ieee sgnc 2015

IEEE Smart Grid is the professional community of more than 70,000 professionals, practitioners and inuencers and the leading provider of globally recognized Smart Grid information.

IEEE Smart Grid brings together IEEEs broad array of technical societies and organizations through collaboration to encourage the successful rollout of technologically advanced, environment-friendly and secure smart-grid networks around the world.

CONNECT with peers and experts engaged in the research, design and development of revolutionary advances in grid modernization around the world.

PROMOTE your latest and hottest Smart Grid topics globally. Opportunities include membership on committees relating to R&D, education, publications, standards, policy technical support and social media.

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IEEE: The expertise to make Smart Grid a reality

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THE WORLDS NEWSSTAND

Previous Page | Contents | Zoom in | Zoom out | Front Cover | Search Issue | Next Page

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IEEE Smart Grid Newsletter Compendium 2015 1

4 Smart Grid: The Next Decade

6 Distribution System Synchrophasor-based Control Systems

9 Transforming Smart Grid Devices from Products to Platforms

11 Power System Flexibility

14 Quantifying the Reliability of a PMU Network

16 Integrating Distributed Resources into Wholesale Markets and Grid Operations

18 The Self-healing Grid - A Concept Two Decades in the Making

20 Is DCs Place in the Home?

22 How to Achieve Completely Automomous Power in the Next Generation of Smart Grids

26 Integrating Distributed Generation into the Smarter Grid

27 Technology Battery Advances for Smart Grids

30 Distribution Automation and the Self-Healing Network

32 Keeping Guard on Power Quality for Better Quality of Service

34 A Vision of a Smart, Happy Citizen as an Enabling Infrastructure for Smart Cities

37 The Role of Demand Side Management

40 Convergence of Electric Vehicles and the Smart Grid

42 How Advanced Metering Can Contribute to Distribution Automation

44 Virtualization of the Evolving Power Grid

46 A Migration Path for Legacy Distribution Protection and Control Systems

48 Achieving Smart Asset Management

50 Microgrids: An Emerging Technology to Enhance Power System Reliability

52 The Relationship Between Smart Grids and Smart Cities

54 Moving to Smart Substations

55 Getting a Grip on the Condition of the Low Voltage Grid

58 How Smart Devices, Online Social Networks and the Cloud Will Affect the Smart Grids Evolution

60 Disruption Becomes Evolution Creating the Value-Based Utility

63 Cooperative Wireless Networking for Smart Grid

66 DOEs Strategic Plan for Grid Modernization

68 The Complexity of Smart Grids

70 Global Utility Industry Still in Need of Transformation

72 Data Analytics for Utility Communications Networks

73 Toward A More Secure, Strong and Smart Electric Power Grid

76 Power Industry is Embracing Automated Demand Response Standard

78 Appendix A - Definitions of the IEEE Smart Grid Domains

79 Appendix B - Definitions of the IEEE Smart Grid Sub-domains

80 Author Index

80 Acknowledgements

OPERATIONS

IEEE SMART GRID NEWSLETTER COMPENDIUM 2015

MARKETS

TRANSMISSION

BULK GENERATION

NON-BULK GENERATION

DISTRIBUTION

CUSTOMER

SERVICE PROVIDER

TRANSMISSION/DISTRIBUTION/CUSTOMER

FOUNDATIONAL SUPPORT SYSTEMS

WELCOME LETTER

APPENDIX/ACKNOWLEDGEMENTS

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EDITOR IN CHIEFEbrahim [email protected]

ASSOCIATE EDITORAngelique Rajski [email protected]

MANAGING EDITORBill [email protected]

EDITORIAL BOARDMassoud AminJay GiriHossein Pakravan Panayiotis MoutisJoseph PaladinoPatrick RyanJulie Compton Bo Yang

IEEE SMART GRIDChair, Massoud Amin Past Chair, Wanda Reder Project Manager, Angelique Rajski Parashis 445 Hoes Lane, Piscataway, NJ 08854, USA+1-732-981-2866Smartgrid.ieee.org

2 IEEE Smart Grid Newsletter Compendium 2015

IEEE Smart Grid provides expertise and guidance for individuals and organizations involved in the modernization and optimization of the power grid. IEEE Smart Grid brings together IEEEs broad array of technical societies and organizations through collaboration to encourage the successful rollout of technologically advanced, environment-friendly and secure smart-grid networks around the world.

