1154 IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 48, NO. 4 JULY/AUGUST 2012 A Comparison of Smart Grid Technologies and Progresses in Europe and the U s. Marcelo Godoy Simã es, Senior Member, IEEE, Robin Roche, Student Member , IEEE, Elias Kyriakides, Senior Member, IEEE, Sid Suryanarayanan, Senior Member, IEEE, Benjamin Blunier, Member, IEEE, Kerry D. Mcbee, Phuong H . Nguyen, Member, IEEE, Paulo F. Ribeiro, Fellow, IEEE, and Abdellatif Miraoui, Senior Member, IEEE Abstract†This paper discusses historical and technical events in the U s . and Europe over the last few years that are aimed at modernizing the electric power grid. The U s. federal government has ratified the â€oesmart grid initiative†as the official policy for modernizing the electricity grid including unprecedented provisions for timely information and control options to consumers and deployment of â€oesmart†technologies. European countries are unified in researching and developing related technologies through various structures supported by the European union. This paper presents the development of smart grids and an analysis of the methodologies, milestones, and expected evolutions of grid technologies that will transform society in the near future. Index Terms†Control, distributed generation (DG), power electronics, power systems, smart grid, smart metering, storage. I. INTRODUCTION THE PRESENT-DAY electric grid was built about a centuryago in most industrialized countries and has been growing in size and capacity ever since. Transmission lines connect large centralized power sources to the grid and have been updated technologically with automation and human monitoring over the last few decades. The electrification of our society has empowered countless advances in other fields such that the U s. National Academy of Engineering ranked it as the greatest engineering achievement of the last century 1. However, this transformation was mostly in the transmission realm and not Manuscript received November 25, 2011; accepted January 23, 2012. Date of publication May 16, 2012; date of current version July 13, 2012. Paper 2011-ESC-567, presented at the 2011 IEEE Energy Conversion Congress and Exposition, Phoenix, AZ, September 17†22, and approved for publication in the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the Energy Systems Committee of the IEEE Industry Applications Society. M. G. Simã es and K. D. Mcbee are with the Colorado School Of mines, Golden, CO 80401 USA (e-mail: msimoes@mines. edu; kerry. d. mcbee@xcelenergy. com). R. Roche is with IRTES-SET, Universitã de Technologie de Belfort†Montbã liard, 90010 Belfort, France (e-mail: robin. roche@utbm. fr). E. Kyriakides is with the University of Cyprus, 1678 Nicosia, Cyprus (e-mail: elias@ucy. ac. cy. S. Suryanarayanan is with Colorado State university, Fort Collins, CO 80523 USA (e-mail: ssuryana@mail. colostate. edu). B. Blunier, deceased, was with IRTES-SET, Universitã de Technologie de Belfort†Montbã liard, 90010 Belfort, France. P. H. Nguyen and P. F. Ribeiro are with the Technische Universiteit Eindhoven, 5600 MB Eindhoven, The netherlands (e-mail: P. Nguyen. Hong@tue. nl; pfribeiro@ieee. org). A. Miraoui is with IRTES-SET, Universitã de Technologie de Belfort†Montbã liard, 90010 Belfort, France, and also with Cadi Ayyad University, Marrakesh 40000, Morocco (e-mail: abdellatif. miraoui@utbm. fr). Digital Object Identifier 10.1109/TIA. 2012.2199730 in the distribution milieu since the latter has traditionally been considered as user end points of service, where power was delivered to traditional loads. The last two decades saw a steady growth of distributed generation (DG), with plans for higher penetration of renewable energy sources, and the policies on electricity distribution have been supporting needs for a â€oesmart grid†for many reasons that will be discussed in this paper. Centralized power plants have enormous economic constraints and benefits, and utilities have been trying to use their assets more efficiently. As an example typically, 20%of the U s. generation capacity is used only for 5%of a year to meet peak demand and is based on coal and gas power plants, which cause environmental concerns and greenhouse gas (GHG) emissions. A paradigm shift in distribution engineering is viewed as the next frontier of advancement in electric power systems, and the smart grid is expected to introduce unprecedented changes in the distribution systems worldwide. Both the U s. and European economies have taken the lead in establishing some early concepts and policies for realizing the smart grid. In this paper a comparison of the various smart grid technologies and the paths of progress in the U s. and in Europe is presented. II. EVOLUTION OF THE SMART GRID IN THE U s. AND EUROPE Conceptualization of techniques to improve the intelligent interaction of distributed assets for smart grids emerged in the 1980s as a call to modernize the grid, allowing deeper pene-tration of alternative and renewable energy sources. The first references to the term smart grid were provided around 2004 by Amin and Wollenberg 2, 3. While some common characteristics of a smart grid exist, Europe and the U s. have been following different paths to make their respective grids smarter. A. Trajectory in the U s. The electric grid in the U s. is composed of approximately 15 000 generators operating in 10 000 power plants, accounting for approximately 3. 95 million MWH (as of 2009), with approximately 160 000 miles of high-voltage transmission lines (at voltages typically above 280 kv) 4, 5. The electric grid in the U s. evolved from small-rated centralized power stations, such as the historical Pearl street Station in Manhattan, NY (such power stations supplied dc electricity to relatively smaller rated loads in the late 19th century), to the interconnected ac 0093-9994/$31. 