Communication Technologies for Smart Grid: AComprehensive Survey

Fredrik Ege Abrahamsen 1,∗, Yun Ai 2 and Michael Cheffena 2

1 Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology,2815 Gjøvik, Norway.

2 Faculty of Engineering, Norwegian University of Science and Technology, 2815 Gjøvik, Norway.* Correspondence: fredrik.e.abrahamsen@ntnu.no

Abstract: With the ongoing trends in the energy sector such as vehicular electrification and renewableenergy, smart grid is clearly playing a more and more important role in the electric power system industry.One essential feature of the smart grid is the information flow over the high-speed, reliable and securedata communication network in order to manage the complex power systems effectively and intelligently.Smart grids utilize bidirectional communication to function where traditional power grids mainly only useone-way communication. The communication requirements and suitable technique differ depending onthe specific environment and scenario. In this paper, we provide a comprehensive and up-to-date surveyon the communication technologies used in the smart grid, including the communication requirements,physical layer technologies, network architectures, and research challenges. This survey aims to helpthe readers identify the potential research problems in the continued research on the topic of smart gridcommunications.

Keywords: review, survey, smart grid, smart grid technologies, smart grid communication, wirelesscommunications, wired communication, smart grid security

1. Introduction

Today’s method for generation and distribution of electric power was designed and constructed inthe last century and has largely remained unchanged since then. The traditional power grids are primarilyradial, and built for centralized power generation. Reliability is ensured by having excessive capacityand one-way power flow from the power plant to the consumer through high voltage transmission lines,often over long distances. With the demand for electric energy continuously increasing, and the existingconventional grid being at the end of its life cycle. Increasing amount of distributed renewable energysources (RES) and energy storage systems (ESS) require new ways of managing and controlling the powergrid and distributing the power in a more efficient, effective environmentally sustainable and economicalmanner. The next generation power grid is often referred to as smart grids (SGs). Smart grids are achievedby overlaying a hierarchical communication infrastructure on the power grid infrastructure [1–3].Since January 1 2019, most end-users in Norway should have installed smart electricity meters to manageautomated meter readings (AMR). In January 2019, 97 % or 2.9 million meters were installed in Norway,among which 2.5 million of these are private households and holiday homes [4,5]. In the European Union(EU), it was committed by the member states to achieve a roll out of close to 200 million smart meters forelectricity by 2020. About 71 % of European consumers then will have a smart electricity meter installed[6]. Globally, it is expected that 800 million smart meters will be installed by 2020 [7]. The installation ofthese metering devices can be seen as one of the first steps toward a smarter grid system, as implementinga smart grid is not a one-time event rather than an evolutionary process. The smart meters have the abilityto collect and report consumption data to the utilities provider several times per hour, rather than the

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consumer having to report every month manually. The smart metes also open up for the consumer tofeed the grid with electricity from, i.e. solar panels or electric vehicles. Other possibilities with the smartmetering are a higher degree of monitoring and control of the grid, automatic fault detection and reports[1,8].

This remainder of the paper is organized as follows: Section 2 gives an overview of smart gridinfrastructure, domains, architecture and applications. Section 3 presents smart grid communicationtechnologies and network structures. Section 4 addresses challenges of smart grid communications, andprivacy and security of smart grid communication. The organization of this paper is summarized in Figure1.

Figure 1. The structure of the paper

2. Overview of Smart Grid

Communication plays an important role in SG, as one of the most significant differences betweentraditional grids and SG are the two-way communication and the potentials this enables (i.e., distributedsmart sensors, distributed power generation, real time measurements and metering infrastructure,monitoring systems, and fast response require reliable communication and information exchange).

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Information exchanges is of great importance for the SG to provide reliable power generation anddistribution. Following is an overview of smart grid infrastructure, domains, network architectureand smart grid applications.

2.1. Smart Grid Infrastructure

Both international and national organizations have developed roadmaps, defined standards anddefinitions on what makes a power grid a smart grid [8–14]. There are not one single definition on whata smart grid is. However, it is common in the SG definitions to emphasize on the communicationfor measurements, monitoring, management and control. The communication plays an essentialrole in providing reliable, efficient and secure power generation, transmission and distribution. Thecommunication systems provide information exchange between the distributed sensing equipment,monitoring systems, and data management systems. These solutions all require fast communicationsas the generation, delivery and consumption all happening at the same time. With the introduction ofdistributed energy sources and energy storage systems, the importance of fast and reliable communicationincreases. The expectations from end-users also change, with real-time information on electricity prices,customers feeding the grid with electricity and electric vehicles acting as batteries in the grid. A key goalfor smart grids are reduced cost and environmental impact, and maximizing reliability, resilience andstability [8]. The smart meter is a key component of the smart grid infrastructure, and part of the advancedmetering infrastructure (AMI). AMI is responsible for enabling a reliable and secure high speed two waycommunication between smart meters at the end-user, and data control centers at the utilities companiesfor monitoring and control [9,15,16]. The full benefit of the smart grid infrastructure is achieved whensmart meters, sensors and measuring devices located throughout the power grid communicate in order toensure stability, detect, predict and prevent faults, forecast load changes and facilitate demand response[17]. Table 1 shows the main differences between traditional grid and a Smart grid.

Table 1. Comparison of traditional power grid and smart power grid [3].

Traditional grid Smart grid

Information flow One-way communication Two-way communicationPower generation Centralized power generation Distributed power generationGrid topology Radial NetworkIntegration of distributed Low degree High degreeenergy sourcesSensors Low degree High degreeMonitoring Manual monitoring Self-monitoringOutage recovery Manual restoration Self-reconfigurationTesting Manual RemoteAbility to control Limited PervasiveEfficiency Low HighEnvironmental impact High Low

2.1.1. Smart Grid Domains

Smart grids are large systems, which include different stakeholders and domains [18]. To structurethe different areas of a smart grid environment, The National Institute of Standards and Technology (NIST)[10] proposed seven domains of smart grid with electrical interfaces and communication interfaces inits conceptual model for smart grid information networks in 2009. The conceptual model has later beenupdated with more communications and electrical interfaces to better reflect the increase in distributedenergy sources and automation of distribution systems [19,20]. Table 2 shows the definition of thesedomains and Figure 2 displays the domains and interfaces. The domains are: customer, distribution,

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transmission, generation including distributed energy resources (DER), markets, operations and serviceproviders. The first four being related to transmission of electricity on the power grid. Table 2 gives thedescriptions of the NIST model.

Figure 2. Domains in smart grid as proposed in NIST Smart Grid Framework 4.0 [20]

Table 2. Smart Grid domains, electrical and communication interface [21].

Domain Communication interface Electrical interface

MarketService provider, Operations, Generation,Transmission, Distribution, Customer None

OperationsMarkets, Service provider, Transmission,Distribution, Customer, Generation None

Service providerMarkets, Operations, Customer,Distribution, Generation None

TransmissionMarkets, Operations Generation,Distribution Generation, Distribution

DistributionOperations, Transmission, Customer,Service Provider Transmission, Customer

CustomerMarkets, Operations, Service provider,Distribution Distribution, Generation

Generation incl. DERMarkets, Operations, Transmission,Customer Transmission, Customer

Each component of Figure 2 is described below.

• Market domain: Grid assets and services are bought and sold within the domain. The marketdomain handles actors such as market management, wholesale, trading and retailing. The market

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domain communicates with all other domains in the smart grid. Communication between marketdomain and the energy supplying domains are critical, due to the need for efficient matching ofproduction and consumption [20].

• Operations domain: The domain is responsible for operations of the grid. Including monitoring,control, fault detection and management, grid maintenance and customer support. These aretypically the responsibilities of the utilities today. With smart grid more of these responsibilities willmove over to service providers [10,11].

• Service provider domain: Actors in the domain support business processes of power producers,distributors and customers. Ranging from utility services such as billing to management of energyuse and generation. Communication interface is shared with the generation, distribution, markets,operations and customer. The communication with operations domain is critical to ensure systemcontrol and situational awareness [10,11].

• Generation domain: The power generation domain is responsible for power generation in bulk ornon-bulk quantities. This can be from for example fossil fuels, water, wind or solar. For the case ofNorway, this is typically hydropower, these are grid-connected power generation stations. Powergeneration include distributed energy resources. Smart grids allow for end-users to also operateas producer of electrical energy, for premise use, storage or for resale. [11,22]. With smart grids,power generation is no longer limited to large fossil or hydroelectric power facilities feeding thetransmission grid. Smart grids allow for smaller scale distribution-grid-connected power generation.This can be wind power parks, solar parks, photovoltaic panels mounted on end-users roof-tops,or electric vehicles feeding the grid [11,23]. Communication with the transmission and distributiondomains are important to maintain energy delivery to customers [10,11].

