supported by the European Community focused on the analysis and optimal design of modern distribution systems that aim to minimize the operational cost and maximize the profit of the users [33].
To achieve high energy efficiency in the smart grid, distributed energy resources have to be well managed and load can be reduced implementing a demand-response (DR) approach. Residential DR is strictly related to the users’ behavior. It is also often linked to the price of energy during the day [34].

2.4. The New Role of the Users

Changes in the users’ behavior are also another important factor in relation to the improvement of the energy performance of buildings. The data from Intergovernmental Panel on Climate Change (IPPC) showed that behavioral changes could affect energy savings in lighting by up to 70% [35]. Recently, users have become more conscious of energy usage in buildings and are increasingly interested in real-time energy monitoring and controlling devices and tools [36]. Furthermore, the market for residential energy management is poised to grow dramatically due to increased users’ demands and new governmental and industry initiatives [37]. Different energy efficient routing protocols and energy management systems have been proposed [38,39,40] to provide information about energy usage patterns. They offer users actionable information and control features while ensuring ease of use, availability, security, and privacy [41].

3. Aim of the Work

This article aims to present a systematic review of existing software, hardware, and communications control systems for smart homes currently available on the market. It gives an overview of the status of smart home technologies by discussing the main relevant features and pointing out the strengths and weakness of each technology and product. It is a guide for users, who need to choose the technology that best suits their needs.

4. Classification Criteria for the Selection of Smart Home Technologies

The existing communication networks strive to increase the exchange of information among utilities, home appliances, and users. The diverse directionality and complexity of the existing communication devices represent a challenge. The growing trend is the development of bidirectional communication using a Home Automation Network (HAN) to monitor and control home appliances; de facto realizing a demand-response (DR) system. According to a report published by the American Council for an Energy-Efficient Economy [42], some of the systems from among the new feedback initiatives that make energy resources visible to residential users achieve the maximum feedback-related savings. If all systems are to do this, they will require a combination of useful technologies with well-designed programs that successfully inform, engage and motivate the users via the following determining factors [43]:
  • Data collection: the technology allows the collection of all relevant data and provides access to them;
  • Data processing: the technology allows the processing and analyzing of relevant data and can combine them;
  • Data representation: the technology allows the relevant data to be made accessible to the users;
  • Control and interaction capabilities: the technology enables users to access the status and monitor the functions of related technologies (bidirectional communication and interaction).
These factors need to be considered when tailoring the data that should be provided to end-users [44,45]. Collected data can be shown to users as: (i) direct feedbacks, which are the representation of the collected data typically provided in real-time; and/or (ii) indirect feedbacks, which are derived from a post-processing task and provided after the energy usage has occurred. Direct feedbacks are: real-time plus feedback (i.e., real-time information about the level of energy used by the appliance), real-time feedback (i.e., real-time premise level information), while indirect feedbacks are daily or weekly feedback, which is that are household-specific information and advice on a daily or weekly basis, estimated feedback (i.e., typically web-based energy audits with information supplied on an on-going basis), and enhanced billing (i.e., household-specific information and advice) [42]. Figure 1 shows the percentages of annual household electricity savings based on 36 studies implemented between 1995 and 2010 [42].
Figure 1. Average household electricity savings disaggregated by feedback type. Modified from reference [42].
Data can be presented in different ways, for example energy, peak power, cost, ecological footprint etc. and they can be compared with benchmarks and historical trends, but, to be effective, feedbacks to the end-users should be:
  • Direct: the more immediate the feedback is, the more effective it is, but it requires a certain degree of knowledge and preparation from users;
  • Personalized: the way of presenting data is customized to end-users’ needs;
  • Comparable: end-users can compare their actual electricity usage with benchmarks as well as with their historical data;
  • Flexible: the feedback technology needs to be continually improved, in response to users’ suggestions and requests.
It is also clear from the literature that the way to communicate the feedbacks to the end-users involves two main approaches:
  • Systemic: the house exists in a systemic context, and the data, retrieved by means of a smart grid, are presented at an individual household level and compared with the average system performance [45].
  • Gamification: the feedback is presented by using elements and concepts that are typical in computer games and is often integrated in a graphical user interface (GUI).
In the following sections, the most relevant technological devices and integrated software or applications today available on the market for improving the interaction between users and home appliances are presented, compared and discussed.