00  2012 IEEE SIMà ES et al.:COMPARISON OF SMART GRID TECHNOLOGIES AND PROGRESSES IN EUROPE AND THE U s. 1155 Fig. 1. Timeline of major events in the U s. electric grid. system of present day that crisscrosses North america 6. The present-day massive North american grid consists of three large asynchronous interconnections, namely, the Western Electricity Coordinating Council system, the Eastern Interconnec-tion, and the Electric Reliability Council of Texas, and has been referred to as the â€oemost complex man-made machine†7. The evolution of the smart grid in the U s. may be traced to several innovations in the transmission grid, such as the wide-area measurement and fast controls, and the installation of power system stabilizers, phase shifting transformers, flexible ac transmission system devices, and phasor measurement units (PMUS). Additionally, the advent of advanced control room visualization has heralded the template for the smart grid. Public awareness and concomitant push for more renewable energy sources in the grid have provided also some impetus to the integration of newer technologies in the grid. However, the modernization of the electricity grid has been restricted largely to the transmission systems and did not penetrate the distribution system level as much. This may be attributed to factors such as higher variability in system scenarios at the latter level and a relatively low economy of scale when compared to the transmission systems. Several legislative mandates have provided various opportunities for the modernization of the electric grid in the U s. Fig. 1 shows a timeline of some events related to the electricity grid in the U s. that have served as harbingers to important changes via mandates and legislations. B. Trajectory in Europe The unification of the European grid was achieved in parallel to the economical unification of European countries. This process has been slow, due to the high cost of building new infrastructures and historical events such as the two world wars and the political separation of Eastern and Western europe for more than four decades. The idea of a pan-European grid was discussed first by the League of Nations in the 1920s. This became a reality only in 1951 with the creation of the Union for the Coordination of Production and Transmission of Electricity which eventually became the Union for the Coordination of Transmission of Electricity (UCTE), which was aimed at interconnecting the grids of France, Germany, and Switzerland. Similar associa-tions were created in other regions of Europe, such as NORDEL or SUDEL. However, during the Cold war, a real intercon-nection of the western and eastern parts of Europe was nearly impossible, and European countries reorganized such interests only after 1990, with the fall of the Iron curtain. In 2008, the regional associations ETSO, ATSOI/UKTSOA (Ireland, Great britain), NORDEL (Finland, Sweden, Norway, and Eastern Denmark), UCTE (23 continental European countries), and BALTSO (Baltic countries) merged into the European Network of Transmission System Operators for Electricity (ENTSO-E), which now coordinates 41 Transmission System Operators (TSOS) from 34 countries 8. Smart grid policies in Europe are relatively new, while at the same time, the European grid is becoming more interconnected and sees that investments decrease. However, the sense of ownership and contribution of each individual country to the whole grid is different from how the U s. directs initiatives through its Department of energy. Some recent European union (EU) initiatives are as follows. 1) The European energy program for recovery (2009), which has some similarities to the U s. Stimulus Fund. This program was aimed at speeding up and securing investments for projects in the energy sector. 2) An overall energy-efficiency action plan (2007†2012) establishes a firm objective of 20%improvement. 3) The European energy infrastructure package identifies smart grids as the key infrastructure for energy modernization in Europe. 4) The Competitiveness and Innovation Framework Program proposes an intelligent energy for Europe program. 5) The European Energy Research Alliance aims at accelerating the development of new energy technologies by maximizing funding sources, facilities, and complemen-tarities among institutes in participating countries. III. GOVERNING BODIES IN SMART GRID DEVELOPMENT The U s. Smart Grid Initiative is the official policy of grid modernization in the U s as formalized by the 2007 Energy Independence and Security Act (EISA07 ) 9. Under the purview of this legislative mandate the U s. smart grid is characterized by the following: 1) increased digital information and controls; 2) dynamic optimization of grid operations, including cyber security; 3) deployment of distributed resources, including renewable resources; 4) incorporation of demand-side resources and demand response; 5) deployment of â€oesmart†technologies and integration of â€oesmart†appliances and consumer devices; 6) deployment of storage and peak-shaving technology, including plug-in hybrid electric vehicle (PHEV; 7) provision of timely information and control options to consumers; 8) standard development for communication and interoper-ability of equipment; 1156 IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 48, NO. 4 JULY/AUGUST 2012 Fig. 2. Future electric smart grid. 9) identification and lowering of unreasonable barriers to adopt smart grid technology, practices, and services 9. An illustration of an implementation of the smart grid is shown in Fig. 2. The U s. National Institute of Standards and Technology (NIST) provides a conceptual model that defines seven important domains: bulk