• Transmission domain: The power transmission domain is responsible for the transfer of power fromthe power generation source to the distribution system. The transmission domain typically consistsof transmission lines, substations, energy storage systems and measurement and control systems.The transmission system is typically monitored and controlled through supervisory control and dataacquisition (SCADA) system which communicates with field and control devices throughout thetransmission grid [10,11].

• Distribution incl. DER domain: This domain is the connection between the transmission and thecustomer domain. The distribution domain may include DERs located at customer or at grid operator.In a smart grid environment, the distribution domain communicates with the market domain due tothe market domains potential to affect local power consumption and generation [10,11,20].

• Customer domain: The customer or end-user could be private, commercial or industrial. In additionto consume the energy, the customer could also generate, and feed the grid with excess energy orstore energy. In cases where the customer generate and deliver energy consumer is referred to as aprosumer [20,24].

Reliable communication is required for information exchange between the different domains to ensurereliable operations of the power grid and its applications. Similar to NIST in the US, in Europe, the smartgrid coordination group defined its smart grid architecture model [9,13,25]. There are similarities betweenthe two models, the domains are the same. In addition to domains this model is also divided in layers andzones.

This is a three dimensional model consisting of five interoperability layers (business, function,information, communication and components). The two dimensions are divided in domains (generation,transmission, distribution, DER, and customer premises), and zones (process, field, station, operation,enterprise and market).

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Figure 3. Smart metering architecture

2.1.2. Architecture

What separates smart grids from traditional electrical grids are the interaction and communicationbetween different the domains. The smart grid infrastructure can be structured by dividing it in fourlayers: the application layer, the communication layer, the power control layer and the power systemlayer. On the customer side, the application layer enables various applications such as home automationand real-time pricing. On the grid side: automation of grid, and power distribution applications. Thecommunication layer is important in distinguishing smart grids from traditional power grids, and inenabling smart grid applications. It is divided into three categories classified by geographic area (widearea network (WAN), neighborhood area network (NAN)/field area network (FAN) and the premise areanetwork (PAN)). Depending on the type of network, different communication technologies are used. Thepower control layer enables management, control and monitoring of the power grid, utilizing equipmentand such as switches, sensors and metering devices. Power system layer handles power generation,transmission/distribution and the customer premises.

2.2. Smart Grid Applications

SG applications for monitoring and grid management include advanced metering infrastructure(AMI), advanced metering readings, distributed automation (DA), distributed generation (DG), distributedStorage, home energy management systems (HEMS), demand response (DR), and supervisory control anddata acquisition. All depending on reliable wired and wireless communication interfaces to operate in thesmart grid infrastructure.

Advanced metering infrastructure (AMI)SG is considered as one of the largest potential IoT network implementations with smart meters, wirelesssmart sensors placed throughout the grid and smart appliances communication with each other to ensurereliable and efficient power generation and distribution. The advanced metering infrastructure consists ofphysical and virtual components, including sensors, monitoring systems, smart meters, software, datamanagement systems and communication networks. AMI is responsible for collecting, analyzing and

Table 3. Overview of smart grid communication layers

Application Layer Power Transmission andDistribution Applications Customer Applications

Communication Layer Wide Area NetworkNeighborhood Area

Network / Field AreaNetwork

Premise Area Network(Home Area Network,

Building Area Network,Industrial Area Network)

Power Control Layer Power monitoring, control and management systems

Power System LayerPower Generationand Transmission Power Distribution Customer

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Table 4. Norwegian smart meter HAN reading specification [29]

Refresh rate Parameter Unit Data type

2 sec. Active power + kW double-long-unsigned

10 sec. Meter ID stringMeter type stringActive power + kW double-long-unsignedActive power - kW double-long-unsignedReactive power + kVAr double-long-unsignedReactive power - kVAr double-long-unsignedCurrent x 3 A long-signedVoltage x 3 V long-unsigned

1 h Cumulative hourly active energy x 2 kWh double-long-unsignedCumulative hourly reactive energy x 2 kVArh double-long-unsignedTime and date in meter string

storing metering data sent from sensors and monitoring systems and smart meters at the end-user to theutility companies for billing, grid management and forecasting. SG interactions based on measured dataand communication from sensor networks. [26,27].

Advanced meter readingsThe smart metering devices installed on the customer premises use different technologies forcommunicating. These vary depending on what manufacturer smart meter the utilities company areinstalling, and the application. Table 4 lists the different parameters available from the end-users’ smartmeters, and refresh rate in the Norwegian market [28,29].

For large apartment buildings the metering devices can be connected to the master device by RS-485[30]. As illustrated in Fig. 3, the metering devices can also be directly connected to the Head-End System(HES) through 3G/4G/5G or fiber network, so called end-to-end connection. The master device uses3G/4G/5G, Ethernet, fiber optics or power line communication (PLC) to communicate with the head-endsystem at the utilities company. Inside the premise area, the smart meter communicates through theHAN-port, the communication is based on IEC 62056-7-8, with RJ45 connector and M-Bus interface. Fromthis port, other third party equipment can be installed i.e. HEMS or household appliances [31].

Grid monitoringSCADA is responsible for monitoring of generation and power transmission, and the communicationis performed on WANs. The SCADA functions are enhanced from traditional grid due to fast two-waycommunication and implementation of large numbers of sensors. For transmission line monitoring,wireless smart sensor nodes are distributed along the transmission line, exchanging measurements tothe neighboring nodes. The nodes forward the measurements to a central collection site over NAN orWAN. The central is connected to a base station with low latency, high bandwidth and low costs links [32].To ensure uninterrupted power delivery continuous monitoring is required. Fast outage identification,management, and restoration systems can be achieved by interfacing the outage management systems withSCADA, AMI and geographical information system. The combination of AMI and smart meters can givenotifications or last gap reports to outage management systems before the customer notices the outage, thushelping in reducing trouble-shooting time and restoration time [32]. These systems for status monitoring,of the smart grid infrastructure down to individual components helps to detect, predict and respondto faults faster. The result is better management, more accurate optimization of resources, better and

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faster identification of faults in the grid, reduction in troubleshooting-time, and improved reliability [26,27].

Distributed energy resources (DER)Distributed energy resources have a substantial potential at generating electricity at the load end. DERinclude solar photovoltaic panels, windpower and biomass. Two-way communication in the AMI enablethe end user to sell surplus energy, and feeding it back to the power grid [33,34].

Distributed storageDistributed storage is an integral part of the smart grid infrastructure. Fast response to stability issues inthe grid are dependent on fast and reliable communication links in the smart grid. Distributed storage incombination with DER can improve the utilization of renewable distributed energy resources [35].

Vehicle to grid (V2G)It is clear that the electrification of vehicles is becoming an ongoing trend around the globe now, whichimplies the frequent interaction between power grid and vehicles in the future. Electric vehicles (EVs)with charges connected to a vehicle to grid network in the smart grid for exchanging power betweenthe grid and the EV by utilizing the stored energy in the vehicle batteries to feed back to the grid whennecessary. EVs in the power grid can be used for power balancing by providing fast response high power.EVs can reduce the energy demand in peak load hours by consuming, storing and returning energy whenneeded. EVs can also be used as back up power or in islanded operation if connection to the grid is notpossible [36,37]. These applications require bidirectional communication between the utilities and the EVs.

Demand response (DR)AMI and communication between end-user and the utilities companies give ability for demand responsefrom the consumer side, or utility side in predefined cases. From the consumer side, demand responsegives the end-user the ability to monitor its energy consumption and production where appropriate andcost at any given time, and for example alter habits to shift the demand to off-peak hours in responsedynamic pricing programs such as time of use, real time pricing, critical peak timing or to incentivepayment when grid reliability is low [38–40]. Demand response can also be an automated part ofhome energy management systems, where certain appliances or lighting can be turned off to reduceconsumption [41]. Demand side management or demand response can be used to reduce power constraint,shift peak load, reduce distribution losses and regulate voltage drops and avoid or postpone the need forbuilding new power lines [26,42].

Home energy management systems (HEMS)HEMS is used to enable demand response applications. HEMS systems permits the end-users tomonitor, control, and manage the power consumption. These systems is comprised of smart appliances,sensors, smart meters and in-home displays, and include applications for for example home automation,temperature zone setting, water temperature, and controlling electricity use depending on real-time pricinginformation etc. Appliances and sensors connects to HEMS through sensor networks and to the utilitycompanies AMI through the smart meter HAN interface [31,32].