IEEE SMART GRID NEWSLETTER COMPENDIUMThe IEEE Smart Grid Newsletter Compendium Smart Grid: The Next Decade is the first of its kind promotional compilation featuring 32 best of the best insightful articles from recent issues of the IEEE Smart Grid Newsletter and will be the go-to resource for industry profes-sionals for years to come. The Compendium also introduces for the first time the IEEE Smart Grid Domains and Sub-Domains created by IEEE Smart Grid members who were inspired by the National Institute of Standards and Technology (NIST) Conceptual Model. Each of the 32 articles is categorized into its appropriate IEEE Smart Grid sub-domain. The articles were selected by the IEEE Smart Grid Publications Commit-tee from an array of 200+ articles by thought leaders around the world. The IEEE Smart Grid Newsletter Compendium serves as a platform for IEEE Smart Grid Society exposure.

IEEE SMART GRID NEWSLETTERSmartgrid.ieee.org/newsletterThe IEEE Smart Grid Newsletter is a complimentary monthly online publication that launched in January 2011 and features practical and timely technical information and forward-looking commentary on Smart Grid developments and deployments around the world. The Newslet-ter is designed to bring clarity to the global Smart Grid industry and to foster greater understanding and collaboration between diverse stake-holders, and brings together experts, thought-leaders, and decision-makers to exchange information and discuss issues affecting the evolution of the Smart Grid.

The IEEE Smart Grid Newsletter publishes articles authored by a mix of IEEE and non-IEEE members. Responsibility for the content rests upon the authors and not upon the IEEE, the Technical Community, or its members.

IEEE SMART GRID TECHNICAL COMMUNITYThe following IEEE societies and organizational units are partners of IEEE Smart Grid:IEEE Communications SocietyIEEE Computer SocietyIEEE Control Systems SocietyIEEE Dielectrics and Electrical Insulation SocietyIEEE Industrial Electronics SocietyIEEE Industry Application SocietyIEEE Instrumentation & Measurement SocietyIEEE Power & Energy SocietyIEEE Power Electronics SocietyIEEE Reliability SocietyIEEE Signal Processing SocietyIEEE Standards AssociationIEEE Vehicular Technology Society

To join the IEEE Smart Grid Technical Community as a member for free, please visit IEEE Smart Grid at smartgrid.ieee.org and click on Join Technical Community in the top right corner.

Copyright and reprint permissions: Abstracting is permitted with credit to the source. For other copying, reprint, or republication permission, write Copyrights and Permissions Department, IEEE Operations Center, 445 Hoes Lane, Piscataway, NJ 08854 USA. Copyright 2015 by the Institute of Electrical and Electronics Engineers, Inc. All rights reserved.

Printed in the USA.

IEEE Smart Grid Newsletter Compendium 2015

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_______________

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Become a member of IEEEs team of globally-recognized Smart Grid leaders

For more information, contact Angelique Rajski at [email protected]

Join the IEEE Smart Grid Community

SHARE YOUR EXPERTISE! Please join one of the following committees

For a FREE Membership to the IEEE Smart Grid Technical Community, visit us at smartgrid.ieee.org

- Smart Grid R&D

- Smart Grid Publications

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- Smart Grid Marketing

- Smart Grid Education- Smart Grid Meetings

& Conferences

- Smart Grid Policy Technical Support

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_________________


WELCOME LETTER

IEEE Smart Grid Newsletter started its publication nearly five years ago, in Janu-ary 2011. So far, more than 215 carefully selected articles have been published in a variety of Smart Grid topics. This compre-hensive inventory provides a rich collection of concise and easy-to-read Smart Grid material from thought leaders and experts in Smart Grid technologies, summariz-ing the body of research and development work all over the world.

Making the Smart Grid a reality along all its vectors requires the engage-

ment of public and private enterprises, innovators and technologists working in many areas where IEEE convenes and leads, some of which include power and energy, sensing, measurement, signal processing, communications, controls, computer and information sciences, big data and analytics, smart cities, Internet of Things, security, standards, materials and devices.

The Smart Grid is a subject of na-tional and regional priority, not just in the United States but in Europe, Can-

ada, South Korea, China, India, Latin America and many other nations. Vari-ous and different aspects of the Smart Grid concepts and applications are emphasized from country to country. However, all countries share a vision of a highly instrumented, overlaid system with advanced sensors and computing with enabling platforms and technolo-gies for secure sensing, communications, automation and controls. These are key elements to engage consumers, enhance efficiency, ensure reliability and security,

Smart Grid: The Next DecadeWritten by Ebrahim Vaahedi, Hossein Pakravan, Angelique Rajski Parashis and Massoud Amin

IEEE Smart Grid Compendium

Figure 1: NIST Smart Grid Framework 3.0

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and to enable integration of renewables and electrification of transportation.