generation, transmission, distribution, customers, service providers, operations, and markets 10. In the EU, the smart grid strategy is motivated by concepts of innovation with regard to social and environmental reforms for an interactive economy. The European energy policy relies on 11 the following: 1) security of supply; 2) sustainability; and 3) market efficiency. In addition, six goals have been set for the EU energy strategy: 1) to achieve the highest levels of safety and security; 2) to achieve an energy-efficient Europe by improving buildings, transportation, and distribution grids; 3) to extend Europe†s leadership in energy technology and innovation; 4) to empower consumers; 5) to build a European integrated energy market; and 6) to strengthen the external dimension of the EU energy market. The European Strategic Energy Technology Plan includes eight European Industrial Initiatives (EIIS) in the field of energy. The EII on electrical grids is called the European Electricity Grid Initiative and has estimated a budget to 2 billion over a period of ten years with guidelines and activities for research and development (R&d) and a program with 20 large-scale demonstration projects 12. The EU established the Third Energy Package in 2007 with objectives and regulations for the implementation of smart grids stating that all European citizens have a range of energy-related rights, such as consumer choice and fair prices. Dispositions are taken also to favor international energy (electricity and gas) trade, collaboration and investment, separation of generation and supply from transmission networks, decentralized generation and energy efficiency, and smart meters and effective national regulators. The European Technology Platforms began to operate in 2005 13 in formulating and promoting a vision for the development of smart grids for year 2020 in compliance with the EU policy. â€oesmart Grids Task Force†was created in 2009 and is composed of European commission officials, experts from the industry, policy makers, and academia 14. The first projects related to smart grids were grouped within the Integration of Renewable Energy Sources and Distributed Generation into the European Electricity Grid cluster. Over 60 projects in the fields of smart grids have been supported by the Sixth Framework Program and correspond to an investment of about 190 million. The Seventh Framework Program, the current program, will run until 2013 and has a total budget of 51 billion, with 7%of it dedicated to energy-related projects 15. Currently, the related EU associations for promoting smart grid projects are as follows: 1) the European Regulators Group for Electricity and Gas and the Council of European Energy Regulators, which allow national regulators to cooperate; 2) the new Agency for the Cooperation of Energy Regulators, a complement to the two previous organizations and ENTSO-E; 3) the European Distribution System Operators Association for Smart Grids; 4) the Union of the Electricity Industry (EURELECTRIC), which represents the common interests of the electricity industry at the European level. IV. ENABLING TECHNOLOGIES Several technologies have to mature in order to make the smart grid a reality 16,17. A. DG DG (also referred to as embedded generation or dispersed generation) refers to small rating electricity sources that are decentralized typically and located close to end-user locations on the distribution side of the electric grid. These may include conventional as well as renewable energy sources. The interconnection of DG to the grid provides a variety of advantages including on-demand power quality of supply, enhanced reliability, deferrals in transmission investment, and avenues for meeting renewable mandates in the face of growing dis-investments in transmission assets†all of which cater to the smart grid philosophy. However, the interconnection of DG is a challenge due to the safety, control, and protection issues associated with bidirectional flows of electricity. In the U s.,the Energy Policy Act of 2005, enacted by the 109th Congress recognized the IEEE 1547 Standard as the national technical standard for interconnection of DG to the electric grid 18. Further information about DG is available in 19. B. Energy Storage Electricity is a highly perishable commodity that must be consumed within a very short span of production and cannot be stored easily, particularly in high quantities. Alternatively, it may be converted into other forms such as mechanical or electrochemical energy. Storage technologies enable these processes and are desired among the features for the smart grid. Multiple existing technologies are compared in Fig. 3. Storage, which can be distributed in the grid, provides the following advantages: 1) makes the grid more efficient 20; 2) enables load leveling and peak shaving, while it reduces de-pendence on spinning reserve; 3) improves grid reliability and SIMà ES et al.:COMPARISON OF SMART GRID TECHNOLOGIES AND PROGRESSES IN EUROPE AND THE U s. 1157 Fig. 3. Comparison of discharge duration versus rated power for some grid energy storage technologies. power quality; 4) provides ancillary services, supplying reactive power for voltage regulation; and 5) supports transmission-and-distribution (T&d) investment deferral. Energy storage with power-electronics-interfaced units can create virtual rotational inertia, the so-called virtual synchronous generators, which can reduce the rate of change of frequency and frequency deviations 21. C. Power Electronics Power electronics is fundamental in the development of smart grids because a deeper penetration of renewable and alternative energy sources requires sophisticated power converter systems. Typically, a power converter is an interface between the smart grid and local power sources 22. Solar photovoltaic and wind energy systems play a significant role as alternative sources for integration in smart grids and are increasingly being installed in residential and commercial locations (typically with a power range of a few kilowatts) as well at high rating in the high-voltage transmission grid. The intermittent nature of these sources affects the output characteristics of generator and converter sets. A power electronics converter is deemed necessary to smooth the output to the desired characteristics and to allow energy storage during surplus of input power and compensation in case of lack of input power. The following characteristics are important for power electronics systems for smart grids. 