Journal Paper. Convergence of Smart Grid ICT architectures for the last mile. Michele Albano Luis Lino Ferreira Luis Miguel Pinho CISTER-TR

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1 Journal Paper Convergence of Smart Grid ICT architectures for the last mile Michele Albano Luis Lino Ferreira Luis Miguel Pinho CISTER-TR /02

2 Journal Paper CISTER-TR Convergence of Smart Grid ICT architectures for the last... Convergence of Smart Grid ICT architectures for the last mile Michele Albano, Luis Lino Ferreira, Luis Miguel Pinho CISTER Research Center Polytechnic Institute of Porto (ISEP-IPP) Rua Dr. António Bernardino de Almeida, Porto Portugal Tel.: , Fax: Abstract The evolution of the electrical grid into a smart grid, allowing user production, storage and exchange of energy, remote control of appliances, and in general optimizations over how the energy is managed and consumed, is also an evolution into a complex Information and Communication Technology (ICT) system. With the goal of promoting an integrated and interoperable smart grid, a number of organizations all over the world started uncoordinated standardization activities, which caused the emergence of a large number of incompatible architectures and standards. There are now new standardization activities which have the goal of organizing existing standards and produce best practices to choose the right approach(es) to be employed in specific smart grid designs. This paper follows the lead of NIST and ETSI/CEN/CENELEC approaches in trying to provide taxonomy of existing solutions; our contribution reviews and relates current ICT state-of-the-art, with the objective of forecasting future trends based on the orientation of current efforts and on relationships between them. The resulting taxonomy provides guidelines for further studies of the architectures, and highlights how the standards in the last mile of the smart grid are converging to common solutions to improve ICT infrastructure interoperability. CISTER Research Center 1

3 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 11, NO. 1, FEBRUARY Convergence of Smart Grid ICT Architectures for the Last Mile Michele Albano, Luis Lino Ferreira, and Luís Miguel Pinho, Member, IEEE Abstract The evolution of the electrical grid into a smart grid, allowing user production, storage, and exchange of energy; remote control of appliances; and, in general, optimizations over how the energy is managed and consumed, is an evolution into a complex information and communication technology (ICT) system. With the goal of promoting an integrated and interoperable smart grid, a number of organizations all over the world started uncoordinated standardization activities, which caused the emergence of a large number of incompatible architectures and standards. There are now new standardization activities that have the goal of organizing existing standards and produce best practices to choose the right approach(es) to be employed in specific smart grid designs. This paper follows the lead of the National Institute of Standards and Technology (NIST) and the European Telecommunications Standards Institute/European Committee for Standardization/European Committee for Electrotechnical Standardization (ETSI/CEN/CENELEC) approaches in trying to provide taxonomy of existing solutions; our contribution reviews and relates current ICT state of the art with the objective of forecasting future trends based on the orientation of current efforts and on relationships between them. The resulting taxonomy provides guidelines for further studies of the architectures, and highlights how the standards in the last mile of the smart grid are converging to common solutions to improve ICT infrastructure interoperability. Index Terms Common information model (CIM), energy saving, International Electrotechnical Commission (IEC), protocols, survey. I. INTRODUCTION T HE ENERGY grid has evolved from a pipeline that brings electricity from the production plant (production domain) to the final user (consumption domain) through the transmission and distribution domains, to a much more complex system. In this novel paradigm, multiple actors of these four domains can interact, produce energy, as well as store it and exchange it with other (peer) actors, in order to enhance the grid s efficiency. The concept of the smart grid has emerged, in which Manuscript received January 28, 2014; revised May 15, 2014 and September 17, 2014; accepted November 16, Date of publication December 08, 2014; date of current version February 02, This work was supported in part by the National Funds through FCT (Portuguese Foundation for Science and Technology); in part by the European Union (EU) Advanced Research & Technology for EMbedded Intelligence and Systems (ARTEMIS) Joint Undertaking (JU) funding, within the Embedded intelligent COntrols for buildings with Renewable generation and storage (ENCOURAGE) project, Ref. ARTEMIS/0002/2010; in part by JU under Grant , within Arrowhead project, Ref. ARTEMIS/001/2012; and in part by JU under Grant Paper no. TII The authors are with the Research Centre in Real-Time and Embedded Computing Systems (CISTER), Instituto Superior de Engenharia do Porto/Instituto Politécnico do Porto (ISEP/IPP), Porto , Portugal. Color versions of one or more of the figures in this paper are available online at Digital Object Identifier /TII the interaction between the involved actors is articulated into an energy plane and a data plane. The new data plane relates to the information that is used to drive the efficient allocation of energy, to different actors as well as to different storage units and energy-consuming appliances. Smart grids are nowadays a very complex interplaying of different systems at different levels. Existing smart grid systems and standards explore a large problem space to attain the same goal of energy efficiency, and they end up featuring many common points and many differences as well. There are numerous challenges to address, such as the low-level communication technologies to be employed [1], or the issues arising when integrating distributed energy resources (DERs) [2] or electrical vehicles [3] in the grid. In this paper, the focus is on the interaction of final domestic and commercial users with the smart grid information and communication technology (ICT) system, and on involved systems and standards. A common characteristic of smart grids is that the embedded devices deployed into the final user s home (the sensors and actuators that manage energy and data planes) are too limited in computational power to be able to decode a complex protocol; therefore the topology of the smart grid is usually centered around a gateway installed in the users houses. The gateway manages a subset of the sensors and actuators deployed in the house using adequate protocols, and it is connected to the internet to interact with services for energy management via a data plane. The in-house topology usually carries the name of home area network (HAN); in the rest of this work, the gateway installed in the user s HAN will be called HAN gateway. Another common characteristic of a typical smart grid system is its size and complexity. In fact, an energy grid usually serves a very large number of users. Together with the fact that each actor is controlled by an independent entity, the emerging complexity is overwhelming for traditional centralized data management paradigms. Differences between smart grid approaches usually regard the employed protocols and the management paradigm for the data. To offer an estimate of the complexity of the ICT system serving a heterogeneous smart grid, the number of involved protocols can be considered. Potentially, a different protocol can be used for each class of connections in the system, thus between each pair of classes of actors; in this sense, the number of involved protocols in a system with n classes of actors may grow as the number of lines between n points, i.e., ( n 2 ), which grows as fast as n 2. While standardization processes can decrease the complexity of the data plane, too many standards and architectures have been proposed in the past. In the last few years, novel standardization efforts addressed the IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See for more information.