5. Review of the Technologies for Smart Homes

The most relevant technologies for smart homes discussed in this article, were grouped according to the following four categories:
  • Integrated wireless technology (IWT);
  • Home energy management system (HEMS);
  • Smart home micro-computers (SHMC);
  • Home automation (SHS/HA).
Table 1 collects and organizes all the analyzed technologies, systems and products.
Table 1. Summary of the analyzed smart home technologies.

5.1. Integrated Wireless Technology and Network

Several studies on information and communications technologies for smart grids and smart homes can be found in literature [46]. Parikh et al. [47] presented several wireless communications options. They discuss the main challenges of each wireless technology. IWT is a communication commonly used within an office building, a private home or any other residence in order to allow internal and external short-range communication throughout smart home technology. IWTs are often preferred to wired technologies. The use of wired solutions, would be economically and/or physically prohibitive for many smart grid applications. Instead, wireless technologies give benefits such as a lower cost of equipment and installation, a quick deployment, widespread access and greater flexibility [48,49].
Furthermore, IWT systems could be implemented through a GUI to monitor and control home appliances remotely. It allows integration and communication within home energy management systems, whereas IWT has some disadvantages when integrated into a smart grid. They do not currently include local renewable energy generation systems such as Photovoltaic (PV) panels.
In this section, the most used wireless communication technologies (WCTs) and network protocols suitable for home area networks are discussed and compared (Table 2).
Table 2. Comparison among the different integrated wireless technologies.
Figure 2 shows the top-level architecture of a smart home. It includes a server/gateway/router as a connection within the house and to the smart grid. These can be installed using one or a combination of the available external networks such as phone lines, digital subscriber lines (xDSL), cable, and power line networks.
Figure 2. Top-level architecture of a typical smart home. Modified from reference [50].

5.2. Home Energy Management

Development of the home energy management system (HEMS) started due to the energy shortage and the effects of global warming. Since its first application in 1976 [67], it has become one of the most popular research topics. The HEMS allows the energy usage of a building to be managed and controlled automatically and helps reduce peak demand for electricity and users’ electricity bills [41].
The number of HEMS installations is rising in areas of North America and Europe that have a high latitude, because of the number of hours of darkness each year. In those areas, the HEMS reduce quite significantly the total electricity demand: up to 30% of the electricity load takes place during peak hours. The peak load can be reduced by, on average, 30% and the operational cost of electricity by 23% [26,68,69].
In smart grids, the use of energy management systems has become a priority to distribute locally the energy generated by users according to the prices of the energy, which is regulated by daily rates. A future trend might be operating using specific hourly rates, i.e., real time pricing (RTP), time of use (ToU), inclining block rates (IBR), critical peak pricing (CPP) etc.
If this method is used, the HEMS will improve the number of products that customers could use to perform daily tasks such as viewing data on energy usage, controlling thermostats, and individual home appliances, looking at tips on ways to save energy, manage a profile for participation in demand-response programs, and viewing their account and billing information. According to LaMarche et al. [69] and Green Tech Media [70], all types of products available on the residential market can be divided into three categories (control devices, graphical user interfaces, and enabling technologies) that include the fundamental aspects summarized in Table 3.
Table 3. Descriptions and examples of HEMSs. Source: [69].
The advantages of the HEMS are:
(i)
The increased savings for both users and utilities providers;
(ii)
A reduced peak-to-average ratio and peak loads;
(iii)
They can include local energy production from renewable sources;
(iv)
They allows the household to be inserted in a systemic context, as a separate local grid, and allow it to be connected to the outside world, i.e., creates a smart grid;
(v)
They allow for historical comparisons of home energy usage.
The use of a centralized control function for the user interface, which includes a control for the use of appliances, is recommend and it would be useful to educate the end-users on how to use the integrated automated controls systems to avoid having automation that the end-users do not know to operate properly. Although, it would be necessary to develop a tailor-made user interface for a HEMS to work in smart homes, HEMS would enable the use of locally generated energy, the integration of energy storage, and an efficient connection with a smart grid. A comparison of the analyzed HEMS available on the market is presented in Table 4.
Table 4. Comparison of the analyzed HEMS.