The purpose of this Compendium though, is to distill this pertinent body of knowledge in a disciplined way to those interested in obtaining a holistic understanding of the Smart Grid. To that end, this Compendium showcases the best of the IEEE Smart Grid News-letter articles in different areas of IEEE Smart Grid Domains.

A challenge that the IEEE Smart Grid Committee faced early on, concerning essentially all of its activities, was how to establish the different areas of Smart Grid as noted above. This categorization would allow Smart Grid contributions and activi-ties to be combined into specific targeted areas for better understanding of the ac-tivities and their correlations. To organize Smart Grid categories in a coherent and disciplined way, the Committee started with the Conceptual Framework 3.0 dia-

gram published by the National Institute of Standards and Technology (NIST), which provides different domains in the energy industry as shown in Figure 1 on page 4.

The NIST Smart Grid Framework 3.0 is based on the major processes that are ex-ecuted in conducting the day-to-day busi-ness within the energy industry. The IEEE Smart Grid Committee used this diagram as a reference document, but it needed to expand it to cover all the important areas of the Smart Grid both for today and with a view toward the future. As such, the fol-lowing enhancements were made:

1) The generation domain was di-vided into bulk generation (con-ventional generation resources) and non-bulk generation (distrib-uted energy resources)

2) Added a domain called Foun-dational Support Systems to cover all other areas which sup-port the main domains

3) Developed sub-domains for each domain

The above additions created a me-thodical approach for organizing the Smart Grid into 32 sub-domains as shown in Figure 2 above.

Each of the 32 sub-domains have been further divided into focus areas covering most of the activities and proj-ects within the Smart Grid arena. Ap-pendices A and B provide the definitions of Domains and Sub-Domains included in the IEEE Smart Grid Model.

While it is expected the IEEE Smart Grid model to evolve in time, it provides a good approach for organizing the widest possible range of Smart Grid-related ac-tivities. This Compendium represents the best effort to provide a collection of top Newsletter articles in each sub-domain.

Figure 2: IEEE Smart Grid Domains and Sub-Domains

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Demonstration projects in the UK are evaluating the use of pha-sor measurement units in wind generation control and microgrid man-agement. But the potential of PMUs in distribution systems does not end there. They also will find application in phase balancing using three-phase measure-ment, improved state estimation, locat-ing faults in distribution systems with generation, short circuit capacity iden-tification, and improved modelling and efficient reinforcement planning, among other things.

Synchrophasor Measurement Units (PMUs) are being increasingly deployed across transmission power grids world-wide. With each PMU capturing 1216 measurements, up to 60 times each sec-ond, with precise time-tags, operators will be armed with a degree of action-able visibility that is unprecedented in the history of grid management. PMUs produce sub-second high-resolution grid measurements, which augment the tra-ditional 24 seconds SCADA measure-ments. For the first time in history, grid operators will be provided with a time-synchronized view of grid conditions.

Today transmission control centers are deploying PMU measurement-based analytics that augment the traditional model-based energy management ana-lytics and pave the way for us to moni-tor, analyze and control grid behavior at a sub-second rate. An advanced vi-sualization framework synthesizes in-formation from the various analytics to

provide operators with not just improved situational awareness, but more impor-tantly, actionable information. Operators want to fix problems, not just know about them.

Operational benefits of adding synchro-phasor applications at the transmission control center in-clude maximizing utilization of exist-ing transmission ca-pacity by operating the grid closer to its true operating limit; pro-viding early warning of grid disturbances; monitoring for un-desirable grid dynamics and oscillations; identifying islanding conditions; and en-abling efficient forensic post-disturbance analysis to find out what just happened, where and why.

Managing the smart grid of the fu-ture will require that we add intelligent solutions not just to the high-voltage transmission but also to lower-voltage distribution systems. Thus, ways are being developed of using synchronised measurement technologies to improve the capabilities of the distribution sys-tem to accommodate sustainable energy resources and maintain or improve secu-rity of supply.