4 188 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 11, NO. 1, FEBRUARY 2015 problem of harmonization and interoperability between existing approaches by means of proposing meta-architectures, which are families of architectural approaches that embrace multiple existing standards and act as frameworks for the positioning of existing standards in a common vision. Therefore, standardization efforts are being spent to design a small number of design patterns [4], where the actors communicate with each other using a small set of standardized protocols [5]. This paper addresses the complexity of the current smart grid, focusing on the enabling ICT architectures, particularly in what concerns the interaction with the users premises (the last mile), and the technologies that are leading standardization trends for the future smart grid. With this aim in mind, after reporting related work in Section II, Sections III VI describe selected current state-of-the-art standards, focusing on the correlated architectures, and the application layer protocols, extending to other layers only when they were developed especially for the smart grid, such as in the case of smart energy profile (SEP) of ZigBee [6]. Since the subject at hand is in a phase of accelerated development, a plethora of standards were and are being developed. Our analysis focuses in a few relevant standardization initiatives, leveraging on the market analysis reported by National Institute of Standards and Technology (NIST) [7] in order to identify the main characteristics of the ICT architectures that will compose the emerging interoperable smart grid. Afterward, in Section VII, a case study exemplifies the application of the proposed taxonomy to an existing architecture to both provide a better understanding of the system, and to support the design of its internals. Supported by the taxonomy and the case study, Section VIII delves into the relationship between standardization efforts and draws conclusions on the emerging convergence of current standards. II. RELATED WORK A large number of previous works have surveyed smart grids and related protocols, on different topics and viewpoints. Not pretending to provide a fully exhaustive list, we here analyze several related works, which provide complementary perspectives to this survey. One important domain that has been extensively analyzed is the communication protocols in the power grid. The work in [8] coped with the usage on the routing protocol for low power and lossy networks (RPL) when used on the devices of the advanced metering infrastructure in the user s HAN. The work in [9] focused on the technologies enabling the smart grid, and in particular on the protocols that are employed in the different domains of the smart grid. Similar to this paper, Gungor et al. [10], [11] surveyed the state of the art of smart grid communications and discussed the still-open research issues in the field, while Usman and Shami [12] take an historical perspective and focuses on the communication protocols that evolved from the original power line communication to current wireless approaches; still, these works focus in the communication protocols, while our analyzes goes through architectures and protocols alike, looking for evolution patterns and convergence points for the future smart grids. Approaching the topic from a different viewpoint, Ye et al. [13] and Wang and Lu [14] considered the security features and requirements of current and future smart grids, the first on an abstract level and the second considering commonly deployed wireless protocols; these papers do not describe techniques to current smart grid standards and architectures for the connection to users HANs. The works in [15] and [16] analyzed the standardization activities in Europe, but focused more on regulations and smart meter standardization, while our work starts from taxonomy of existing standards for user side smart grids and from a hierarchical organization of current architectures into meta-architectures/architectures/design standards to delve into current trends in the industry. The analysis in this survey focuses on the ICT architectures themselves, particularly in what concerns the interaction with the users premises, to expose the technologies that are leading standardization trends for the future smart grid. Apart from attaining the result of identifying an emerging standardization trend of current standards, the structured taxonomy is also a novel contribution by itself with respect to the current state-of-the-art analysis. Regardless of the architecture employed by the smart grid, the huge quantity of collected and used data substantially increased the need for storing and processing large volumes of data. It is orthogonal to the analysis presented in this paper, but it is important to note the efforts devoted to develop improved data bases both of structured query language (SQL) and nosql kinds and to optimize them to store and process time series data in real time [17]. Also, prototypes of systems using big data techniques on smart grid data have already been deployed. For example, Simmhan et al. [18] describe a system deployed in USA that leverages standard tools such as the Hadoop MapReduce platform, optimized to scale with the smart grid size by harvesting the elasticity of private cloud infrastructures. The results in [19] describe a similar system deployed in Europe, more focused on the market side and on the strategic planning, which uses a cloud computing model for managing the real-time streams of smart grid data for the near realtime information retrieval needs of the different energy market actors. The extensive work in [20] focuses on database systems, and delves deeply into the analysis of data mining for the electrical power grid comprising the interrelated subsystems of power generation, transmission, distribution, and utilization. Another work [21] presents a more holistic approach, which embraces the application of big data technologies to the critical infrastructure of the electrical grid, how to implement data analytics, coping with smart grid legislation, and how to leverage on the processed data to realize returns on smart grid investments. Regarding the data models to be used to ease the management of smart grid data, research works [22], [23] are debating how to realize the double goal of information integration and efficient data processing. Both works considered the common information model (CIM) [24] as a viable candidate to be either [22] reified into a database tailored to allow an efficient use of the query processing engine Hadoop or, as in [23], integrated into novel architectures for the management of high data volumes, which are then made available to cross-department analytical applications and enterprise-wide decision-making support.