5.3. Smart Home Micro-Computers

Smart Home Micro-Computers (SHMC) are small-sized computers that are connected to other devices in order to automatize and control the whole smart home system. They consist in a microcontroller with complementary components that facilitate programming and incorporation into other circuits. An important aspect is their standard connectors, which lets users be connected to a central processing unit (CPU) board to a variety of interchangeable add-on modules known as shields. They allow the users make interactive projects and applications with the environment by using multiple extensible connectors and by receiving inputs from many sensors and affect its surrounding by controlling lights or other actuators.
In literature, there are some examples of applications where SHMCs have been combined with wireless sensors to create home automation systems to monitor and control home appliances [81].
The strengths and weaknesses of each SHMC have been summarized in Table 5.
Table 5. Strengths and weaknesses of the analyzed SHMCs.

5.4. Home Automation Systems

Home Automation (HA) provides an intelligent interface that monitors and learns the users’ habits and might anticipate and facilitate their movements. HA can make life easier and more comfortable or provide some energy efficiency savings by interacting with users remotely [82].
HA provides part of the system for managing the smart home. However, the HA system would need to be combined with non-automated devices for user interaction. For example, using only HA systems would not provide users with the ability to adjust their energy usage. But provided that, feedback is given to end-users based on the control activities performed as part of the smart home automation system. Such technology could well be included into an intelligent system that saves energy and improves thermal and visual comfort in the home by implementing both short-term and long-term thermal and visual discomfort indices [83,84]. Some of the most adopted HA systems available on the market are described in Table 6.
Table 6. Features, strengths, and weakness of the analyzed HA systems.

6. Discussion

In this section, the actual and future benefits and challenges related to the presented technologies will be discussed from different perspectives.

6.1. Challenges Related to Smart Home Technologies

The need for energy management systems is thus motivated by (i) the possibility of efficiently managing energy flows by using intelligent commands and a supervision system that is capable of interacting with both loads and generations to balance demand and supply, and (ii) the possibility of interacting with the external network to plan the production levels that are necessary to benefit economically from exchanging energy with the grid [111].
Integration of the forecasting models, which are able to predict hourly power generation according to the weather forecasting inputs could make an optimal operation schedule in such a way that economically optimized power dispatch can be maintained to fulfill certain load demand. Some studies show that this would reduce daily costs by 28%. Further research could be performed to improve this method by including more relevant factors, such as the industrial and commercial profiles of a city or region [112].
Peak demand charge is one of the major components of a customer’s power bill and is the calculation of the amount of energy required during the peak demand periods. To cover the peak demand, utility companies are compelled to purchase reserves that remain untapped most of the time and are, only to be used for short periods of high demand or during failure of other reserves.
Furthermore, smart homes are basically equipped with renewable energy generation technologies. Unfortunately, local energy generation from renewable energy sources (RES) and energy requirements are misaligned. Therefore, a smart technology might be able to modify indoor environmental conditions to time shift energy requirements from peak to off-peak hours. Moreover, if the building is equipped with an electric storage, energy from RES can be used to charge the storage when the electricity cost is low, and discharge the storage during high-cost periods. Thus, the use of storage in conjunction with RES might help optimize the cost effectiveness of a smart home. A renewable energy time shift is particularly valuable for intermittent sources [113].