3. Smart Grid Communication

From the previous section we can see that SG is highly dependent on information flow andcommunication between different entities in different networks. Communication is one of enablingtechnologies of SG. As the number of sensors increases, the amount of data coming to the utility increases.

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3.1. Quality-of-service (QoS) Requirements for SG

SG applications result in increased data, these applications have different QoS requirements. Securebi-directional communication that satisfies the different SG application’s QoS requirements are essential[32]. Control, management and automation applications such as demand response and substationautomation require low latency and high reliability to ensure grid operation. Other applications suchas meter readings can tolerate a higher latency, but still require high reliability [32]. With the differentequipment interconnected in the SG, interoperability must be ensured for seamless communication [11].Interoperability must also be ensured for legacy and evolving communication protocols.

SG Application Data Rate Latency Reliability

Smart Metering Low High MediumSCADA Medium Low LowSubstation Automation Low Low HighDER Medium Low HighDR Low Low High

Table 5. Smart Grid QoS Requirements

3.2. Communication Network Structure

A defined communications framework is necessary in this infrastructure. It is crucial to have clearlydefined standards to ensure reliable, efficient and secure communication throughout the system [43]. Thedifferent network types in the communications layer mentioned above have all different requirementswhen it comes to data rate and coverage distance, and the chosen communication technology mustsupport these specific requirements, which are summarized in Figure 5 and Table 6. The networks utilizedifferent technologies for communication, both wireless and wired. The premise network (HAN, NANor IAN) is closest to the end-user, and enables information and communication flow between homeappliances or for example heating, ventilation and air conditioning (HVAC) systems within the end-userpremise. Multiple HANs connects to a NAN. The NAN collects information, and enables communicationto the WAN. WAN handles communication of metering information from the end-user to the utilitiescompanies [44].

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Figure 4. Networks in SG

Figure 5. Data rate and communication range requirements in SG hierarchy

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Table 6. Overview Network types and requirements

Network type Coverage Data raterequirements Data rate Technology

alternatives

WAN 10 - 100 km

High data rate.Devices such asrouters andswitches

10 Mbps- 1 Gbps

Wireless: WiMAX, 3G,4G,5G.Wired: Ethernet, Fiber Optic

NAN/FAN 10 m - 10 kmHighly dependenton node densityand topology

100 kbps- 10 Mbps

Wireless: ZigBee, WiFi,WiMAX, Cellular.Wired: Power LineCommunication

HAN/BAN/IAN 1 - 100 m

Dependent onapplication.Generally lowdata raterequired.

10 - 100 kbps

Wireless: ZigBee, Z-wave,WiFi.Wired: Ethernet, HomePlug,M-Bus.

Wide area networkA WAN forms the backbone of the communication network in the power grid. It connects smallerdistributed networks such as transmission substations, control systems and protection equipment e.g.supervisory control and data acquisition, remote terminal unit (RTU) and phasor measurement unit(PMU) to the utility companies’ control centers [18,45]. Other terms used for WAN is backbone networkor metropolitan area network [18]. WAN applications require a higher number of data points at highdata rates (10 Mbps – 1 Gbps), and long-distance coverage (10 – 100 km). Real-time measurements aretaken throughout the power grid by measurement and control devices and sent to control centers. Inreverse, instructions and commands are sent from control centers to the devices [45]. This communicationrequires both a high degree of distance coverage and speed to maintain stability. Suitable communicationtechnologies for this application are PLC, fiber optic communication, cellular or WiMAX. Satellitecommunication can be used as backup communication or in remote locations [18,46].

Neighborhood area network/Field area network:The NAN and FAN are networks within the distribution domain, both enables the flow of informationbetween WAN and a premise area network (e.g., home area network (HAN), building area network(BAN), and industrial area network (IAN)). The NAN connect premises networks within a neighborhoodvia smart meters at the end-user. The NAN enable services such as monitoring and controlling electricitydelivery to each end-user, demand response and distribution automation. The area NAN/FAN coverscan in some cases be large, one of the features of NAN/FAN is communication between intelligentelectronic devices (IEDs). The data in a NAN/FAN is transmitted from a large number of sources to adata concentrator or substation. This requires a high data rate and large coverage distance. The existinggrid infrastructure in the NAN/FAN covered areas are in most cases not possible to make extensivealterations to the infrastructure. Because of the varying nature of the physical environment of whichthe NAN/FAN operate, coverage requirements etc. different technologies for communication are used.When the coverage requirements are lower, standards from NAN can be applied, if longer coverage isrequired, other technologies will be more suitable. The communication technologies used has therefore tobe adapted to each specific situation. Both wired and wireless technologies are used in NAN/FAN, andthe different communication technologies should be complementary. As distributed energy generation aredeployed, these are connected to the NAN/FAN. Communication technologies such as ZigBee, WiFi,Ethernet or PLC are widely used in these networks [18,46,47].

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Premise area networkThe premise area network divides into three sections depending on the environment. These are wired orwireless networks within the end-user’s premise. The purpose of the HAN is to provide communicationbetween for example the smart meter and home automation, appliances, Home Energy ManagementSystems, solar panels, or electric vehicles. BAN and IAN are commercial and industrial focused andcommunicate typically with building automation systems such as heating and ventilation or energymanagement systems. These applications do not require large coverage, high speed, or high data rate, andcan be managed with low power, low-cost technologies such as PLC, WiFi or ZigBee [46]. The requiredbandwidth in HANs vary from 10 to 100 kbps for each device, depending on function. The premisenetworks should be expandable to allow for the number of connected devices to increase [48]. Otherapplications for the smart metering devices within the premise area are delivering information suchas power and real-time price information to the end-user through HEMS. The end-user can then makedecisions whether to use appliances during high price periods or wait for lower price. This can in turnhelp with peak demand reduction and load shifting [49].

3.3. Smart Grid Communication Technologies

Communication technologies utilized in smart grid can as mentioned be wired or wireless. Mostpower systems use a combination of different wired and wireless technologies, depending on theinfrastructure. Several factor that has to be taken into account when deciding on communication technologyused in SG and smart metering. Wireless communication alternatives have some advantages over wiredcommunication, such as low cost and connectivity in inaccessible areas. A number of factors have tobe considered for each different case to decide on communication technology. Requirement includeaspects such as geographical topography, technical and operational requirements and cost [50]. Wirelesscommunication is less costly to implement in a complex infrastructure and ease of installation in someareas. Wired connection will not necessarily struggle with interference issues as wireless solutions maydo. Both types of communication are necessary in smart grid environment. The technology that fits oneenvironment may not be suitable in a different environment. Following is a summary of some of the wiredand wireless communication technologies used for smart grids, together with advantages and limitations.

3.3.1. Wired Communication

Power line communication (PLC)Power line communication utilizes the power transmission lines to transmit data. High frequency signalsfrom a few kHz to tens of MHz are transferred over the power line [51]. Initial cost of PLC is lower since ituses already existing power line infrastructure. The technology is mature, and has already been in usefor decades for commercial broadband and is highly reliable. PLC provide high throughput and lowlatency which makes it a suitable for SG communication in densely populated areas [52]. Power linecommunications divides into narrowband and broadband PLC. Narrowband PLC (NB-PLC) is operatingat 300-500 kHz with a data rate up to 10-500 Kbps and a range up to 3 km. This is further divided intoLow Data Rate Narrowband PLC and High Data Rate Narrowband PLC. Low data Rate NarrowbandPLC is single carrier based, with a data rate up to 10 kbps. High Data Rate Narrowband PLC is multicarrier based with a data rate up to 1 Mbps. Broadband PLC (BB-PLC) is operating between 1.8 and 250MHz with a data rate up to 300 Mbps. Power Line Communication can be used in nearly all parts of asmart grid environment, from home appliances in low voltage to grid automation in high voltage [53].Channel noise from power electronics is a major concern with this form of communication [54–56]. Datadistortion around transformers, and the need to bypass these using other communication techniques

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is another disadvantage with PLC [48]. Extensive field measurements show that the characteristics ofPLC channel differ significantly from one environment to another, which leads to varying performance[57]. The omnipresence of the power cables also makes the combination of PLC technique with othercommunication technologies (e.g., RF, visible light communication (VLC), etc.) an attractive approach toextend the communication coverage, thus enabling a variety of applications such as smart home, Internetof Things, etc [58–60]. HomePlug is type of power line communication specifically developed in-homeapplications and appliances. HomePlug Green PHY (HPGP) uses PLC technology, and is developed andmarketed towards HAN applications. It has a data rate up to 10Mbps, and operates in the 2 MHz - 30MHz spectrum [61,62]

Fiber optical communicationFiber optical communication is well suited for control and monitoring, and backbone communicationin WANs, although more expensive than other alternatives it has the advantages of long range, highbandwidth and high data rate, and and not being susceptible to electromagnetic disturbances. Limitationsof fiber optic communication is the number of access points. Fiber optics are used to connect substations tothe utility companies control centers [32,63].