1) High efficiency: Only a negligible part of the power should be dissipated during conversion stages. 2) Optimal energy transfer: All renewable energy sources are constrained energy and, as such, need algorithms to achieve the maximum power point which must be considered in the design of the power electronics interface. 3) Bidirectional power flow: Power converters have to be able to supply the local load and/or the grid. 4) High reliability: Continuity of service is a major issue when delivering energy. 5) Synchronization capabilities: All power sources connected to the grid have to be synchronized fully, thus ensuring high efficiency and eliminating failures; therefore, standards such as IEEE 1547 should be incorporated in power electronics interfaces 23.6) Electromagnetic-interference filtering: The quality of the energy injected into the grid must adhere to apt electromagnetic-compatibility standards. 7) Smart metering: The interface between the local source/load and the grid must be capable of tracking the power consumed by the load or injected into the grid. 8) Real-time information must be passed to an automatic billing system capable of taking into account parameters such as energy bought/sold in real time, informing end users of all required pricing parameters. 9) Communications: The intelligent functioning of the smart grid depends on the capability to support a communication layer in tandem with an energy delivery layer in the grid. 10) Fault tolerance/self-healing: A key issue is a built-in ability to minimize the propagation of failures and resilience against such local failures. This capability should be incorporated with monitoring, communication, and reconfiguration features of power electronics systems. Additionally, power electronics interfaces must be configured to avoid nuisance trips. D. Control, Automation, and Monitoring A smart grid is a highly complex nonlinear dynamic network of distributed-energy assets with bidirectional flow of power and information that presents many theoretical and practical challenges. Monitoring and control are key issues that need to be addressed to make it more intelligent and equip it with self-healing, self-organizing, and self-configuring capabilities. This requires much more sophisticated control, sensing, and computer-oriented monitoring than in the contemporary grid, where grid operations are rather reactive, with a number of critical tasks performed by human operators. Therefore, some modern control techniques have been claimed to be the best fit for smart grids, for example, agent-oriented programming and implementing computational intelligence into distributed-system operation 24; however, most of these are yet to transcend the research domain into large-scale deployment. A combination of agent-based control techniques and power electronics possess the potential to create an intelligent and flexible interface between consumers, storage, DGS, and the network, as well as among network areas. Fig. 4 shows different power electronics layers to integrate a cluster of prosumers (an entity in the future grid capable of both producing and consuming electric power) into the grid. The two-way communication ability of smart meters allows the transmission of delivered and generated energy data along with actionable commands to customers. With technologies such as WIFI Zigbee, and home area network (HAN) communication systems, smart meters can now act as interfaces for energy management entities, customers, and utilities to control a number of appliances within a residential home based on price signals 25. Power quality analyzing capabilities of smart meters may improve the ability to identify system and customer voltage 1158 IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 48, NO. 4 JULY/AUGUST 2012 Fig. 4. Intelligence-based control structure for power electronics in smart grids. deficiencies, harmonic distortions, and onset of equipment failure. Daily energy usage and generation profiles may be recorded for forecasting-relevant system parameters. Threshold voltage events can trigger communication with utilities for providing alerts to disturbances prior to customer equipment failure or discomfort. These functionalities may also improve the ability of utilities to locate the source of system events, which is a difficult and complex task on the existing electric distribution system, but may introduce the risk of increased susceptibility to cyber intrusions by malicious agents 26. Several utilities in the U s. and Europe have seen already improved power quality due to the installation of smart meters 27. E. DSM Demand-side management (DSM) refers to the ability to change energy consumption patterns and characteristics via structured programs. Historically, most DSM programs aimed at achieving targets in energy efficiency while some conservation programs aimed at deferring investments in new assets (including generating facilities, power purchases, and T&d capacity additions). However, with the advent of the smart