Active network management is be-ing increasingly used to facilitate con-nection of more renewable generation to distribution grids. Direct control is

needed especially to limit generation to enable the network to be loaded beyond the present security limits. This involves

constraining the active plant con-nected to the network, so that

the network is not loaded beyond its safe capa-

bility. Generation, loads, tap changers and storage devices can be candidates for active control to maintain system

operation within its safe operating bound-

aries, such as: thermal constraints, voltage limits,

fault level limits and for power re-versals in transformers.

So far, the most active network man-agement schemes have used steady-state measurements at all possible constrain-ing boundaries and define the output limits for the participating devices. A great many measurement points are re-quired to capture network limits, which implies a high dependency on measure-ment and communication from many lo-cations. What is more, such schemes are generally defined for intact networks and are not easily reconfigured for mainte-nance schedules.

By using synchrophasor measure-ments, it is possible to capture key op-erating conditions of the system without detailed monitoring. Synchrophasor measurements provide a better represen-tation of the loading conditions between

OPERATIONS

Distribution System Synchrophasor-based Control Systems Written by Jay Giri and Douglas Wilson

Distribution Operation

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EXPAND YOUR NETWORK & ENHANCE YOUR CAREER

WITH IEEE PES

Whether youre a young professional or a top executive, being a member of the IEEE Power & Energy Society can help you expand your network and enhance your career. Whether its chairing a committee, writing articles for our publications, speaking at or attending one of our many conferences, or presenting as part of our monthly webinar series, PES members get involved.

To learn more about connecting with our membership of 33,000 electric power industry professionals, Visit our website at ieee-pes.org

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the measured locations. Limits based on angle difference between synchropha-sors, or other values derived from the synchrophasor measurements, enable constraint enforcement using fewer mea-sured variables and therefore simpler reli-able control schemes.

Furthermore, the speed of synchro-phasor measurement captures the dy-namic behavior of the power system and therefore can be used to provide a fast response to a fault or system reconfigu-ration. Another advantage is that PMU-based systems can be designed to accom-modate maintenance scenarios with one or more outages.

The concept of using synchrophasor measurements in wind generation control in a 33kV network is being demonstrated in the Scottish Power Manweb network in the UK. In the network where the scheme is applied, a total of 18 potential constraint locations can be accommo-dated with four remote measurements. In the part of the network where the project is applied, the capacity for fit-and-for-get wind connections is fully used, with no direct control of generation; and any new connections require either expensive network reinforcement or active control.

Applying a conventional control ap-proach would require many monitor-ing points, as relieving one constraint through a measurement fed into a con-troller would result in another unob-served network segment becoming the constraining factor, and so on.

In a relatively complex 33kV net-work, many line currents, voltage levels and transformer loads need to be moni-tored and included in an active control mechanism. By contrast, synchrophasor measurement provides angle differences between key points of the network that summarise the loading within sections of the network with many components. The phasor measurements can differentiate the high generation / low load scenarios where generation should be constrained, with only a few measurements.

Synchrophasor information also can be important in a microgrid where gener-ation resources are dispersed and require remote measurement and communica-tion to manage the changeover between

grid-connected and autonomous opera-tion and ensure supply to connected loads.

In a demonstration project in the UK, the use of synchrophasors is being tested on the Isles of Scilly network on geo-graphic islands off the coast of England. The intention of this project is to show that a network of phasor measurements can be used to: Identify the separation and the con-

nections between distributed gener-ators. Instead of shutting down and restarting generation that has sepa-rated from the bulk transmission system, it is possible to continue to supply load using the local distrib-uted generation. Separation from the transmission system must be detectable, and the control scheme of the island must be adapted to the emergency scenario.

Signal to the generators which mode of operation to deploy: grid-connected, speed setting, or speed following. Grid-connect-ed, the generator will operate in constant power mode, without responding to frequency. When the distribution subsystem is separated from the bulk grid, the local generation must maintain a stable frequency. One generator should be designated speed set-ting for the network and run in a frequency control mode. Other generators connected to the same subsystem will operate with a droop characteristic. However, there can be different topologies and generation connection, so the control mode must be decided when the fault occurs.

Align the generator angle to a re-mote angle in the bulk grid. This is done through the same mecha-nism that the generator uses for synchronising to the grid, but with the difference that the gov-ernor control and alignment is applied to a remote measurement in the bulk grid rather than the grid-side of its own breaker.

Enable or block the resynchro-nisation of the island network with the bulk grid.