5 ALBANO et al.: CONVERGENCE OF SMART GRID ICT ARCHITECTURES 189 III. STANDARDIZATION EFFORTS FOR SMART GRIDS The usage of a large number of legacy and closed technologies in smart grids has the potential of creating several noninteracting networks in each user s HAN, one per vendor and/or home system. A number of standardization bodies all over the world have reacted to this situation by producing standards, but these uncoordinated activities brought even more chaos in the field, leading to further standardization activities, which have the goal of organizing existing standards and produce best practices to be employed in a smart grid design. The taxonomy of existing solutions for smart grids can be driven, at the top level, by a vision of system engineering, which builds systems by first devising the system architecture, and then refining it into a system design by completing it with data encoding, protocols, interfaces, etc. All approaches provide general elements for the architecture of the proposed smart grid, but then target different parts of the grid and report different levels of detail. In order to address these different views, this work proposes to categorize existing ICT solutions for smart grids into three sets. Meta-architectures provide a family of ontologies to map existing and future architectures onto, i.e., they provide guidelines on how to use architectural standards. This group comprises the efforts done by NIST [7] and European Committee for Standardization (CEN), European Committee for Electrotechnical Standardization (CENELEC), and European Telecommunications Standards Institute(ETSI)[25] approaches. Architectural standards limit their content to the proposed smart grid architecture and to the functionalities that must be supported. ETSI machine to machine (M2M) [26] and device language message specification (DLMS)/companion specification for energy metering (COSEM) [27] belong to this group. Design standards go deep into low-level details, like data encoding and protocols to be employed. Standards like CIM [24] by International Electrotechnical Commission (IEC) and SEP [28] are part of this group. This work leverages on the methodical market analysis performed by meta-architectures proponents (e.g., the list of core standards in Section IV-C of [7] and in Section 2 of [25]), to decide which architectures and design standards to consider as representatives of the respective groups. For this, the next three sections provide examples for each of the categories identified above: Section IV copes with meta-architectures; Section V describes architectural standards; and Section VI provides details regarding design standards. IV. META-ARCHITECTURAL STANDARDS A. NIST Canonical Data Model (CDM) The NIST put forward an initiative to coordinate the smart grids standardization process in the USA. Its efforts are coordinated by the smart grid interoperability panel (SGIP) and by the Smart Grid Federal Advisory Committee, where the first is mostly responsible for the standard definition and the second is mainly responsible for the strategy and evaluation of the NIST effort. The NIST has been pushing forward efforts to bring together manufacturers, consumers, energy providers, and Fig. 1. NIST operational domains. regulators to develop interoperable standards for smart grids. Being the main objective of NIST to enable several different smart grid systems and their components to interoperate, the canonical data model (CDM) was built upon a unifying framework of interfaces, protocols, and other consensus standards. The main results of this initiative are described in the NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 2.0 [7], where a reference architecture is proposed. Instead of providing a concrete architecture, the document provides a family of ontologies to map existing and future architectures onto. It also contains an analysis on the requirements of the smart grids and how existing standards can cope with these requirements. It is completed by a long list of standards [currently 61 standards, spanning from NIST Federal Information Processing Standards (FIPS) for smart grid cryptographic modules accreditation, to IEEE 1901 for broadband communication over power lines] that are compatible with the NIST vision, and a recommendation on which kinds of applications to target with each standard. NIST defines seven domains, as depicted in Fig. 1, which are high-level groupings of organizations, buildings, individuals, systems, devices that have similar objectives and that participate in similar types of applications. 1) Bulk Generation, Transmission, Distribution, and Customer: These domains correspond roughly to the original electrical pipeline, and operate at the voltages typical of their traditional counterparts. The most prominent novelties introduced by the smart grid are that all components may store energy for later distribution/usage; all the components can produce electricity, integrating microplants accessing renewable energy sources with the primary power plants of the bulk generation domain; extensive online collection of data on energy production and consumption in every part of the grid; remote control of users appliances to limit energy-hungry processes when less energy is available; massive usage of ICTs to leverage data for optimization of energy consumption. All the components extract information from their systems to inform stakeholders and other systems in real time, and use data coming from other components and external services, such as weather forecasts, to optimize their operation. 2) Markets: Electricity producers and traders participating in electricity markets, where electricity is bought and sold via futures contracts. DERs allow actors in the customer and distribution domains to produce electricity, and storage techniques can allow the later usage or redistribution of the energy, thus the customers can be the actors selling the energy, inverting the usual flows of energy and money. 3) Service Providers: The organizations handling thirdparty operations on the other domains. These operations