EthernetSuited for communication in WAN between substations and control centers. Advantages with this formof communications is its high availability and high reliability. Ethernet is also used in HAN for thecommunication between smart meters and home central.

3.3.2. Wireless Communication

Cellular communicationCellular communication can be used where continuous communication is not required. It is used forcommunication in smart meters in rural areas. Advantages with this technology is that is alreadyexisting, it has widespread coverage, low cost and high security. One disadvantage with cellularcommunication is the fact that the network is shared with many other users, this can in some cases resultin network congestion. Universal mobile telecommunications system (UMTS), long-term evolution (LTE),LTE-machine type communication (LTE-M) and narrowband internet-of-things (NB-IoT) are technologiesused for communication in smart grids. The last two specifically developed for IoT applications. LTE-Mand NB-IoT are both low power wide area networks. LTE-M offers higher data rate, but require morebandwidth [64–66].The fifth generation mobile communication network (5G) utilizes wide frequency range including mmwave spectra and operate at higher frequencies than LTE/4G system, allowing for higher speeds andlower latency, and ability to connect a high number of devices. This makes it suitable for SG infrastructure[67,68]. A comprehensive review on the use of 5G for SG with the future roadmaps and challenges isprovided in [67]. The security for smart grid in future generation (5G and beyond) mobile networks isdiscussed in [68].

WiMAX (IEEE 802.16)Worldwide inter-operability for microwave access (WiMAX) is a short range wireless communicationtechnology based on the IEEE 802.16 standards with a data rate up to 70 Mbps and a range of 50 km.WiMAX operate on two frequency bands, 11-66 GHz for line-of-sight, and 2-11 GHz for non-line ofsight communication [69]. The physical and media access control (MAC) layer of WiMAX are definedby IEEE 802.16. The physical layer uses orthogonal frequency-division multiple access (OFDMA) and

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multiple-input multiple-output (MIMO) antenna system providing increased non-line of sight capabilities.The MAC layer applies data encryption standard (DES) and advanced encryption standard (AES)encryption to ensure secure and reliable communication. The MAC layer also utilizes power savingtechniques such as sleep and idle [70]. WiMAX is scalable and can be set up as networks on local orregional level. WiMAX is well suited for sensors and meters provided sufficient numbers of nodes in thearea. One limitation with WiMAX is that coverage becomes highly limited due to signal losses (e.g., rainattenuation, blockage, etc.) [71].

ZigBee (IEEE 802.15.4)ZigBee is an open wireless mesh network standard based on the IEEE 802.15.4 standard. It is a shortrange, low data rate, and energy efficient technology. ZigBee operate on four different frequency bands,868cMHz (20 kbps per channel), 915 MHz (40 kbps per channel), and 2.4 GHz (250 kbps per channel)[72,73]. ZigBee has mesh capabilities and a coverage range from 10 to 100 meters [43]. Mesh networksare decentralized, where each node are self-manageable, and can re-route, and connect with new nodeswhen needed. This makes ZigBee well suited for use in HAN applications such as remote monitoring,home automation, consumer electronics and smart meter readings [74,75]. A ZigBee mesh network isconstructed of three different types of nodes: coordinator, router and end-device. ZigBee uses AES-128access control to manage a high level of security. Because of the low transmission power level, thistechnology is vulnerable to multipath distortion, noise and interference [73]. ZigBee operating on 2.4 GHzband is also affected by distortion from technologies such as WiFi, USB, Bluetooth and microwave ovensas these operate on the same unlicensed frequency band [76–78].

Z-Wave (IEEE 802.15.4)Z-Wave is a proprietary communications standard intended for remote control of applications inresidential and commercial areas. In Europe, it operate on 868 MHz with a data rate of 9.6 kbps, and on 2.4GHz with a data rate up to 200 kbps. Range wise Z-Wave typically have around 30 meters indoor range,and up to 100 meters outdoors. Z-Wave is short range, low data rate and low cost alternative. Z-Wave canalso be organized as mesh network, increasing the range [73]. Similar to ZigBee, Z-Wave also uses AES128encryption standard to maintain a high level of security in the network [79].

WiFi (IEEE 802.11)WiFi technology, based on the IEEE 802.11 family of standards, is a wireless networking technique that isbeing widely used for Internet access. It can also be a good choice in the context of smart grid, whichenables consumers to monitor the improve their energy use [80]. WiFi solution is already being utilized ina number of devices that contribute to the so-called smart home. For instance, WiFi is used in thermostats,appliances, and new smart energy home devices that will connect them all together to help consumersmanage their own energy consumption [80–82].

Satellite communicationSatellite communication can play an important role in SG communication in rural areas without cellularcoverage, or as a backup solution for other communication technologies [83]. Examples of areas of use forsatellite communication are control and monitoring of remotely located substations [84].

Free-space optical (FSO) communicationsThe demand for higher data rates requires broader bandwidth for communication system. Amongdifferent potential technologies, FSO communication is one of the most promising technologies addressingthe problem of large bandwidth and data rate requirements, as well as the “last mile bottleneck”. FSO

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system functions by transmitting modulated laser light through the air between the transmitter andreceiver. More specifically, the signal is transmitted using a lens or parabolic mirror by narrowing the lightand projecting it towards the receiver. The emitted light is then picked up at the receiver with a lens ormirror. Subsequently, the received light is focused on an optical detector and converted to electrical signalsfor further information extraction [85]. Besides the advantages of large data rate with unlicensed spectrum,the FSO communication is also considered to be a more secure technique than the RF communication[86–89]. Thanks to the various advantages of FSO communications, FSO link can be part of the backhaulcommunication network for rural or remote substations monitoring applications. In [90], the FSO systembased on microring resonator (MRR) with the ability to deliver up to gigabit (line-of-sight) transmissionper second is proposed for the two smart grid applications (AMI and DR). The experimental resultsdemonstrate up to 10 times bandwidth improvement over the radius as large as 600 meters and maintainreceive power higher than the minimum threshold (- 20 dBm) at the controller/users, so the overall systemis still able to detect the FSO signal and extract the original data without detection. The feasibility of FSOcommunications technology from the atmospheric context of Bangladesh has been analyzed for smartvillage energy autonomous systems in [91].

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Table 7. Overview of wired communication technologies in SG.

Wired communication technologies

Technology Data rate Coverage Application Advantages Disadvantages Network type

EthernetUp to100 Gbps

Up to100 m

In-home communication,SCADA, backbonecommnunication

Good on shortdistances

Coveragelimitations

Premise network,NAN/FAN, WAN

Broadband PLCUp to300 Mbps

Up to1500 m

SCADA, backbonecommunication inpower generationdomain

Existinginfrastructure,standardized,high reliability

Noisy channelenvironment,Disturbance

NAN/FAN, WAN

Narrowband PLC10-500Kbps

Up to3 km

SCADA, backbonecommunication in powergeneration domain

Existinginfrastructure,standardized,high reliability

Noisy channelenvironment,Disturbance

NAN/FAN, WAN

HomePlug4, 5, 10Mbps

Up to200 m

In-home communication,Smart appliances

Low cost,low energy

Coveragelimitations,Disturbance

Premise network

Fiber opticUp to100 Gbps

Up to100 km

SCADA, backbonecommunication in powergeneration domain

High bandwidth,high data rate.not susceptible toelectromagneticinterference

Costly WAN

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Table 8. Overview of wireless communication technologies in SG.

Wireless communication technologies

Technology Data rate Coverage Application Advantages Disadvantages Network type

WiMAX 75 MbpsUp to50 km

In-home communicationSmart meter reading

Low cost,low energy

Not widespread,coverage highlyreduced if loss inline of sight

NAN/FAN, WAN

ZigBee 20-250 kbpsUp to100 m

In-home communication,energy monitoring,smart appliances,home automation

Mesh capability,simplicity, mobility,low energy, low cost.

Low data rate,short range,interference

Premise network,NAN/FAN

Z-Wave 9-40 kbpsUp to30 m Wireless mesh network

Mesh capability,simplicity, mobility,low energy, low cost.