grid, DSM may provide paradigm shifts in the normal operation of the electricity market or from government-mandated energy-efficiency standards. In the last few years, there has been increased an interest in dynamic pricing, i e.,, a time-varying pricing at the end-user level, different from the state of the art of tariffs. Dynamic pricing, which is available in the U s. bulk power (transmission) markets since mid-1990s following deregulation of the industry, has enabled economic efficiency, fostered investments in technological innovations, and, for the most part, removed the ills of market power and monopoly 28. Such a differentiated or tiered rate of electricity in the distribution system is viewed as an enabler for the smart grid. When enabled with such information on dynamic pricing of electricity, customers and utilities will need to interact via DSM structures aimed at increased energy efficiency, lowered cost of engaging inefficient and costly generators at peak periods, coordinated charging of PHEVS, or other similar objectives. Several dynamic pricing models have been proposed in order to better reflect the actual cost of producing energy on the specific day and time and provide incentives to customers to become more active in controlling their electricity consumption 29, 30. The following time-varying pricing methodologies are viewed as possible enablers of DSM. 1) Time-of-use (TOU) electricity rates have been shown to be effective in promoting customer participation in demand management 30. TOU rates use predetermined time intervals during which electricity use is recorded. Each time interval has fixed a price that is proportional to the electricity availability during that same time interval. 2) Real-time pricing is a methodology whereby the customer is informed a time period ahead of the electricity price so as to make rational decisions regarding the consumption of electric energy. The retail price of electricity in this pricing methodology floats based on the actual cost of electricity. If the time period is 1 h then real-time pricing is known as hour-ahead pricing. 3) Critical peak pricing is used to â€oeforce†customers to avoid consuming electric energy during specific peak periods. These periods are defined well by the utility, and the cost of electricity during these periods is increased significantly. 4) The peak time rebate has a similar concept as the critical peak pricing. Instead of a penalty, the conscious customer receives a reward for reducing their electricity consumption below a certain baseline. If the customer consumes more than the baseline, there is no penalty imposed. Data management is critical for the widespread operation of the smart grid in the near future because vast raw data will have to be processed, aggregated, validated, and transmitted for further processing and analysis. F. Distribution Automation and Protection Smart grid technology supports a wide range of applications in power systems, such as protection and automation of the distribution system and security. It is possible to design self-healing protection systems using the capabilities of the advanced distribution automation 32. The protection of the power system is a critical necessity in order to achieve continuity, reliability, and security of supply. Protection deals with the detection and clearance of abnormal system conditions such as faults and overloads. High penetrations of DG can compromise existing protection schemes which are based on single sources supplying unidirectional power through radial distributed lines. In the smart grid, where bidirectional flow of electricity through partially networked systems in the distribution milieu will be prevalent, protection mechanisms are adaptive and incorporate intelligent automated functions. Recent activities in protection engineering focus on developing microprocessor-based devices called intelligent electronic devices. Such devices may be smart distribution switches or integrated solutions for substations. The International Electrotechnical Commission (IEC) 61850 Standard (Communication Networks and Systems in Substations) provides authoritative information relevant to the design of substation automation 33. SIMà ES et al.:COMPARISON OF SMART GRID TECHNOLOGIES AND PROGRESSES IN EUROPE AND THE U s. 1159 Fig. 5. Characteristics of some wireless communication technologies: Band-width versus transmission range. G. Communication systems Self-healing systems have been sought to be incorporated into power systems, particularly as the complexity and inter-actions of several market players significantly increase the risk for large-scale failures. Reconfiguring the system in islanded mode may require hitherto unknown rate and amount of data exchange, two-way communication links, and advanced central computing facilities. Decentralized intelligent control could enable islands to accommodate their native load and generation in a more reliable and efficient manner. Local controllers may ensure that each island is operating within the security limits safeguarding the electricity supply to its customers 34. A self-healing system should be based on a wide-area monitoring network that incorporates a variety of sensors, such as PMUS that obtain phasor measurements by synchronizing with each other through the global positioning service 34,35. The measurements and signals obtained from sensors may be used either by local (distributed) or centralized controllers to enable the self-healing of the system under disturbance or fault conditions. These measurements and signals may be submitted for processing to a single controller, despite the fact that they may be originating from different proprietary networks 36. IEEE Standard 1451.4 requires analog sensors to have a transducer