6 190 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 11, NO. 1, FEBRUARY 2015 comprise the management of the ICT infrastructure supporting the data plane of the smart grid and interaction with customers, and the services provided span from the monitoring of room occupancy to optimize heating, ventilation, and air conditioning (HVAC) systems utilization, to interaction with social networks to publish energy consumption in different sections of a cell [29], to the management of outage and the planning of smart grid expansion and maintenance. Most third-party services that have yet to be invented are part of this domain. 4) Operations: This domain controls the energy plane of the smart grid. The actors of this domain perform the maintenance, upgrade and analysis of electricity connections, and control the actual transference of energy between parties, which is driven by the data exchanges in the ICT infrastructure. The goal of the process proposed by NIST is the orchestration of complex smart grids into a common vision, which enables their interoperation, to allow data exchanges between the different components of the system. The NIST model also addresses the problem of the scalability of smart grids by considering the complexity of the interconnections between actors, and hence it proposes adhering to a general semantic model called CDM, with the goal of mapping the semantic models of other architectures onto it. The interface of the application producing the data has the obligation to transform its output to the canonical form, and then the receiver interface has the obligation to transform from the canonical form to the receiver form. Where multiparty exchanges exist, all parties transform only to and from the canonical form and never need to know the internal details of any other application. The NIST approach proposes a strategy for the migration from current custom energy grids to smart grids in the most graceful way, by upgrading the different parts of the grid gradually and with a strategy that takes into account regulatory and economical aspects, and predicted maturity of involved technologies in the close future. Finally, the NIST approach can be used to map a scenario over the standards, to investigate whether the considered standards and protocols are covering the scenario at hand, and eventually discover the standardization gaps when considering a particular use case. As far as security and encoding formats are concerned, CDM is a meta-architecture and thus it is very general and can adopt different kinds of security measures and encoding formats, on which we provide some details in Section V (architectures) and Section VI (design standards). B. ETSI/CEN/CENELEC Smart Grid Architecture Model The joint effort of CEN, CENELEC, and ETSI developed a meta-model called smart grid architecture models (SGAM). The work of CEN/CENELEC/ETSI started with a Joint Working Group (JWG) on standards for smart grids, which produced in March 2011 a report addressing the landscape of standards [30] and recommendations for standardization in Europe [31]. On March 2011, the European Commission (EC) issued a standardization mandate M/490 requesting these organizations to develop the European standards framework for the field of smart grids. For that purpose, the three organizations created the CEN/CENELEC/ETSI Smart Grids Coordination Fig. 2. ETSI/CEN/CENELEC extension to NIST model. Group (SG-CG). The SG-CG delivered a report on the reference architecture for the European smart grid [25]. The results of the report that are of major interest to this paper are the conceptual model, which describes the main actors in the smart grids and their main interactions, and the first SGAM, which is composed by a set of architectural views focused on different viewpoints (different stakeholders, analysis of technical or economical or managerial requirements, and different detail levels). Like in the case of the NIST model, SGAM provides domains to map existing and proposed architectures onto. The main difference between the two models is that SGAM (Fig. 2) is specialized in the direction of DERs usage (see Section of [25]). Even though DERs were already introduced in the NIST model and were already part of their distribution and customer domains, the SGAM is a specialization that provides more details on the adoption of DER usage. The extension to the NIST model is important to fulfill European requirements for providing distributed local generation of energy. In the SGAM, the only actors that can produce energy are the bulk generation and the DER, and are characterized by different voltages and connections with other actors on the technological level, as well as different goals and interaction with the markets on the socioeconomical level. The DER can be a user that produces its own energy and sells the surplus, but also a company that produces energy as part of its business model. The DER is distributed all over the territory and one of its goals is to save energy by allowing customers to consume the energy in the proximity of its production, since a transmission over long distances would incur in energy losses for both the actual transmission and for the conversion to/from the voltage of the transmission domain. The meta-architecture proposed in the SGAM (Fig. 3) is articulated over a small number of viewpoints (conceptual, functional, communication, information security, and information architectures). The viewpoints target mainly the ICT aspects of the system, and pursue the goals of upgradeability, simplicity and reuse, to attain a cheap evolution from the traditional energy grid to the smart grid. The resulting model is articulated over a small set of layers (business, function, information, communication, and component layers), the domains involved in the transport of the electricity (generation, transmission, distribution, DER, and customer premises), and the zones, which represent different levels of aggregation in the power system management (whole operations on the energy market like trading energy, down to single technical processes on a generator). This complex model allows any standard to

7 ALBANO et al.: CONVERGENCE OF SMART GRID ICT ARCHITECTURES 191 Fig. 3. Smart grid architecture model (SGAM) [25]. position itself, to describe which actors it operates on, the granularity of its operations, and which level of data abstraction is used. For example, communication via general packet radio service (GPRS) can be used on the communication layer, it usually coordinates actors belonging to the distribution domain and the DER domain, and the granularity of the resulting interaction is between field zone (auxiliary equipments in the power grid that protect, control and monitor the process of the power system) and enterprise zone (commercial and organizational processes that involve whole utilities). As in Section IV-A, the SGAM is a meta-architecture and can adopt different kinds of security measures and encoding formats, which are further described in the following sections. A. ETSI M2M V. ARCHITECTURAL STANDARDS ETSI Technical Committee for M2M (TC M2M) is involved into providing a European response to the EC mandates on smart grids (M/490), which led to the definition of the SGAM described in the previous section, and smart metering (M/441). TC M2M covers five thematic areas related to M2M communication (smart metering, ehealth, connected consumers, automotive, and city automation), and it addressed smart meters by an application profile of the broader M2M standard. Incidentally, the two application areas that are under fastest development are e-health and smart grids [32] that aim to leverage the M2M generic platform to enrich application capabilities in this context. M2M technology implementations are now available by multiples vendors, who basically provide the communication stack, making it available to the original equipment manufacturer (OEM). The first is mostly the case of telecom operators all over the world (see, e.g., [33]). More general implementations of M2M technology are widely available as both closed source, such as the NOS M2M starter kit [34], and open source, such as the implementation by the eclipse community [35]. The M2M TC has been working on a generic platform to deliver M2M services that can support the vertical domains of smart metering and smart grid. The rationale behind this approach is that the smart grid needs a decentralized organization instead of the hierarchical organization of traditional electricity grids, and a higher volume of data exchanges for its operations. The M2M smart metering use case [26], which addresses the M/441 mandate, prescribes that the meter is empowered with real-time transmission of data regarding energy consumption, which is then used by the customer to tune up its energy usage, and by the electricity company to manage the electricity network. The M2M platform devoted to smart metering is designed as horizontal communication architecture, composed by three different categories of units, the end device (smart meter), the HAN gateway and the service platform. ETSI M2M had a big economic impact in Europe. Some European countries have already started a massive installation of smart meters based on ETSI M2M, such as ENEL, Italy s largest power company, which has installed over 30 million M2M-based smart meters in its customer base between 2000 and 2005, spending 2.1 billion Euros on a project that estimates savings of 500 million Euros/ year [36]. The European Union as a whole is going toward the adoption of at least M2M smart meters, and possibly more advanced smart grids enablers, by 2020, with a predicted volume of 180 million equipments (one unit per household) plus more smart meters to cope with electric cars, considered by the mandate M/468 [37]. When including other countries, the resulting volume of the smart metering business will amount to 1 billion smart grids installations [38]. M2M platforms are based on representational state transfer (REST) [39], which prescribes that interaction between components must be stateless, queries are initiated by a client on a server, and clients interact with data using four basic operations (create, read, update, and delete) that are inspired on the operation of the World Wide Web. In the case of M2M, sensors and actuators are represented by resources located into the servers, resources have system-wide unique names, and the server does not store any context information regarding the interaction with the client. M2M does not specify protocols, still it recommends to encode data using constrained application protocol (CoAP) [40] or extensible markup language/efficient xml interchange (XML/EXI) [41], and to use transport layer security (TLS), extensible authentication protocol (EAP), or generic bootstrapping architecture (GBA) to set up the communication channels and perform data exchange. B. DLMS/COSEM DLMS/COSEM is an architectural standard that addresses data exchange for meter reading, tariff, and load control. Since 2006, the international community adopted the IEC series as the IEC International Standard version of the DLMS/COSEM specification [27]. In particular, IEC uses DLMS to model object-oriented services and support exchanging messages among distributed devices, and COSEM to define interfaces and the object-oriented representations of smart meters.

8 192 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 11, NO. 1, FEBRUARY 2015 DLMS/COSEM sets the rules for data exchange with and between energy meters. COSEM models physical metering equipment as a set of objects. Every meter is represented by a logical device that has a world-wide unique identifier called the logical device name. All the information held by a device is organized into attributes and attribute values, which can also be modified remotely to control device behaviors. Objects that share common characteristics (same attributes and methods) make up an interface class, which are then instantiated into interface objects. The devices offer the access to their data to the communication layers by using the interface objects, which also expose information about the resources available in the logical device in a given context, depending on the access rights. The interface objects are specific to the metering domain, using concepts like register, demand register, profile, clock, and scheduling. The IEC is gaining a stronger presence in the industry, since the standard is approved and maintained by both the DLMS/COSEM community and by the IEC, the latter grouping the DLMS/COSEM specifications under the common heading: Electricity metering Data exchange for meter reading, tariff, and load control. The specification is divided into four specification documents. 1) The blue book describes the COSEM meter object model and the object identification system. 2) The green book describes the architecture and protocols. 3) The yellow book treats all the questions concerning conformance testing. 4) The white book contains the glossary of terms. If a product conforms to DLMS/COSEM yellow book then it automatically implies conformance to IEC set of standards. Data communication is based on a request/respond custom connection-oriented protocol, and data are modeled with XML but exchanged after being translated in a binary protocol. Security is divided into two domains: 1) access security that concerns ensuring that only authorized clients (e.g., user application) can access the data stored in a server (e.g., electricity meter); and 2) transport security that protects the confidentiality and integrity of the communication by encrypting the binary protocol using advanced encryption package (AES)-128. C. Open Smart Grid Protocol The open smart grid protocol (OSGP) [42] is another architectural standard adopted by ETSI. It is intended to support communication requirements between large deployments of smart grid devices and utility companies for billing purposes, to control user s consumption in case of energy shortage, and to provide usage information to the user. OSGP is meant to cover the upper layers for the International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) [43], while the network layer of EN is composed by proxy agents that communicate directly with the smart grid devices, proxy sources that encapsulate the application layer messages and start the communication procedures, and proxy repeaters that relay the messages. The OSGP application layer specializes the EN by introducing the data concentrators and the OSGP smart grid devices. Data concentrators are the only entities that start communications, store collected data, and send control commands to smart grid devices. OSGP smart grid devices collect data, perform actions on the energy grid, and communicate with the proxy agents only. In actual deployments, this standard is more focused on meter reading over power line communications with limited bandwidth than on general smart grids, and the number of loads that can be controlled using this standard is quite limited, still OSGP