Low data rate,short range,interference

Premise network

WiFi2 Mbps -1.7 Gbps

Up to100 m

In-come communication,smart appliances,home automation,SCADA

Good on shortdistances. Security

Premise network,NAN/FAN

3GUp to42 Mbps 70 km

SCADA,Smart meter reading

Already existingnetwork, highsecurity, low cost,large coverage

Network sharedwith consumersmay result incongestion.

NAN/FAN, WAN

4G/LTEUp to979 Mbps

Up to16 km

SCADA,Smart meter reading

Already existingnetwork, highsecurity, low cost,large coverage

Network sharedwith consumersmay result incongestion.

NAN/FAN, WAN

LTE-M 7 Mbps 11 km Smart meter readingLow cost, lowenergy, scalability,coverage

Lower data rate NAN/FAN

NB-IoT 159 kbps Smart meter readingLow cost, lowenergy, scalability,coverage

Lower data rate NAN/FAN

5GUp to20 Gbps

SCADASmart meter reading

High data rate,scalability Lower data rate NAN/FAN, WAN

Satellite 50 MbpsBackup, remote locationcommunication

Good when noother alternative isviable

High cost WAN

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4. Challenges of smart grid communication

In this section we will discuss future trends of smart grid communications and applications, and acomprehensive review of these challenges.

4.1. Robust Transmission

Robust transmission of information with high QoS is one of the most prioritized requirements forsmart grid communications. It will greatly improve the system robustness and reliability by harnessingthe modern and secure communication protocols, the communication technologies, faster and more robustcontrol devices, embedded intelligent devices for the entire grid from substation and feeder to customerresources [92]. As the use of communication systems in other scenarios, there are many challengesto achieve robust transmission because of limited bandwidth, limited power, adverse transmissionenvironment (interference, high path loss, etc) [93–97]. As discussed in the previous sections, bothwireless and wired communication technique consists important parts of the smart grid communicationwith its own advantages and disadvantages. In many cases, a hybrid communication technology mixedwith wired and wireless solutions can be used in order to provide higher level of system reliability,robustness and availability[98].

4.2. Security

Cyber security is considered to be one of the biggest challenges to smart grid deployment as the gridbecomes more and more interconnected, and every aspect of the SG must be secure [99]. Security measuresmust cover issues involving communication and automation that affects operation of the power systemand the utilities managing them. It must address deliberate attacks as well as inadvertent accidents suchas user error and equipment failure [11,99].

Smart grids are vulnerable to cyber-attacks due to the integration of communication paths throughoutthe grid infrastructure. Smart grids are still evolving, and considering security in a new smart gridenvironment is important, but challenging. Undetected cyber-attacks can lead to critical damage affectingthousands or millions of customers and life threatening infrastructure [100,101]. Securing the data isvital for both end-user and power companies to ensure trust. As more functions and capabilities areimplemented to the smart grid importance of secure and safe communication increase. From distributedenergy generation, energy storage, electric vehicles to power station and power grid control systems. Alsosomething possibly as trivial as securing that the reading from the end-user’s smart meters are sendingcorrect billing information, or that the utilities companies receive the correct information is essential [102].As for any other communication systems, security enhancement for smart grid communication can beachieved at different layer of the protocol by utilizing the techniques from the conventional upper layercryptography [103–107] to the physical layer security [108–111]. Different communication technologies,wired and wireless, interconnects and are required to operate the grid securely. Different authorities areresponsible securing different data and security aspects in smart grid/smart metering. For the Norwegiancase:

• Norwegian metrology service: measurement accuracy• Norwegian directorate for civil protection (DSB): electrical safety• Norwegian communications authority: communication• Norwegian water resources and energy directorate: application, function and safety of smart meters.

Personal data act, Section 13 sets requirements for satisfactory information security [112]. Based on this,the Norwegian Electrotechnical Committee (NEK) emphasizes on the following three aspects in relation tosecurity in smart grids: confidentiality, integrity and availability, as well as the following four elements[113].

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• Protection against unauthorized access to measurement data on the meter.• Protection against unauthorized retrieval of measurement data.• Protection against tampering or alteration of measurement data.• Ensuring that measurement data is available when needed.

Vulnerabilities and threats may also be categorized as consumer threat, naturally occurring threat,individual and organizational threat, impacts on consumer, impacts on availability, financial impacts andlikelihood of attack [114]. NEK recommends that communication in HAN use synchronous encryptionAES-128, since the data has fixed length. The end-user have to request the utility company to open up forHAN, and to receive encryption key [28]. In Norway, the Norwegian Data Protection Authority (DPA) hasidentified several aspects relating to smart grid and smart metering privacy. Since the smart meters can belinked to address, and home-owner, behavioral information can be traced back to individual person [115].Earlier SCADA systems were isolated on a separate computer network, but the development towardsconnecting all devices to the Internet, are making the system vulnerable to cyber-attacks [116,117]. Attackshave been carried out on SCADA networks in the past, some with significant impact to infrastructure andpower delivery [118]. Attacks on smart grids can occur on all levels, from generation and distribution tohome networks, it can be protocol-based attacks, routing attacks, intrusion, malware and denial-of-serviceattacks (DoS). Successful attacks can lead to grid instability, or worst case failure and blackouts [102,114,119]. A reliable SG depends on avoiding attacks, or detecting and establishing mitigation measures.Protection used within SG for message authentication, integrity and encryption. Security must also addressloss of communication, unauthorized access to network and devices (eavesdropping), network attacksdenial of service (DoS), distributed denial of service (DDoS), man-in-the-middle (MITM), and jamming ofradio signals [68].

There have been several attacks on power companies the last years, where some have led to systemfailure and blackout. In 2006 a nuclear power plant in Alabama, USA failed due to overload on thecontrol system network. Investigations later identified the source to be manipulated smart meter powerreadings [119]. In 2013-2014 an attack affected more than 1000 energy companies in 84 countries includingGermany, France, Italy, Spain, Poland and the US [120]. In December 2015, Ukraine experienced a cyberattack on three regional power distribution companies, leaving people in the dark for over six hours. Overtwo months after the attack, control centers were not fully operational. The attack was distributed viaspear-phishing email, targeting IT staff and systems administrators in companies responsible for powerdistribution. By opening an attachment in an email, malicious firmware were uploaded SCADA-network.The intruders gained access to substation control centers via virtual private networks (VPNs) and wasable to send commands to disable uninterruptible power supply (UPS) systems, and open breakers insubstations. The blackout affected around 225,000 customers, and manual operations were required toturn the power back on [100,118]. In 2016 Ukrainian power distribution was once again attacked, parts ofthe city of Kyiv lost power for an hour. The malware enabled control of circuit breakers to the attackers. In2020, the European Network of Transmission System Operations for Electricity experienced an attack onits office network. The attack did however not infect any of the systems responsible for controlling thepower grid [120,121].

Denial of service attackIt has been claimed that DoS attacks are one of the greatest concerns for service providers. SG consistsof a number of measurement devices such as smart meters, smart appliances, data aggregators, PMUs,IEDs, RTUs, PLCs, etc. Attacks to SGs can result in loss of data availability, loss of communication control,compromised data integrity, and loss of power [122].

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Use of encryptionThe security of the power grid is depends on authentication, authorization. Encryption of communicationflowing between devices in the grid and data centers is crucial to reduce attackers ability to gain accessto data or achieve system control. Depending on communication technology, different solutions arepreferred, such as advanced encryption standard (AES) and triple data encryption (TDES) [99]. Encryptionensures identification and authorization.

Authentication and authorizationAuthentication is the process of verifying the identity of a user, application or device. Authorization in theprocess of verifying whether the user, application or device has permission or the rights to access thesystem, or perform an operation. Authentication, authorization and access control is necessary in SG dueto the vast amounts of connected devices. Different users with different roles and level have access tocontrol systems, sensors communication networks in the SG. Entities in the SG must be bidirectionallyauthenticated. Common types of authentication schemes in SG are: device-to-device, device-to-networkand user-to-network [123].

4.3. Privacy

Communication in smart grids are often linked to information related to individual customers andtheir lives. This is why securing authentication, authorization, and confidentiality is so important in asmart grid environment. It is of greatest importance not to disclose private data customer to anyone otherthan consented entities. Private data include consumer identification, address, energy usage information[40]. Smart meters are expected to provide high accuracy reading of power consumption at defined timeintervals to the utilities companies. This data is used for billing purposes and grid management. However,measurement data from smart meter may be used for other purposes. Usage pattern analysis can be usefulfor power saving, but involves a significant risk. The data holds a great amount of information aboutindividual consumers [44,124]. Non-intrusive appliance load monitoring (NALM) technologies usesextracts detailed information on appliance use based on energy measurements [125]. By analyzing dataand usage patterns, it may be possible to predict when people are at home or away from home, or whatappliances are in use. This information is could be of interest for the police, tax authorities, insurancecompanies etc. [17,126]. NIST have acknowledged that the major benefit of smart grids is the ability toreceive richer data from smart meters and devices, is also the biggest weakness from a privacy standpoint.