The advantage of this application is to ride through loss of connection between the geographic islands and the bulk grid, and the reconnection, without loss of supply to the customers.

In considering the overall benefits of incorporating phasor measurement units in distribution system design, bear in mind that PMUsin contrast to tradi-tional SCADA measurementsmeasure all three phases of voltages and currents. Therefore they are ideally suited to moni-tor unbalanced distribution systems and have immense promise for the intelligent management of distribution networks. There are opportunities for improved ob-servability and control that can improve power quality and grid resilience; better planning decisions also will result.

The cases described in this paper illustrate only two applications of syn-chrophasor measurements, in renewable generation connection and microgrid management. But there are many more applications that can be explored through similar pilot projects and later rolled out to widespread application. For example, the technology can be applied to phase balancing using three-phase measure-ment; significantly improved state es-timation, as most distribution networks are not fully observed; managing open points for running in a closed loop con-figuration or for ease of switching to move the open point; locating faults in distribution systems with generation; short circuit capacity identification; and improved modelling and efficient rein-forcement planning.

Having said that, there is a need for many more demonstration projects to be applied to a variety of different systems in order to gain practical experience, evaluate benefits and standardize the design and deployment processes. These project experiences will be invaluable to-wards making these solutions available for beneficial use in distribution systems worldwide.

ContributorsJay Giri, an IEEE Fellow, is Di-

rector of Power Systems Technology and Strategic Initiatives at ALSTOM Grid in Redmond, Washington, and

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an affiliate professor at the Univer-sity of Washington, Seattle. In 1978, he and 11 other engineers co-founded Energy System Computer Applications (ESCA), which after numerous mergers became part of Alstom Grid in 2010. Previously, at ESCA, he designed and implemented the original software for an automatic generation control sys-tem that controls half of North Ameri-can generation today, and a dispatcher training simulator that is used world-wide. He earned his doctoral degree at Clarkson University in New York, and his bachelors at the Indian Institute of Technology (IIT), Madras. He is a member of the IEEE Power & Energy Society governing board.

Douglas Wilson is Chief Tech-nology Officer for Psymetrix Ltd, an Alstom company. He has worked with Psymetrix since 1998, and was involved in developing and deploy-ing the worlds first continuous os-cillation monitoring system, which has been operational in the GB sys-tem for 15 years. He has an interest in synchrophasor measurement, with an emphasis on the application of the technology in real-time operational systems, dynamics analysis and con-trol, control system tuning, and re-newable generation connections. He graduated B.Eng and PhD from the University of Edinburgh and MSc from the University of Manchester.

He is involved in R&D, consulting and in commercial application of synchrophasor technology. This has included working closely with cus-tomers on WAMS applications in over 40 projects worldwide. He has been involved in consulting and studies projects in North and South Ameri-ca, Scandinavia, GB, Australia, New Zealand and Central Europe. This work includes a wide range of topics including power system performance studies, risk assessments, wide area control design, root cause analysis for dynamics problems, disturbance analysis, and controller tuning.

Transforming Smart Grid Devices from Products to PlatformsWritten by Michael W. Howard

Field Device Operation

dvancements in integrated circuit technology have made it possible

for expanded flexibility in grid devices such as advanced meters, smart switches, reclosers, capacitor control-lers and voltage regulators by building them as platforms for applications in-stead of products with built-in, limited functionality. Utilities could gain a new degree of control and manageability over their systems, and distributed resources, such as PV smart inverters, energy stor-age controls and electric vehicle charg-ing stations are also good candidates for these open application platforms.

Up until a few years ago, most com-mon personal electronic devices such as cell phones and personal digital as-sistants (PDAs) had fixed functionality. Manufacturers differentiated their prod-ucts by offering new built-in capabilities, but these were inflexible, and the user had no control or ability to modify their product.

Today, users think of their PCs and smart devices separately from the ap-plications that run on them. The devices come with certain functionality pre-load-ed, but users can tailor them to their per-sonal needs by adding new apps at any

time. This makes the devices platforms that can expand their capabilities, rather than just products.

When a platform is made open and ac-cessible, a wide range of entitieslarge and small companies, consultants or individualscan offer applications that run on it. Application development re-quires an in-depth understanding of cus-tomer needs, creativity, and innovation, but does not require capital-intensive plant or tool investments. Manufacturers are taking advantage of this capability to more efficiently update and evolve their product offerings, and its now possible

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for the users and owners of these devices to independently develop or acquire apps to load and run on their equipment.