represents an example of a working standard that attained the status of a de facto standard. A main goal of this standard is to maintain compatibility with smart meters already operational throughout Europe, and OSGP has been quite successful on this respect. In fact, OSGP was initially developed by the Energy Service Network Association (ESNA), and it has been adopted by ETSI after it became a de facto standard for smart meters: around 3 million OSGP smart meters are operative in Europe, and 30 millions use the same power line communication technology of OSGP. The application layer of the protocol is based on the master/ slave communication paradigm. OSGP mainly defines commands for the retrieval of smart meter readings, time settings, display, logs, etc. Apart from this set of data collection commands, OSGP supports a limited number of functions to control the connection and disconnection of loads to the grid. The security of OSGP is based on the authentication mechanisms of EN 14908, still the application layer has got its own security mechanisms for confidentiality and authentication, based on private keys shared between the endpoints of the application layer communication, which are the data concentrator and the OSGP device. VI. DESIGN STANDARDS A. Common Information Model (CIM) The CIM [24] is a design standard developed by the IEC. The IEC effort on smart grids is structured around the strategic group on smart grid (SG3), which is responsible for monitoring new ideas and technologies that have got the potential of being the basis for new standards in the area. The group is responsible for more than 100 standards, and the most relevant ones regarding smart grids are the IEC and IEC standard series, which define the CIM and the representation of physical entities in the software model [24], [44], and the IEC standard series, which completes the CIM by defining the data exchange protocols for energy markets [45]. In power grid systems, the information needs to be shared among different platforms with different types of information systems. The management of these systems is an important aspect especially with the increasing number of users, applications, services, and information sources. The CIM was developed in order to effectively exchange data among different information systems and protocols. The CIM was officially adopted by IEC to represent common components within power systems, which can be used by the energy management system (EMS) and the application programming interfaces (APIs) alike. This standard mainly specifies the interfaces between components, therefore establishing a common language and protocol to allow different software modules, from different vendors, to communicate with each other. Since October 2010

9 ALBANO et al.: CONVERGENCE OF SMART GRID ICT ARCHITECTURES 193 [46], NIST recommends the adoption of the CIM to manage the data exchanged between smart grid devices. CIM is devolved based on the unified modeling language (UML), and it applies object-oriented design approach to smart grid systems. CIM defines the components of a power system as classes, and it makes heavy use of the inheritance mechanism between classes, as well as their relationships and interactions. This gives the base for a common model to describe all situations of a power system, independent of any specific proprietary data standard or format, which facilitates the interoperability among software applications. Three IEC series address the specification of the different parts of the CIM, supporting different tasks within the energy grid. The IEC is the standard series describing EMSs, providing adequate interfaces for exchanging data regarding the configuration of EMSs, including the actors pertaining to the transmission, distribution and generation domains. The IEC targets the distribution system and is intended to support the integration of utility enterprise systems with heterogeneous applications that exchange data during system execution. The main interaction pattern is event driven, and the standard series is intended to be implemented into middleware services that act as message brokers between applications. The IEC is the series of standards targeted to e-business in energy markets, and it comprises communications between market consumers and market operators, and the business operations encompass trading, consumption, market services, and billing. A few more standards from IEC are related with the CIM, even though not being part of it. The IEC (seamless integration reference architecture) discusses electric power system management, by introducing multiple reference architectures and how to compose them, with the goal of describing how different IEC standards can be combined with each other. The IEC standard series consists of 10 parts, and it provides interoperability for the description and the exchange of information for electrical substations [47], it uses transmission control protocol (TCP)/IP as the basic transmission protocol, peer to peer as the communication paradigm, and the manufacturing messaging specification (MMS) standard, defined in IEC , for client server communication. Despite being targeted toward different systems (IEC focuses on electrical substations, while CIM aims at describing EMSs) a current IEC activity is devoted to harmonizing CIM and IEC to create a common approach toward the two different scenarios [48]. IEC 62056, described in Section V-B, deals with the data exchange for meter reading, tariff and load control using DLMS, created to model object-oriented services, and support exchanging messages among distributed devices) and COSEM (defining communication interfaces) specifications. The IEC [49] addresses information security for power system control operations, covering data exchanges related to CIM. The IEC series regards the functional safety of electrical, electronic, and programmable electronic equipment, it is not limited to power grids, and it aims at building a system able to prevent critical failures [50], be it hardware or software failures, incorrect specifications of the system or human errors. As specified above, IEC defines the information to be used in designing and managing smart grids, but it does not specify the message formats for data exchange, and instead it limits itself to providing examples for some use cases, at the level of application layer message formats only. CIM is implemented and completed with a full protocol stack in the SEP (SEP 2.0) of ZigBee, as described in [28] and in the next section, and implemented, e.g., in [51]. B. Smart Energy Profile 2.0 The SEP version 2.0 [28], produced by the joint work of the ZigBee Alliance and the HomePlug Powerline Alliance, is a profile of the ZigBee protocol suite, and as such it depends on the basic ZigBee functionalities defined in the ZigBee cluster library (ZCL) [52] to provide a complete and functional protocol. It has been developed to map directly to the CIM, it adheres to the NIST framework, and it follows a RESTful architecture. This work considers the SEP 2.0 as a