5. Conclusion

In this paper, an overview of smart grid infrastructure, communications technologies, and itsrequirements, and applications in premises network, neighborhood area network and wide area networkwere presented. Cyber security challenges are briefly presented. We are currently in the brief beginning ofwhat will be a major change in how electric power grids and power generation are organized and managed.The changes are likely to be significant, and new possibilities emerge as new technologies are furtherdeveloped. The amount of data and information exchange are increasing rapidly as new technologies areimplemented to the grid. Security concerns must be addressed to ensure a reliable power supply.

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References

1. Zhou, X.; Ma, Y.; Gao, Z.; Wang, H. Summary of smart metering and smart grid communication. Proceedingsof IEEE International Conference on Mechatronics and Automation (ICMA). IEEE, 2017, pp. 300–304.

2. Priya, P.P.S.; Saminadan, V. Performance analysis of WiMAX based smart grid communication traffic prioritymodel. Proceedings of International Conference on Communication and Signal Processing. IEEE, 2014, pp.778–782.

3. Farhangi, H. The path of the smart grid. IEEE Power and Energy Magazine 2009, 8, 18–28.4. Norwegian Water Resources and Energy Directorate. Smarte strømmålere (AMS), 2020.5. Arne Venjum. Smarte målarar (AMS) Status for installasjon per 1. kvartal 2019. Sluttrapport. Report,

Norwegian Water Resources and Energy Directorate, 2019.6. European Commission Joint Research Centre Smart Electricity and Interoperability. Smart Metering

Deployment in the European Union.7. Global Smart Grid Federation. Smart meter security survey, 2016.8. International Energy Agency. Technology Roadmap, 2011.9. International Electrotechnical Commission. IEC smart grid standardization roadmap. SMB Smart Grid Strategic

Group (SG3) 2010.10. National Institute of Standards and Technology. NIST Framework and Roadmap for Smart Grid Interoperability

Standards, Release 1.0. Report, National Institute of Standards and Technology, 2010.11. National Institute of Standards and Technology. NIST Framework and Roadmap for Smart Grid Interoperability

Standards, Release 3.0. Report, National Institute of Standards and Technology, 2014.12. The German Roadmap E-Energy/Smart Grid 2.0, 2013.13. Smart Grids Austria Technology Roadmap, 2015.14. ITU Telecommunication Standardization Bureau Policy & Technology Watch Division. Activities in Smart Grid

Standardization Repository (Version 2.0, April 2011), 2011.15. Chren, S.; Rossi, B.; Pitner, T. Smart grids deployments within EU projects: The role of smart meters. 2016

Smart cities symposium Prague (SCSP). IEEE, 2016, pp. 1–5.16. Gözde, H.; Taplamacıoglu, M.C.; Arı, M.; Shalaf, H. 4G/LTE technology for smart grid communication

infrastructure. Proceedings of International Istanbul Smart Grid Congress and Fair (ICSG). IEEE, 2015, pp. 1–4.17. Goel, S.; Hong, Y.; Papakonstantinou, V.; Kloza, D. Smart Grid Security 1st ed.; Springer London, 2015.18. Kuzlu, M.; Pipattanasomporn, M.; Rahman, S. Communication network requirements for major smart grid

applications in HAN, NAN and WAN. Computer Networks 2014, 67, 74–88.19. National Institute of Standards and Technology. Update of the NIST Smart Grid Conceptual Model (Discussion

DRAFT). Report, National Institute of Standards and Technology, 2018.20. National Institute of Standards and Technology. NIST Framework and Roadmap for Smart Grid Interoperability

Standards, Release 4.0. Report, National Institute of Standards and Technology, 2021.21. Hossain, E.; Han, Z.; Poor, H.V. Smart grid communications and networking; Cambridge University Press, 2012.22. Ma, R.; Chen, H.H.; Huang, Y.R.; Meng, W. Smart grid communication: Its challenges and opportunities. IEEE

transactions on Smart Grid 2013, 4, 36–46.23. Samad, T.; Annaswamy, A.M. Controls for smart grids: Architectures and applications. Proceedings of the IEEE

2017, 105, 2244–2261.24. Souri, H.; Dhraief, A.; Tlili, S.; Drira, K.; Belghith, A. Smart metering privacy-preserving techniques in a

nutshell. Procedia Computer Science 2014, 32, 1087–1094.25. European Committee for Electrotechnical Standardization. CEN-CENELEC-ETSI Smart Grid Coordination

Group — Framework Document, 2012.26. Kimani, K.; Oduol, V.; Langat, K. Cyber security challenges for IoT-based smart grid networks. International

Journal of Critical Infrastructure Protection 2019, 25, 36–49.27. Kabalci, E.; Kabalci, Y. Introduction to smart grid architecture. In Smart Grids and Their Communication Systems;

Springer, 2019; pp. 3–45.

22 of 26

28. Norwegian Electrotechnical Committee. Vedlegg 1 – HAN Personvern – et tillegg til utredningen «AMS +HAN – om å gjøre sanntids måledata tilgjengelig for forbruker».

29. Norwegian Electrotechnical Committee. Norwegian HAN specification.30. Bouwmeester, J.; van der Linden, S.; Povalac, A.; Gill, E. Towards an innovative electrical interface standard for

PocketQubes and CubeSats. Advances in Space Research 2018, 62, 3423–3437.31. Fines, S. AMS og HAN-grensesnittet. NEKs Elsikkerhetskonferanse 2017. NEK, 2017.32. Faheem, M.; Shah, S.B.H.; Butt, R.A.; Raza, B.; Anwar, M.; Ashraf, M.W.; Ngadi, M.A.; Gungor, V.C. Smart grid

communication and information technologies in the perspective of Industry 4.0: Opportunities and challenges.Computer Science Review 2018, 30, 1–30.

33. Salinas, S.; Li, M.; Li, P.; Fu, Y. Dynamic energy management for the smart grid with distributed energyresources. IEEE Transactions on Smart Grid 2013, 4, 2139–2151.

34. Tushar, W.; Chai, B.; Yuen, C.; Smith, D.B.; Wood, K.L.; Yang, Z.; Poor, H.V. Three-party energy managementwith distributed energy resources in smart grid. IEEE Transactions on Industrial Electronics 2014, 62, 2487–2498.

35. Logenthiran, T.; Srinivasan, D. Intelligent management of distributed storage elements in a smart grid.Proceedings of IEEE Ninth International Conference on Power Electronics and Drive Systems. IEEE, 2011, pp.855–860.

36. Liu, C.; Chau, K.; Wu, D.; Gao, S. Opportunities and challenges of vehicle-to-home, vehicle-to-vehicle, andvehicle-to-grid technologies. Proceedings of the IEEE 2013, 101, 2409–2427.

37. Bach Andersen, P.; Hashemi, S.; Sousa, T.; Meier Soerensen, T.; Noel, L.; Christensen, B. The Parker Project:Cross-Brand Service Testing Using V2G. World Electric Vehicle Journal 2019, 10, 66.

38. Balakumar, P.; Sathiya, S. Demand side management in smart grid using load shifting technique. Proceedingsof IEEE International Conference on Electrical, Instrumentation and Communication Engineering (ICEICE).IEEE, 2017, pp. 1–6.

39. Mohagheghi, S.; Yang, F.; Falahati, B. Impact of demand response on distribution system reliability. Proceedingsof IEEE Power and Energy Society General Meeting. IEEE, 2011, pp. 1–7.

40. Tsado, Y.; Lund, D.; Gamage, K.A. Resilient communication for smart grid ubiquitous sensor network: State ofthe art and prospects for next generation. Computer Communications 2015, 71, 34–49.

41. Budka, K.C.; Deshpande, J.G.; Thottan, M.; others. Communication networks for smart grids; Springer, 2016.42. Balijepalli, V.M.; Pradhan, V.; Khaparde, S.; Shereef, R. Review of demand response under smart grid paradigm.

Proceedings of Innovative Smart Grid Technologies Conference (ISGT). IEEE, 2011, pp. 236–243.43. Güngör, V.C.; Sahin, D.; Kocak, T.; Ergüt, S.; Buccella, C.; Cecati, C.; Hancke, G.P. Smart Grid Technologies:

Communication Technologies and Standards. IEEE Transactions on Industrial Informatics 2011, 7.44. Fan, Z.; Kulkarni, P.; Gormus, S.; Efthymiou, C.; Kalogridis, G.; Sooriyabandara, M.; Zhu, Z.; Lambotharan,

S.; Chin, W.H. Smart grid communications: Overview of research challenges, solutions, and standardizationactivities. IEEE Communications Surveys & Tutorials 2012, 15, 21–38.