6.2. Challenges, Benefits, and Motivations Related to the Users

Due to the direct involvement of end-users in the energy management of the power grid, the issue of load level has gained increasing interest in the last few years also considering that the unpredictable human factors can have significant influences on DR system’s performance and the energy management of homes. A study conducted in Denmark investigated the heat usage in 290 identical homes. It was found that the highest heat consumption was up to twenty times higher than the lowest due to the occupant’s behavior [114]. Users’ habits play a key role related to energy use [115,116]. Other studies [34,111,117] pointed out that users can efficiently operate in a real-time frame to optimally control all major residential energy loads, storage and production components while properly considering the customers’ preferences and comfort level. The main objective functions for the operation of each household appliance are electricity payment minimization [22]. Therefore, users are becoming aware that they can manage energy resources and have an active role in the operation of the energy system by using the following strategies related to smart grids via their smart home technologies:
(i)
Rationalizing the amount of energy required from controllable loads: smart grids enable providers to better control and plan production and to adjust the price levels of electricity. Previous studies have systematized approaches to home energy management, which may belong to one or any mix of the following three categories: (i) a technology-oriented approach; (ii) an economically-oriented approach or (iii) an environmentally-oriented approach.
(ii)
Wisely scheduling running times for smart appliances that are likely to be shifted in time. Households’ involvement in cutting their overall energy demand and the evening peaks in energy usage is still being explored. Currently, a lot of interest is being directed to making homes more flexible energy users. This flexibility aims to modify households’ load shape thanks to feedback on real-time energy usage and an indication from them of which tariff information they found useful in relation to optimizing their energy costs.
(iii)
Turning themselves into potential carbon-free generators of energy, through the use of renewable resources: so far, the focus of smart grid technologies has been on integrating RES into the grid to reduce the cost of power generation. Integrating these resources requires storage systems. Load/generation shifting can be used by customers, utility providers, or renewable power producers to take advantage of the different electricity rates available at various times of the day [113].
Although the potential benefits of an active management of homes’ energy use are significant, households as energy users are still subject to several concerns that could inhibit a rapid adoption of smart home technologies. The most significant concern is that, in order to maximize the benefits of smart grids, utility providers’ and suppliers’ of energy management solutions must adapt existing technological infrastructures to new bidirectional and dynamic loads. Therefore, the capabilities and the advantages of these systems are currently not fully deployed. This is one reason why widespread adoption of smart technologies in homes has been hindered [118]. Several experiments conducted on users’ behavior have demonstrated that energy management systems for residential applications allow energy costs to be reduced by about 18%, while preserving the user comfort [22].

6.3. Barriers and Futures Trends

Future research should be continued to develop algorithms and to study human habits to improve the efficiency and flexibility of the energy management strategy [119]. The potential benefit of communicating households energy usage in a systemic context, i.e., considering the dwelling as a part of a smart grid, has also been explored and has been recognized as a significant potential driver for the deployment of energy management solutions in households [45].
The effect of feedback on end-users has been proven to be more effective the more direct it is. Furthermore, the representation of data should ideally be personalized to fit end-users’ needs, habits, and education. Supplying users with the possibility of comparing their home energy usage with benchmarks as well as with their own historical data has also been shown to be an advantage. However, what is a relevant comparison will also vary among the users. For instance, a few user may be interested in comparing their own usage with that of others, hence adding a reference element, while others may not be interested at all in competing in this context. Moreover, users may by grouped according to different rules, e.g., per homes of comparable size, buildings with analogous occupation time, or buildings with similar average energy usages [45]. The most challenging aspect of users’ motivation is that whichever type of feedback is used, the technology needs to be continually developed to meet the challenge of domestication. The process implies that end-users adapt the technology according to their own needs and expectations. However, this process has, from a visualization point of view, an adverse side effect [120]: any positive effect of any visualization methods used for end-users’ benefit eventually stop as part of the domestication process. Consequently, any management system, independent of how effective it might prove to be, will only remain effective if the presentation of data is flexible and can be adjusted to vary over time [118]. The challenge lies in offering the end-users not only relevant data but also continual involvement in this adaptation and customization process.
Recently, the potential of offering gamification, i.e., the use of videogame elements and concepts from non-gaming contexts to improve user experience and engagement with an interface has started to be explored [121]. Having the option to compare own energy usage with that of others may include a potential gamification element.
Finally, another significant barrier, represented by users’ knowledge about smart technologies has to be taken into consideration to realize a proper home automation system able to interact with users. Not only do smart appliances have to be correctly installed and properly configured, but the users’ knowledge of smart devices needs to be consistently increased as well as their awareness of energy management.