design standard, since it goes deep into low level details such as the encoding of the data to be exchanged in the electrical grid. The SEP 2.0 can be considered an application layer protocol, built on top of an internet protocol (IP) stack. The device types supported by the SEP include HAN gateways, called energy service interface (ESI), metering devices, in-home-displays (IHD), programmable communicating thermostat (PCT), load control devices, etc. The RESTful [39] architecture assumes the existence of clients and servers. The server is the device that hosts a resource, and the client is the device that interacts with the representation of the resource by accessing its status, and extending, updating, or deleting representations. Devices may be both clients and servers at the same time. SEP 2.0 also allows publish/subscribe communication, in order to reduce polling. Therefore, clients (subscribers) can subscribe to resources, and the server (notifier) will contact each subscribed client to notify changes whenever a change occurs. In addition to data modeling, encoding and transmission, SEP 2.0 considers device discovery and network formation (via multicast domain name system and DNS-service discovery), security (using transport layer security) for both privacy and integrity of smart grid transactions, support heterogeneity of devices and of physical communication layers (among the others, physical layers can be the ones of , , and Bluetooth). The functionalities provided by SEP 2.0 are divided into function sets: demand response and load control to deliver commands to the devices, metering for remote access to sensed data, pricing to inform users regarding tariffs, messaging to let utility companies send messages to the users premises, billing to compute costs of users current and future activities and to propose incentives to the users in exchange for energy saving implementation, prepayment to support users payment of the services, and finally DERs control to manage renewable integration into the power grid by grouping microproducers into virtual power plants and regulating them via service level agreements. Moreover, since SEP 2.0 is part of the ZigBee protocol suite, it can provide functionalities from ZCL, such as upgrading a

10 194 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, VOL. 11, NO. 1, FEBRUARY 2015 TABLE I COMPARISON BETWEEN THE CHARACTERISTICS OF REPRESENTATIVE STANDARDS Fig. 4. Case study: ENCOURAGE. device s configuration and firmware, and advertising its physical location. VII. COMPARISON AND CASE STUDY Table I summarizes the details related to the standards we presented as representatives of the various categories. The table testifies the large diversity that exists between the approaches, and that it is hard to compare standards belonging to different parts of the taxonomy. The rest of this section is devoted to reporting a case study to exemplify how to apply the analysis made in Sections II VI. The Embedded intelligent COntrols for buildings with Renewable generation and storage (ENCOURAGE) project [51], whose structure is reported in Fig. 4, aims at building a smart grid whose deployment view features a number of HANs, each connected to the ENCOURAGE platform via custom protocols that are translated through gateways to the protocol used in the CIM-based middleware. A database keeps historical data on everything happening in the grid, and the supervisory control module takes energy saving decisions to be reported back to and implemented by the HANs, based on the data collected from the HANs and from external information services (not reported in Fig. 4). The SGAM meta-architecture can be used to understand the ENCOURAGE approach, and for describing it (layered over distribution to customer domains, station to operation zones, information and communication layers [25]) to third parties that are working in similar areas for interoperability with their systems. On the architectural level, ENCOURAGE can be identified as a subset of DLMS/COSEM, since both are focused on data exchange for meter reading and load control. ENCOURAGE internal protocol, CIM, is converging to a one-to-one mapping with the XML of DLMS/COSEM (see Section VII). Thus, a description in terms of DLMS/COSEM can be used to both corroborate ENCOURAGE architecture, and to promote its architectural compatibility with other approaches based on DLMS/COSEM. Finally, on the level of the design standard, the core of EN- COURAGE uses CIM and externally it uses SEP and energy automation and control system (EACS), the latter being a custom protocol that implements a subset of SEP functionalities. The application of design standards, and in particular of SEP, ensures protocol and semantic compatibility of the ENCOURAGE platform with other projects adopting similar techniques. VIII. DISCUSSION AND CONCLUSION In the world of the future smart grid, one of the main challenges will be the interoperability between systems of different vendors. Overcoming this challenge will lead to several correlated benefits, from the creation of new markets and reduction of costs, to the broader dissemination of the technology and its stronger impact on the general public. As put forward in the introduction, the current smart grid industry features a number of different incompatible standards, some matured from domotics, others created from scratch by ICT companies, or by electrical utilities. The result is the lack of coordination of the smart grid subsystems deployed in the users HAN or in between different actors, very far away from the vision of a true smart environment.

11 ALBANO et al.: CONVERGENCE OF SMART GRID ICT ARCHITECTURES 195 Fig. 5. Relationships between current approaches. The meta-architectures discussed in this paper were created with the aim of building a harmonization path for the interoperation of protocols and architectures. The other approaches proposed also to converge when functionalities are overlapping, and interconnect when targeting different use cases and/or scenarios. Fig. 5 provides a graphical representation of the relations between the efforts discussed in this paper; these relations are the focus of the remainder of this section. The NIST meta-architecture was created from the need for common standards for smart grids, thus building upon many of them [7]. NIST recommends CIM as implementation for an architecture aimed at EMSs, and IEC for the electrical substations, as per Section 4.3 of [7]. Moreover, the same section considers DLMS/COSEM as an architecture that must be integrated by means of adapters and protocol translators. Since ZigBee SEP is an implementation of CIM [28], NIST is implicitly implemented by this protocol. Finally, SGAM was born as a European extension of NIST vision to include explicitly DERs, by specializing the smart grids toward an architecture where DERs are present in the distribution domain (see Section of [25]). Apart from being extended from the NIST model, the SGAM has a strong connection with the other European (ETSI, CEN, and CENELEC) initiatives, since