Advancements in integrated cir-cuit technology have made it possible for the same flexibility to exist in grid devices such as advanced meters, smart switches, reclosers, capaci-tor controllers, and voltage regulators. Utilities would gain a new degree of con-trol and manageabil-ity over their systems, and could work both with the origi-nal equipment manufacturers and inde-pendently to add new functionality to their equipment. Distributed resources, like PV smart inverters, energy storage controls and electric vehicle charging stations are also good candidates for an open application platform.

This transformation of smart grid equipment can be very beneficial: Extending useful service life

platform devices could be up-graded more effectively over time to revise and/or enhance their functionality. This capabil-ity is particularly valuable for products with the possibility of long service lives.

Communication upgradeabilitywhole communication protocols, cyber security, routing, address-ing, etc. could be upgraded when needed.

Customizationusers with unique needs could gain the spe-cific functionality they require.

Timelinessthe independent nature of app development could make features available in a more timely fashion, aligning with overall utility projects.

CompetitionWith standardized platforms, both hardware and ap-plication providers could be held to higher standards of product quality and customer service.

CreativityA greater number of companies with opportunity to develop device functionality could lead to a broader range of

more innovative products.The value can be in-

creased if the applica-tion environment for classes of platforms is standardized. In this way, a devel-oper could create an application once and

it would be compat-ible with many brands

and models of the intend-ed class of product.

The vision of open platforms includes the ability to run many ap-plications simultaneously. For example, using a single device, a utility could deploy one app to monitor power qual-ity disturbances, another app for outage reporting, and a third for detecting and reporting tampering or thermal issues.

EPRI currently is working with a group of interested parties to develop one example of an open application platform focused on the meter as the device type. This group includes utilities, meter manufacturers, and other technology companies. EPRI and the meter manufac-turers also are inde-pendently developing hardware platforms that support the Applica-tion Program Interface (API) and virtual ma-chine. These develop-ments are in preparation for open application demonstrations that will follow.

EPRI plans to further develop this platform capability and contribute to standards organizations. Some stake-holders favor the establishment of a certi-fication and compliance framework that could be applied to both platforms (such as meters) and apps. An independent authority would test products and ap-

plications to ensure that they had proper design and would interoperate with other products built to the same standard.

Upon completion of a meter open platform specification, EPRI and par-ticipating manufacturers plan to demon-strate the results and capability. These demonstrations would be conducted at various industry conferences and events and would consist of the independent development of a few example applica-tions, perhaps developed by university students or other research entities.

In the end, the evolution of smart grid devices from products to platforms will be driven by costs and benefits. EPRI does not view open apps as driving any significant product cost, but rather as following the natural upward evolution of silicon capability and performance. The benefits lie in the enabling of need-ed new functionality, the correction of problems, and the extension of useful service life.

You can find out more about what EPRI is doing to advance the grid tran-sition from products to platforms in a new public report, Transforming Smart

Grid Devices into Open Application Plat-forms (EPRI document 3002002859, available for download on the EPRI website).

ContributorMichael Howard is

the President and CEO at the Electric Power Re-search Institute (EPRI). He has more than 30 years of experience in organizations ranging from entrepreneurial

start-ups to large public companies with increasing responsibilities in operations, finance, sales and marketing, product de-velopment, and strategic planning. Most of his experience is in providing techni-cal consulting services and products to both U.S. and international electric util-ity companies.

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The vision of open platforms includes the ability to run many applications simultaneously.

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Power System FlexibilityWritten by Arshad Mansoor, Clark Gellings and Ron Schoff

Transmission Operation

Increasingly, power systems will in-corporate distributed smart technolo-gies, flexible communication, a wide variety of digital devices on the power systems, and distributed command and control systems. In this new world, flex-ibility will be keyflexibility of genera-tion resources, flexibility of the transmis-sion and distribution system, flexibility at the consumer level, and flexibility of the market to incentivize the power system to account for variability.

In the last decade there has been a nine-fold increase in the global installed capacity of variable generation from wind and solar, which now comprise approximately 7 percent of total world capacity. In some countries such as Ger-many and Spain, variable generation comprises nearly 30 percent of installed capacity. At the same time, consumers are reaping the benefits of a connected lifestyle through end use technologies such as electric vehicles, consumer elec-tronics and home appliances.