electronic data sheet to provide calibration information to the data acquisition system 37,38. Fig. 5 shows how several communication technologies can be applied for such data, according to their characteristics. The ranges of operation and bandwidth of these technologies vary significantly; some of them may be chosen for HAN, while others may be used for longer distances such as from houses to concentrators or between substations 27. Two-way-communication-enabled smart appliances, smart meters for control of sources, loads, and storage must be implemented in a platform that allows both digital information and electric energy to flow through a two-way smart infrastructure. The requirements for these communication infrastructures are reliability and resilience, bandwidth, interoperability, and costs. Several communication protocols and media are currently under various stages of R&d for implementation in smart grids. Examples include broadband over power line and power line communications which use existing power lines to transmit information; Ethernet, digital subscriber line, and optic fiber, which are already in use for the Internet; Zigbee and WIFI, which are used already for HAN applications; Wimax, a â€oesuper WIFI, †with a much higher range; and 3g, LTE/4g, and other mobile telephone communication protocols. V. COMPARATIVE METRICS FOR THE U s. VERSUS EUROPE Making the grid smarter requires considering all aspects of smart grids as part of the decision-making process. This section compares the practices in the U s. and the EU on several topics for the development of smart grid technologies. A. Legislation in the U s. The legislation that led to the present-day U s. Smart Grid Initiative might be traced back to the 1970s, when deregulation was introduced initially as a direct result of the Arabic oil embargo that escalated a nationwide energy crisis. In 1977 the Federal Power Commission was restructured to form the Federal Energy Regulatory Commission (FERC), with the objective of regulating energy transactions and transmission across different states in the Union. The National Energy Act of 1978 was passed to conserve energy and increase efficiency by judicious use of resources and amenities by utilities and introduced the Public utilities Regulatory Policies Act, which advocated the need for small power productions, for cogen-eration and for renewable energy sources that could compete as independent power producers in the electricity market with other utilities. The 102nd Congress of the United states passed the Energy Policy Act of 1992 which included provisions for alternative fuels, electric motor vehicles, energy-efficiency improvement, and energy-conservation techniques 39. FERC mandated open transmission access, with the mandated open-access transmission tariff requiring that all investor-owned util-ities make separate functionalities of generation, distribution, transmission, and marketing services. It also mandated the creation of independent system operators, eventually making possible the creation of an open-access same-time information system†a Web-based secure database of transmission-system-related information. These orders were the template for the evolution of the deregulated electricity market structure that is currently in place in the U s. Following the Northeast blackout of August 2003 in the U s. the 109th U s. Congress passed the 2005 Energy Policy Act, with provisions for tax incentives and subsidies for renewable-energy integration and energy-efficiency technologies. Fig. 6 shows a timeline of some key legislative events in the U s. history vis-Ã-vis the smart grid. The 110th U s. Congress is credited with passing the EISA07, which explicitly characterized the smart grid through the U s. Smart Grid Initiative in Title XIII. The other highlights of this act included electrifying the transportation fleet, reductions in fossil fuel usage in certain sectors, and carbon sequestration. This was followed by the American Recovery and Reinvestment Act of 2009 (ARRA09 passed by the 111th U s. Congress, which included provisions 1160 IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 48, NO. 4 JULY/AUGUST 2012 Fig. 6. Key U s. legislative events vis-Ã-vis the smart grid. TABLE I SELECTED U s. SMART GRID PROJECTS (FROM 40) for energy infrastructure improvements via the implementation of the smart grid. Table I lists some details of selected smart grid projects in the U s. supported under ARRA09 40. The Smart Grid Clearing house is a Web resource that lists all ARRA09-funded smart grid projects geographically as well as according to their technical focus. B. Legislation in Europe Energy needs are responsible for 80%of all European GHG emissions 13. Therefore climate change legislation and energy policy have been linked intimately with a strong impact on investment decisions from private companies. As a consequence of the Kyoto protocol, European leaders made a unilateral commitment to reach three legally binding objectives by 2020, known as the â€oe20†20†20†targets 41:1) reach a 20%share of energy consumption coming from renewable sources; 2) achieve a reduction of 20%of primary energy use through energy-efficiency measures; 3) reduce GHG emissions by at least 20%below 1990 levels. With the Third Energy Package, additional requirements were introduced, such as the encouragement to roll out 80%smart meters in Europe by 2020 42. GHG target reductions may be increased to 30 %if other major emitting countries set themselves ambitious objectives. A proposal to cut emissions by 80%to 95%by 2050 has also been suggested. Table II shows a list of selected smart grid projects in Europe supported by EU funding in the last few years 43. TABLE II SELECTED EU SMART GRID PROJECTS (FROM 43) C. Barriers