7. Conclusions

In this article, the concept of the smart home and the advent of the smart grid have been presented. Smart technologies and products available on the market that allow an intelligent energy management of homes have been reviewed. The technologies summarized in Table 1, which include both optimization-based and communication-based ones, have been evaluated. It was also discussed a general system’s architecture and the barriers, challenges, benefits and future trends that future smart homes and grids will face. Efficient usage of electricity results in lowering peak load, reducing energy bills, and minimizing greenhouse gas emissions. In order to realize an effective integration of smart homes into a smart grid, the migration towards bi-directional communication networks has to be fostered, and well-tuned home automation system has to be designed.
It is expected that the work described in this article might channel efforts towards the choice of a more efficient, user-friendly system for smart home [21].
The current trend indicates that in the near future, more and more smart homes will be built and the technology inside them will grow very fast in order to create a more responsive and active environment able to respond to the users’ needs. In this regard, companies that produce software and home appliances are creating new applications and technologies specifically targeted at smart homes. The effect will be threefold: (i) in the future, homes will not be the same as today; (ii) existing infrastructures, such as smart grids, will be continually improved, and (iii) people’s everyday lives will inevitably be affected by changes in available technologies and systems.
Concerning the role and motivation of the potential users of the energy management technologies that are being developed, much still remains to be explored before these systems will satisfy users’ needs and help them fulfill their full potential as active and aware users. However, providing end-users with systems that are tailored to fit end-user profiles is a good start for providing real-time feedback. The option to measure performance against relevant benchmarks and make comparisons with other households’ performances should preferably be included in such systems. The challenge to build in a well-functioning flexibility into the systems’ presentation of data is likely to remain a continuous challenge for these systems as the users will gradually get used to any means of visualization of data and want it to be changed regularly. The need to provide homes with a systemic context calls for more cooperation with the smart grid’ managers at a systemic level and more end-user studies. Finally, the potential use of gamification elements should be further explored to keep up with the latest computer game industry into smart technologies.

Acknowledgments

This work was partially funded by the European Union’s Seventh Framework Programme under grant agreement 608806, acronym CoSSMic, and by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement 680529, acronym QUANTUM. The sole responsibility for the content of this article lies with the authors. It does not necessarily reflect the opinion of the European Commission (EC). The EC is not responsible for any use that may be made of the information this article contains. Finally, the authors would like to thank Michele Liziero, Antonio Fallacara and Claas Pinkernell for their support during the collection of data.

Author Contributions

The work presented in this article is the result of a collaboration of all authors. Gabriele Lobaccaro and Erica Löfström analyzed the literature on the subject. Gabriele Lobaccaro, Erica Löfström and Salvatore Carlucci contributed in writing the manuscript and editing the document. Salvatore Carlucci critically reviewed the article. Gabriele Lobaccaro and Salvatore Carlucci actively contributed to finalize the manuscript. All authors contributed to the discussion and conclusion of this research.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

ACORDappliance coordination
ACORD-FIappliance coordination with feed
AiSEGartificial intelligence and smart energy gateway
BTbluetooth
CPPcritical peak pricing
CPUcentral processing unit
DDdashboard or display device
DRdemand-response
DsTdecision support tool
ECEuropean commission
EMUenergy management unit
GHGsgreenhouse gasses
GSM/GPRSglobal system mobile
GUIgraphical users interface
HANhome area network
HEMShome energy management system
IPinternet protocol
IPPCintergovernmental panel on climate change
ICTsinformation and communication technologies
IBRinclining block rates
INinsteon
IPMRintelligent power management rostrum
IWTintegrated wireless technology
LPlinear programming
MACmedium access control
NANneighborhood area networks
OLMoptimum load management
OREMoptimization-based residential energy management
PCphysical component
PVPhotovoltaics
RCremote control
RFIDradio frequency identification
REFrenewable energy source
RTPreal time pricing
Ssensor
SHMCsmart home micro-computers
SHS/HAsmart home systems/home automation
SMsmart meter
ToUtime of use
ZBzigBee
ZWZ-wave
WANwide area network
WSHANwireless sensor home area network
WSNwireless sensor networks
xDSLdigital subscriber lines

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