The grid is evolving to keep pace with those changes, as more intelligent electronic devices including sensors, data and communications technologies are deployed. But the changes on both the demand and supply sides represent a challenge to how the grid is managed. The industry is having to rethink how to match load with bulk power generation, and how best to monitor and possibly control both bulk and local variable gen-eration and storage resources whose per-formance and availability is inherently difficult to forecast.

Increasingly, power systems will in-corporate distributed smart technolo-

gies, flexible communication, a wide variety of digital devices, and distributed command and control systems. The in-tegrated communications infrastructure will require hardening for cyber security to ensure reliable long-term operations of millions of nodes.

In short, the power system of tomorrow will look very different from todays. In this new world, f lexibility will be keyflex-ibility of generation resources, flexibil-ity of the transmis-sion and distribution system, flexibility at the consumer level, and flexibility of the market to incentivize the power system to ac-count for variability.

What follows is an overview of some of the technology innovations in trans-mission and distribution and in energy utilization that could make the power system more flexible, with some em-phasis on work done here at the Electric Power Research Institute (EPRI). It, of course, only scratches the surface; many more technology innovations are under development that could offer greater flexibility, and more will emerge as the industry evolves.

With the proliferation of new genera-tion storage, and end-use technologies, the architecture of the power system will need to adapt. One concept that could support adaptation is EPRIs service-marked ElectriNet, a combination of local energy networks that includes in-

terconnected distributed end use, local generation, storage, and utility technolo-gies at the building, community, or dis-tribution level.

ElectriNet offers the potential for greatly enhanced flexibility through

improvements in energy delivery and efficiency, power qual-

ity, reliability, and cost of operation for very

concentrated and localized loads. To fully realize these benefits, however, it will be necessary to coordinate the con-

trol of complex local energy networks that

may comprise several different kinds of local gen-

eration and storage systems, which may also be geographically dispersed.

The present grid operating system was not designed to offer that coordi-nation and control. A new grid operat-ing system, which we at EPRI refer to as Grid Operating System 3.0, could allow sufficient flexibility to facilitate high levels of security, quality, reliabil-ity, and availability of electric power; improve economic productivity and quality of life; and minimize envi-ronmental impact while maximizing safety. This new grid operating system will monitor, protect and automatically optimize the operation of its intercon-nected elementsfrom the central and distributed generator through the high-voltage network and distribution system, to industrial users and building automation systems, to energy storage

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installations, and to end-use consumers including their thermostats, electric ve-hicles, appliances, and other household devices.

Grid 3.0 must manage a two-way flow of electricity and information to create an automated, widely distributed energy de-livery network. It must also incorporate the benefits of distributed computing and communications into the grid to deliver real-time information and to enable the near-instantaneous balance of supply and demand at the device level.

Grid 3.0 will enable additional in-novations such as the use of dynamic protection. This concept builds on the laws of physics to develop protection ap-proaches that do not depend on system studies. This new approach automati-cally adjusts protection to the situation through the use of high-speed data ac-quisition and basic power system analyt-ics, eliminating one of the major causes of power system failures.

With the advent of photovoltaic (PV) and other distributed generation resourc-es, consumers may now be served by a combination of grid-supplied energy services and power generated on-site. Availability of local generation and stor-age in combination with sophisticated end use devices such as plug-in electric vehicles offers inherent flexibility for consumers.

Plug-in electric vehicles, both all-electric and hybrid, could be used to supply energy to a home during an out-age. Hybrid electric vehicles also could operate as a gasoline-fueled generator to provide additional standby power. Auto-makers are interested in the concept, but the technologies require further devel-opment. Nissan Motor Co., Ltd. recently unveiled a system that enables the Nis-san Leaf to connect with a residential distribution panel to supply residences with electricity from its lithium-ion batteries. The batteries can provide up to 24 kWh of electricity, sufficient to power a households critical needs for up to two days.

Increasingly, consumers are install-ing rooftop PV systems to augment grid-supplied electricity. Usually limited by roof area and sized to meet an economi-

cally viable portion of the buildings electrical needs, these systems cannot supply 100 percent of a residences typi-cal demand, nor do the systems, as cur-rently configured, allow for operation as independent microgrids to supply part of a residences needs. EPRI assessments have identified inverter and control de-signs that could convert PV systems into self-sufficiency technologies, but few inverter manufacturers have stepped for-ward to serve this need.