Several barriers may slow down the development of smart grids on both continents as depicted next. A first issue is related to financing. During 2009, stimulus plans were used for funding dozens of projects. However, as more and more governments are taking austerity measures, this funding is expected to decrease, or not be renewed, and will need to be replaced either or supplemented by private funding sources. This raises the question of the real interests of the many stakeholders in the smart grid. The cost to modernize distribution networks is high, and utilities may consider if the benefits will overweigh the costs. Moreover, the smart grid requires utilities to make significant changes to their present business models (e g. reducing demand is contradictory with present-day models. Regulators are expected to balance costs in order to ensure that each player finds an acceptable ratio between the costs and returns on investments. They should also enable dynamic electricity pricing, a requirement for demand response actions and DSM programs to achieve success. The acceptance of consumers regarding smart metering and changes in general is a challenge. In some U s. states, consumers raised concerns to the installation of smart meters, regarding an increase of the electricity bill, or the privacy of information transmitted to the utility. Technology maturity and availability present another challenge, particularly regarding distributed-energy-resource integration and control. The operating security is also critical as shown by the Stuxnet case 44. The establishment of standards for smart grids is also a crucial step. By allowing components to interact with each other, and ultimately to reduce costs, standards will enable true interoperability between assets produced by various companies. The U s. NIST, IEEE, IEC, and other organizations have been working on several standardization activities. VI. PATH FORWARD The EU and the U s. have different approaches in fostering smart grid technology. Europe has been influenced by concerns derived from the diversity and evolution of power grids across European countries while the U s. needs to increase security and to respond to the predicted growth in demand for a long-term vision. It is expected that such technologies will have widespread growth subject to economies of scale. Distribution networks will dramatically change in the near future, and energy storage is expected to become increasingly available, even at the distribution level, in order to SIMà ES et al.:COMPARISON OF SMART GRID TECHNOLOGIES AND PROGRESSES IN EUROPE AND THE U s. 1161 compensate the intermittent nature of renewable energy sources that will penetrate the distribution sector. Communication and user interfaces will be pervasive, and the integration with the new web of things will allow individual home and business electric devices to be controlled and operated from remote locations. Power distribution will be more controllable and dispatchable, and new distribution systems will have massive automation and sensing systems that will allow any user to interact with any other one on the electrical network. A smart grid is expected to emerge in the U s . and in Europe in the next decade and to evolve thereafter; notwithstanding the avatar of this smart grid, which will be a function of the policies shaping this evolution, the desired characteristics of resilience, sustain-ability, increased energy efficiency, engaging highly dispersed assets with temporal and spatial stochastics, and breeding a new class of informed customers who engage in the grid operations are expected to be achieved. ACKNOWLEDGMENT The authors dedicate this paper to the memory of their friend and coauthor, Dr. B. Blunier, formerly an Associate professor with the Universitã de Technologie de Belfort†Montbã liard, who passed away on February 23, 2012. REFERENCES 1 W. A. Wolf â€oegreat achievements and grand challenges, †Nat. Acad. Eng. Bridge, vol. 30, no. 3/4, p. 6, 2000.2 S m. Amin and B. F. 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Energy Convers. vol. 25, no. 3, pp. 901†908, Sep. 2010.1162 IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 48, NO. 4 JULY/AUGUST 2012 Marcelo Godoy Simã es (S†89†SM€ 98) received the B. S. and M. S. degrees from the University of SãO Paulo , SãO Paulo, Brazil, in 1985 and 1990, respectively, the Ph d. degree from The University of Tennessee, Knoxville, in 1995, and the D. Sc. degree (Livre-Docã ncia) from the University of SãO Paulo in 1998. He is currently an Associate professor at the Colorado School Of mines, Golden, where he has been establishing research and education activities in the development of intelligent control for high-power-electronics applications in renewable-and distributed-energy systems. Dr. Simã es is currently the Past Chair of the IEEE Industry Applications Society/International Advance Computing Conference and a Cochair of the IEEE Industrial Electronics Society Smartgrid Committee. He has been involved in activities related to the control and management of smart grid applications since 2002 with his National Science Foundation CAREER award â€oeintelligent Based Performance Enhancement Control of Micropower Energy Systems. †Robin Roche (S†09) received the M. S. degree in electrical engineering from the Universitã de Technologie de Belfort†Montbã liard, Belfort, France, in 2009, where he is currently working toward the Ph d. degree in electrical engineering in the Research Institute on Transportation, Energy and Society (IRTES. His research interests include intelligent energy management in power systems, smart grids, applications of computational intelligence, energy storage, and hybrid vehicles, as well as the societal and economic impacts of these