45. Wang, W.; Xu, Y.; Khanna, M. A survey on the communication architectures in smart grid. Computer networks2011, 55, 3604–3629.

46. Saputro, N.; Akkaya, K.; Uludag, S. A survey of routing protocols for smart grid communications. ComputerNetworks 2012, 56, 2742–2771.

47. Meng, W.; Ma, R.; Chen, H.H. Smart grid neighborhood area networks: a survey. IEEE Network 2014, 28, 24–32.48. Mohassel, R.R.; Fung, A.; Mohammadi, F.; Raahemifar, K. A survey on advanced metering infrastructure.

International Journal of Electrical Power & Energy Systems 2014, 63, 473–484.49. Aravind, E.; Vasudevan, S.K.; others. Smart meter based on real time pricing. Procedia Technology 2015,

21, 120–124.50. Parikh, P.P.; Kanabar, M.G.; Sidhu, T.S. Opportunities and challenges of wireless communication technologies

for smart grid applications. Proceedings of IEEE PES General Meeting. IEEE, 2010, pp. 1–7.51. Lee, J.J.; Kim, Y.H.; Bae, J.M.; Seo, J.K.; Nam, D.H.; Kim, J.Y.; In, D.S. AMR field trial on underground power

distribution line using BPLC. Proceedings of IEEE International Symposium on Power Line Communicationsand Its Applications. IEEE, 2011, pp. 204–208.

23 of 26

52. Emmanuel, M.; Rayudu, R. Communication technologies for smart grid applications: A survey. Journal ofNetwork and Computer Applications 2016, 74, 133–148.

53. Ai, Y.; Cheffena, M. Capacity analysis of PLC over Rayleigh fading channels with colored Nakagami-m additivenoise. Proceedings of IEEE Vehicular Technology Conference (VTC-Fall). IEEE, 2016, pp. 1–5.

54. Mathur, A.; Ai, Y.; Cheffena, M.; Bhatnagar, M.R. Performance of Hybrid ARQ over Power LineCommunications Channels. Proceedings of IEEE Vehicular Technology Conference (VTC2020-Spring). IEEE,2020, pp. 1–6.

55. Pinomaa, A.; Ahola, J.; Kosonen, A.; Nuutinen, P. Noise analysis of a power-line communication channel in anLVDC smart grid concept. Proceedings of IEEE International Symposium on Power Line Communications andIts Applications. IEEE, 2013, pp. 41–46.

56. Ai, Y.; Bhatnagar, M.R.; Cheffena, M.; Mathur, A.; Sedakov, A. Game-theoretical analysis of PLC systemperformance in the presence of jamming attacks. Proceedings of International Conference on Decision andGame Theory for Security. Springer, 2017, pp. 74–90.

57. Ai, Y.; Ohtsuki, T.; Cheffena, M. Performance analysis of PLC over fading channels with colored Nakagami-mbackground noise. Proceedings of IEEE Vehicular Technology Conference (VTC Spring). IEEE, 2017, pp. 1–6.

58. Ai, Y.; Kong, L.; Cheffena, M.; Chatzinotas, S.; Ottersten, B. On Performance Characterization of CascadedMultiwire-PLC/MIMO-RF Communication System. arXiv preprint arXiv:2010.04099 2020.

59. Song, J.; Ding, W.; Yang, F.; Yang, H.; Yu, B.; Zhang, H. An indoor broadband broadcasting system based onPLC and VLC. IEEE Transactions on Broadcasting 2015, 61, 299–308.

60. Mathur, A.; Bhatnagar, M.R.; Ai, Y.; Cheffena, M. Performance analysis of a dual-hop wireless-power linemixed cooperative system. IEEE Access 2018, 6, 34380–34392.

61. Hazen, M.E. The technology behind homeplug av powerline communications. Computer 2008, 41, 90–92.62. Pinomaa, A.; Ahola, J.; Kosonen, A.; Nuutinen, P. HomePlug green PHY for the LVDC PLC concept:

Applicability study. Proceedings of IEEE International Symposium on Power Line Communications and ItsApplications (ISPLC). IEEE, 2015, pp. 205–210.

63. Bian, D.; Kuzlu, M.; Pipattanasomporn, M.; Rahman, S. Analysis of communication schemes for advancedmetering infrastructure (AMI). Proceedings of IEEE PES General Meeting| Conference & Exposition. IEEE,2014, pp. 1–5.

64. Karagiannis, G.; Pham, G.T.; Nguyen, A.D.; Heijenk, G.J.; Haverkort, B.R.; Campfens, F. Performance of LTEfor smart grid communications. Proceedings of International Conference on Measurement, Modelling, andEvaluation of Computing Systems and Dependability and Fault Tolerance. Springer, 2014, pp. 225–239.

65. Surgiewicz, R.; Strom, N.; Ahmed, A.; Ai, Y. LTE uplink transmission scheme. Chalmers University of Technology2014.

66. Cheng, P.; Wang, L.; Zhen, B.; Wang, S. Feasibility study of applying LTE to Smart Grid. Proceedings of IEEEInternational workshop on smart Grid Modeling and Simulation (SGMS). IEEE, 2011, pp. 108–113.

67. Dragicevic, T.; Siano, P.; Prabaharan, S.; others. Future generation 5G wireless networks for smart grid: Acomprehensive review. Energies 2019, 12, 2140.

68. De Dutta, S.; Prasad, R. Security for smart grid in 5G and beyond networks. Wireless Personal Communications2019, 106, 261–273.

69. Mao, R.; Julka, V. WiMAX for advanced metering infrastructure. Proceedings of International Conference onGreen and Ubiquitous Technology. IEEE, 2012, pp. 15–19.

70. Usman, A.; Shami, S.H. Evolution of communication technologies for smart grid applications. Renewable andSustainable Energy Reviews 2013, 19, 191–199.

71. Rengaraju, P.; Lung, C.H.; Srinivasan, A. Communication requirements and analysis of distribution networksusing WiMAX technology for smart grids. Proceedings of International Wireless Communications and MobileComputing Conference (IWCMC). IEEE, 2012, pp. 666–670.

72. Parvez, I.; Sundararajan, A.; Sarwat, A.I. Frequency band for HAN and NAN communication in Smart Grid.Proceedings of IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG), 2014, pp.1–5.

24 of 26

73. Mahmood, A.; Javaid, N.; Razzaq, S. A review of wireless communications for smart grid. Renewable andsustainable energy reviews 2015, 41, 248–260.

74. Zafar, R.; Mahmood, A.; Razzaq, S.; Ali, W.; Naeem, U.; Shehzad, K. Prosumer based energy management andsharing in smart grid. Renewable and Sustainable Energy Reviews 2018, 82, 1675–1684.

75. Burunkaya, M.; Pars, T. A smart meter design and implementation using ZigBee based wireless sensor networkin smart grid. Proceedings of International Conference on Electrical and Electronic Engineering (ICEEE). IEEE,2017, pp. 158–162.

76. Ai, Y.; Cheffena, M.; Li, Q. Radio frequency measurements and capacity analysis for industrial indoorenvironments. Proceedings of European Conference on Antennas and Propagation (EuCAP). IEEE, 2015, pp.1–5.

77. Cheffena, M. Industrial Wireless Communications over the Millimeter Wave Spectrum: Opportunities andChallenges. IEEE Communications Magazine 2016, 54.

78. Ai, Y.; Cheffena, M.; Li, Q. Power delay profile analysis and modeling of industrial indoor channels. Proceedingsof European Conference on Antennas and Propagation (EuCAP). IEEE, 2015, pp. 1–5.

79. Bekara, C. Security issues and challenges for the IoT-based smart grid. FNC/MobiSPC, 2014, pp. 532–537.80. Samuel, S.S.I. A review of connectivity challenges in IoT-smart home. Proceedings of MEC International

conference on big data and smart city (ICBDSC). IEEE, 2016, pp. 1–4.81. Granelli, F.; Domeniconi, D.; Da Fonseca, N.L.; Tsetsgee, B. On the Usage of WiFi and LTE for the Smart Grid.

Proceedings of International Conference on Ubi-Media Computing and Workshops. IEEE, 2014, pp. 1–5.82. Li, L.; Xiaoguang, H.; Ke, C.; Ketai, H. The applications of wifi-based wireless sensor network in internet of

things and smart grid. Proceedings of IEEE Conference on Industrial Electronics and Applications. IEEE, 2011,pp. 789–793.