it is itself born from a European mandate (M/490). Regarding the IEC efforts, SGAM assumes in Annex E of [25] that its meta-architecture will be able to leverage on NIST s work on standardization between different IEC approaches such as CIM, IEC 61850, and DLMS/COSEM (IEC 62056), thus it will be able to seamless integrate its data model at the information plane between the domains and zones. Even though it is already a full-fledged architecture, ETSI s M2M aims at using an underlying DLMS/COSEM protocol [53]. Besides that, under pressure from M/441, OSGP is evaluating a one-to-one mapping into DLMS/COSEM, with the double purpose of interoperability with IEC 62056, and of integration into the European M2M architecture [53]. Even though the specification of DLMS/COSEM is more focused on smart metering than on smart grids in general, it still overlaps with the CIM. With the purpose of converging toward a better interoperability, the relation between the CIM and the DLMS/COSEM was described by means of CIM message profiles contained in IEC At the end of 2012, the different IEC working groups that maintain the two standards have been cooperating in defining document [54] that provides a mechanism to translate the query messages used within CIM to DLMS/COSEM, and vice versa, leaving the translation of other message kinds to future work. Finally, as already reported, ZigBee SEP is in itself an alternative implementation of CIM [28]. The resulting picture is that the different directions taken by standardization activities and architectures are converging toward a common vision where overlapping architectures interact by means of adapters, and standards covering different use cases are made compatible with the means of complementing each other. In particular, the above discussion highlights the creation of a convergence bus, centered on the design standard IEC CIM and its implementation ZigBee SEP, which offer the same functionalities, and comprise all the capabilities of the remaining standards. This highlights that standards in the last mile of the smart grid are converging to common solutions to improve interoperability and integration of systems at different levels of abstraction. 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IEC/TS : Mapping Between the Common Information Model CIM (IEC ) and DLMS/COSEM (IEC 62056) Data Models and Message Profiles, accessed on Dec Michele Albano received the B.Sc. degree in physics in 2003, and the B.Sc., M.Sc., and Ph.D. degrees in computer science in 2004, 2006, and 2010, respectively, from the University of Pisa, Pisa, Italy. He was a Visiting Researcher with the Universidad de Malaga, Malaga, Spain, in 2007; was with Stony Brook University, New York, NY, USA, in 2009; and before being a Researcher, he worked as Software Engineer and Wireless Technology Specialist in private companies in During , he was involved in European Union (EU) funded projects secure middleware for embedded peer to peer systems (SMEPP) and enabling linux for the grid (XtreemOs), and in the period , he held a Postdoctoral Researcher position with the Instituto de Telecomunicações, Lisbon, Portugal, where he worked on PEACE, C2POWER, GREEN-T, and ROMEO, acting as Technical Manager for GREEN-T, and as Work Package Leader for ROMEO. Since 2012, he has been a Research Scientist with the Research Centre in Real-Time and Embedded Computing Systems of Polytechnic of Porto, Porto, Portugal, working on communication for smart grids and on middleware for embedded systems. He has coauthored more than 60 papers published in international journals and conference proceedings. His research interests include the areas of smart grids, wireless sensor networks, and peer-to-peer networks. Dr. Albano is serving on the editorial boards of the Transactions on Emerging Telecommunication Technologies and the International Journal on Social Technologies.

13 ALBANO et al.: CONVERGENCE OF SMART GRID ICT ARCHITECTURES 197 Luis Lino Ferreira received the Ph.D. degree in electrical and computer engineering from the University of Porto, Porto, Portugal, in He is the Sub-Director of the Master on Informatics with the Department of Computer Engineering, School of Engineering, Polytechnic Institute of Porto, Porto, where he is also Adjunct Professor. He is a Research Associate with CISTER (Research Centre in Real-Time and Embedded Computing Systems), where he is currently CISTER Coordinator for the Arrowhead project. While in CISTER, he also participated in several national and international projects such as the Embedded intelligent COntrols for buildings with Renewable generation and storage (ENCOURAGE) project, parallel software framework for time-critical many-core systems (P-SOCRATES), QoS-Aware cooperative embedded systems (CooperatES), and high performance wireless fieldbus in industrial multimedia-related environment (R-Fieldbus). He has authored more than 40 papers in international venues and journals in the area of real-time embedded systems. He was Program Chair at simpósio de informática (INFORUM) 2014, and Special Session Organizer at the IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) 2014 Special Session on Flexible and Interoperable Automation Systems. He has also participated in several program committees and has been a reviewer of most conferences and journals in the area. His research interests include the area of real time and embedded systems, particularly in middlewares for distributed systems, holistic analysis, and sensor networks. Luís Miguel Pinho (M 03) received the Ph.D. degree in electrical and computer engineering from the University of Porto, Porto, Portugal, in He is a Coordinator Professor with the Department of Computer Engineering, School of Engineering, Polytechnic Institute of Porto, Porto. He is a Vice-Director and Research Associate at CISTER (Research Centre in Real-Time and Embedded Computing Systems), with more than 15 years of experience in research in the area of real time and embedded systems, particularly in concurrent programming models, languages, operating systems, and embedded middleware. He has participated in more than 15 R&D projects, being Coordinator of the FP7 R&D European Project Parallel Software Framework for Time-Critical Many-core Systems (P-SOCRATES); Coordinator of the National QoS-Aware cooperative embedded systems (CooperatES) and Reflect projects; CISTER Coordinator of the Artemis the Embedded intelligent COntrols for buildings with Renewable generation and storage (ENCOURAGE), ITEA 2 CarCoDe, FP5 REMPLI European projects, and several national projects; and Work Package Leader on several European and national projects. He has authored more than 100 papers in international venues and journals in the area. He was a Senior Researcher of the ArtistDesign Network of Excellence (NoE) and is a Member of the HiPEAC NoE. Dr. Pinho is the Editor-in-Chief of Ada User. He was Keynote Speaker at RTCSA 2010, Conference Chair and Program Co-Chair of Ada-Europe 2006, Program Co-Chair of Ada-Europe 2012, and General Co-Chair of ARCS 2015.