technologies. Elias Kyriakides (S†00†M†04†SM€ 09) received the B. Sc. degree in electrical engineering from Illinois Institute of technology, Chicago, in 2000, and the M. Sc. and Ph d. degrees in electrical engineering from Arizona State University, Tempe, in 2001 and 2003, respectively. He is currently an Assistant professor in the Department of Electrical and Computer engineering, University of Cyprus Nicosia, Cyprus, where he is a Founding Member of the KIOS Research center for Intelligent Systems and Networks. He is the Action Chair of the European Science Foundation COST Action IC0806 â€oeintelligent Monitoring, Control, and Security of Critical Infrastructure Systems†(2009†2013). His research interests include synchronized measurements in power systems, security and reliability of the power system network, optimization of power system operation techniques, modeling of electric machines, and renewable energy sources. Sid Suryanarayanan (S†00†M†04†SM€ 10) received the Ph d. degree in electrical engineering from Arizona State university, Tempe, in 2004. He is currently an Assistant professor in the Department of Electrical and Computer engineering, Colorado State university, Fort Collins, where he serves as the Site Director of the Center for Research and Education in Wind and as a 2011†2012 Resident Faculty Fellow of the School of Global Environmental Sustainability. His research interests are in the design operation, and economics of finite-inertia systems and integration of renewable-energy systems to electric grids. Benjamin Blunier (S†07†M†07) received the M. Sc. and Ph d degrees in electrical engineering from the Universitã de Technologie de Belfort†Montbã liard (UTBM ), Belfort, France, in 2004 and 2007, respectively. He studied fuel-cell-system modeling, particularly the system†s air management and control for hybrid and electric vehicles. He was an Associate professor at UTBM until his death on February 23, 2012. His research interests included fuel cell systems; electric, hybrid, and plug-in hybrid vehicles; and intelligent energy management in smart grids and microgrids. Kerry D. Mcbee received the B. Sc. degree from the Department of Engineering, Colorado School Of mines, Golden, in 1999, and the M. Sc. degree in electric power engineering from Rensselaer Polytechnic institute, Troy, NY, in 2000. He is currently working toward the Ph d. degree in the Department of Engineering, Colorado School Of mines. During his career, he has focused on power quality, reliability, forensic engineering, and distribution design for companies such as NEI Power Engineers, Peak Power Engineering, Knott Laboratory, and Xcel Energy. His field of interest is the effect of smart grid implementation upon distribution engineering and utility operations. Phuong H. Nguyen (M†06) was born in Hanoi Vietnam, in 1980. He received the B. E. degree in electrical engineering from Hanoi University of Technology, Hanoi, in 2002, the M. Eng. degree in electrical engineering from the Asian Institute of technology, Pathum Thani, Thailand, in 2004, and the Ph d. degree from the Technische Universiteit Eindhoven, Eindhoven, The netherlands, in 2010, where he started the Ph d. program with the â€oeelectrical Infrastructure of the Future†project in 2006. Since the end of 2010, he has been a Postdoctoral Researcher at the Tech-nische Universiteit Eindhoven. His research interests include distributed state estimation, control and operation of the power systems multiagent systems, and their applications in smart grids. Paulo F. Ribeiro (M†79†SM€ 88†F†03) received the Ph d. degree from the University of Manchester, Manchester, U k. He is currently an Associate professor of electrical engineering at the Tech-nische Universiteit Eindhoven, Eindhoven, The netherlands. His research interests include power electronics, power quality, system modeling and simulation, energy storage, integration of renewable resources, smart grids, engineering education, and philosophy of technology. Abdellatif Miraoui (SM€ 09) was born in Morocco in 1962. He received the M. Sc. degree from Haute Alsace University, Mulhouse France, in 1988, and the Ph d. and Habilitation degrees from the University of Franche-Comtã, Besancon, France, in 1992 and 1999, respectively. He is currently the President of Cadi Ayyad University, Marrakesh, Morocco. Since 2000, he has been a Full professor of electrical engineering (electrical machines and energy) at the Universitã de Technologie de Belfort†Montbã liard1, Belfort, France, where he was the Vice-president of Research Affairs from 2008 to 2011, the Director of the Electrical engineering Department from 2001 to 2009, and the Head of the â€oeenergy Conversion and Command†Research Team (38 researchers in 2007). He is Doctor Honoris Causa of the Technical University of Cluj-Napoca, Cluj-Napoca, Romania. He was an Editor of the International Journal on Electrical engineering Transportation. He is the author of over 80 journal and 150 international conference papers. He is also the author of four textbooks (three in French and one in English) about fuel cells. His special interests include fuel cell energy, energy management (ultracapacitor, batteries, etc. in transportation, and design and optimization of electrical propulsions/tractions. Dr. Miraoui is a member of several international journal and conference committees. He is a member of IEEE Power Electronics Society, IEEE Industrial Electronics Society, and IEEE Vehicular Technology Society. In 2007, he received a high distinction from The french Higher education Ministry, â€oechevalier dans l†Ordre des Palmes Acadã miques. †He was distinguished also as an Honorary Professor by the Transylvania University of Brasov, Brasov, Romania

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