83. Meloni, A.; Atzori, L. The role of satellite communications in the smart grid. IEEE Wireless Communications2017, 24, 50–56.

84. De Sanctis, M.; Cianca, E.; Araniti, G.; Bisio, I.; Prasad, R. Satellite communications supporting internet ofremote things. IEEE Internet of Things Journal 2015, 3, 113–123.

85. Abrahamsen, F.E.; Ai, Y.; Wold, K.; Mohamed, M. Free-Space Optical Communication: From Space to Groundand Ocean. IEEE Potentials 2021.

86. Ai, Y.; Mathur, A.; Cheffena, M.; Bhatnagar, M.R.; Lei, H. Physical layer security of hybrid satellite-FSOcooperative systems. IEEE Photonics Journal 2019, 11, 1–14.

87. Verma, G.D.; Mathur, A.; Ai, Y.; Cheffena, M. Secrecy performance of FSO communication systems withnonzero boresight pointing errors. IET Communications 2020.

88. Ai, Y.; Mathur, A.; Lei, H.; Cheffena, M.; Ansari, I.S. Secrecy enhancement of RF backhaul system with parallelFSO communication link. Optics Communications 2020, 475, 126193.

89. Ai, Y.; Mathur, A.; Verma, G.D.; Kong, L.; Cheffena, M. Comprehensive Physical Layer Security Analysis ofFSO Communications over Mlaga Channels. IEEE Photonics Journal 2020.

90. Sivakumar, P.; Nagaraju, R.; Samanta, D.; Sivaram, M.; Hindia, M.N.; Amiri, I.S. A novel free spacecommunication system using nonlinear InGaAsP microsystem resonators for enabling power-control towardsmart cities. Wireless Networks 2020, 26, 2317–2328.

91. Haider, M.F.; Siddique, A.R.; Alam, S. An approach to implement frees space optical (FSO) technology forsmart village energy autonomous systems. Far East Journal of Electronics and Communications 2018, 18, 439–456.

92. Moslehi, K.; Kumar, R. Smart grid-a reliability perspective. Innovative Smart Grid Technologies (ISGT). IEEE,2010, pp. 1–8.

93. Ai, Y.; Cheffena, M. A comparative study of wireless channel propagation characteristics in industrial andoffice environments. Proceedings of International Symposium on Antennas and Propagation (ISAP), 2015.

94. Güzelgöz, S.; Arslan, H.; Islam, A.; Domijan, A. A review of wireless and PLC propagation channelcharacteristics for smart grid environments. Journal of Electrical and Computer Engineering 2011, 2011.

95. Ai, Y.; Andersen, J.B.; Cheffena, M. Path-loss prediction for an industrial indoor environment based on roomelectromagnetics. IEEE Transactions on Antennas and Propagation 2017, 65, 3664–3674.

25 of 26

96. Al-Samman, A.M.; Mohamed, M.; Ai, Y.; Cheffena, M.; Azmi, M.H.; Rahman, T.A. Rain attenuationmeasurements and analysis at 73 GHz E-band link in tropical region. IEEE Communications Letters 2020,24, 1368–1372.

97. Ai, Y.; Cheffena, M. On multi-hop decode-and-forward cooperative relaying for industrial wireless sensornetworks. Sensors 2017, 17, 695.

98. Zhang, J.; Hasandka, A.; Wei, J.; Alam, S.; Elgindy, T.; Florita, A.R.; Hodge, B.M. Hybrid communicationarchitectures for distributed smart grid applications. Energies 2018, 11, 871.

99. Yan, Y.; Qian, Y.; Sharif, H.; Tipper, D. A survey on cyber security for smart grid communications. IEEECommunications Surveys & Tutorials 2012, 14, 998–1010.

100. Saxena, N.; Xiong, L.; Chukwuka, V.; Grijalva, S. Impact evaluation of malicious control commands incyber-physical smart grids. IEEE Transactions on Sustainable Computing 2018.

101. Yang, Q.; Barria, J.A.; Green, T.C. Communication infrastructures for distributed control of power distributionnetworks. IEEE Transactions on Industrial Informatics 2011, 7, 316–327.

102. Sgouras, K.I.; Birda, A.D.; Labridis, D.P. Cyber attack impact on critical smart grid infrastructures. Proceedingsof Innovative Smart Grid Technologies Conference (ISGT). IEEE, 2014, pp. 1–5.

103. Iyer, S. Cyber security for smart grid, cryptography, and privacy. International Journal of Digital MultimediaBroadcasting 2011, 2011.

104. He, D.; Wang, H.; Khan, M.K.; Wang, L. Lightweight anonymous key distribution scheme for smart grid usingelliptic curve cryptography. IET Communications 2016, 10, 1795–1802.

105. Gope, P.; Sikdar, B. Privacy-aware authenticated key agreement scheme for secure smart grid communication.IEEE Transactions on Smart Grid 2018, 10, 3953–3962.

106. Sharma, M.; Agarwal, A. Survey on authentication and encryption techniques for smart grid communication.Proceedings of India International Conference on Power Electronics (IICPE). IEEE, 2016, pp. 1–5.

107. Nicanfar, H.; Leung, V.C. Password-authenticated cluster-based group key agreement for smart gridcommunication. Security and Communication Networks 2014, 7, 221–233.

108. Lee, E.K.; Gerla, M.; Oh, S.Y. Physical layer security in wireless smart grid. IEEE Communications Magazine2012, 50, 46–52.

109. Ai, Y.; Cheffena, M.; Ohtsuki, T.; Zhuang, H. Secrecy performance analysis of wireless sensor networks. IEEESensors Letters 2019, 3, 1–4.

110. Islam, S.N.; Baig, Z.; Zeadally, S. Physical layer security for the smart grid: vulnerabilities, threats, andcountermeasures. IEEE Transactions on Industrial Informatics 2019, 15, 6522–6530.

111. Ai, Y.; Kong, L.; Cheffena, M. Secrecy outage analysis of double shadowed Rician channels. Electronics Letters2019, 55, 765–767.

112. Act of 14 April 2000 No. 31 relating to the processing of personal data (Personal Data Act).113. Norwegian Electrotechnical Committee. AMS + HAN Om å gjøre sanntid måledata tilgjengelig for forbruker.114. Tan, S.; De, D.; Song, W.Z.; Yang, J.; Das, S.K. Survey of security advances in smart grid: A data driven

approach. IEEE Communications Surveys & Tutorials 2017, 19, 397–422.115. Datatilsynet. Automatisk strømmåling, 2018.116. Kumar, S.; Gaur, N.; Kumar, A. Developing a Secure Cyber Ecosystem for SCADA Architecture. Proceedings

of International Conference on Computing Methodologies and Communication (ICCMC). IEEE, 2018, pp.559–562.

117. Sun, C.C.; Hahn, A.; Liu, C.C. Cyber security of a power grid: State-of-the-art. International Journal of ElectricalPower & Energy Systems 2018, 99, 45–56.

118. Liang, G.; Weller, S.R.; Zhao, J.; Luo, F.; Dong, Z.Y. The 2015 Ukraine blackout: Implications for false datainjection attacks. IEEE Transactions on Power Systems 2016, 32, 3317–3318.

119. Kim, M. A survey on guaranteeing availability in smart grid communications. Proceedings of InternationalConference on Advanced Communication Technology (ICACT). IEEE, 2012, pp. 314–317.

120. Kshetri, N.; Voas, J. Hacking power grids: A current problem. Computer 2017, 50, 91–95.121. Fingrid Oyj. ENTSO-E: cyber intrusion on its office network, 2020.

26 of 26

122. Huseinovic, A.; Mrdovic, S.; Bicakci, K.; Uludag, S. A Survey of Denial-of-Service Attacks and Solutions in theSmart Grid. IEEE Access 2020, 8, 177447–177470.

123. Saxena, N.; Choi, B.J. State of the art authentication, access control, and secure integration in smart grid.Energies 2015, 8, 11883–11915.

124. Quinn, E.L. Privacy and the new energy infrastructure. Available at SSRN 1370731 2009.125. Hart, G.W. Nonintrusive appliance load monitoring. Proceedings of the IEEE 1992, 80, 1870–1891.126. Prudenzi, A. A neuron nets based procedure for identifying domestic appliances pattern-of-use from energy

recordings at meter panel. Proceedings of IEEE Conference on Power Engineering Society Winter Meeting.IEEE, 2002, Vol. 2, pp. 941–946.