The existing controls associated with PV arrays are not sufficiently function-al to match the electrical demand of a residence without grid supply or local storage. Companies are developing resi-dential circuit breaker panels that can control individual circuits and appli-ances. Control devices could be devel-oped to weave these breaker panels into the PV system, so that when grid power is lost, load is automatically curtailed to balance supply and load for the resi-dential microgrid. These systems also could manage the ramps that occur as the sun rises and sets, or as clouds block sunlight.

Solar and wind energy eventually will get a boost from evolving energy storage technologies, which help make variable generation dispatchable and can provide a temporary solution to overcome regional and local capacity shortages and localized transmission and distribution congestion. Advances in technology and expansion in pro-duction capacity have brought some storage technologies to the verge of cost-effectiveness, but their overall economics are still marginal. A broad-er range of benefits must be realized for these technologies to become cost-effective. The applications that con-tribute to the value of storage solutions have various requirementsmeeting certain ramp rates, storage capacity, round-trip efficiency, and othersand these requirements have not yet been systematically developed, nor have the issues of allocating the costs and ben-efits across different portions of the power system.

Careful policy formulation, accel-erated infrastructure investment, and

greater commitment to public/private research, development, and demonstra-tion can help overcome such barriers to grid modernization and provide the flexibility needed for optimal operation. As our power system becomes more variable on both the generation and consumer sides, the grid will need to act flexibly to maintain balance. Tech-nology development should be a central component of the strategy to provide balancing resources as more variable generation is added.

ContributorsClark W. Gellings, a fellow at the

Electric Power Research Institute, has had a long career in technical manage-ment at EPRI, serving in seven vice-pres-idential positions. He is a life fellow of IEEE and an honorary and distinguished member of CIGRE, the International Council on Large Electric Systems. He is a past-president of CIGREs U.S. Na-tional Committee.

Arshad Mansoor is Senior Vice President, Research and Development for the Electric Power Research Institute (EPRI). Previously he served as Vice President of EPRIs Power Delivery and Utilization sector where he led research, development, demonstration and appli-cation of transmission and distribution and energy utilization technologies; as Vice President of the former EPRI sub-sidiary, EPRI Solutions; and as Vice President and Director of Engineering with the EPRI Power Electronics Appli-cation Center.

Ron Schoff is the manager of the Technology Innovation (TI) program at the Electric Power Research Insti-tute (EPRI). The programs portfolio of cross-cutting research, development and demonstration projects scouts, in-fluences and builds on early-stage work across the global science and technology communities to capture innovations for application-oriented development and demonstration by EPRI.

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IEEE Standards & Smart Grid: Uniquely Positioned for InteroperabilityIEEEs technical explorations, standards, and standards projectsfrom infrastructure to securityand the interconnection of various distributed resources, has no match.

IEEE has more than 100 standards and standards in development relevant to smart grid, including the over 20 IEEE standards namedin the NIST Framework and Roadmap for Smart Grid Interoperability Standards. In addition, IEEE Smart Grid Research is building oneof the industrys most comprehensive portfolios of smart grid- related intelligence, including materials such as visiondocuments and research papers that address problemsand challenges in both the long- and short-term.

Get involved in Smart Grid standards development, visit standards.ieee.org/getinvolved

Find & purchase standards & Smart Grid Research, visit standards.ieee.org/findstds/standard/smart_grid.html

Subscribe to the Smart Grid community,visit smartgrid.ieee.org

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Quantifying the Reliabilityof a PMU NetworkWritten by Wenyuan Li and Yang Wang

Visiblity and Control

The wide area measurement system (WAMS) is gradually becoming an important guarantee of security and stability in smart transmission grids. In the utility industry, WAMS is some-times referred to as a PMU (phasor mea-surement unit) network, as synchronized PMUs are the most crucial elements in collecting real-time monitoring infor-mation. A PMU network provides much better observability and controllability in smart grid operations. However, like any other physical system, a PMU net-work itself can fail. The consequences of PMU network failure are serious and can include a large blackout. Therefore, the reliability of PMU networks should be quantitatively evaluated and assured.

A PMU network is composed of PMUs at substations and generation sta-tions, phasor data concentrators (PDCs), local communication networks, backbone communication networks and a control center. The reliability of a PMU network can be quantified using reliability evalua-tion methods. A PMU network is divided into three types of substructures: the pha-sor measurement devices, the regional communication network and the back-bone communication network. The basic procedure consists of two main steps. The failure modes of modules in each substructure are analyzed first to build an equivalent two-state reliability model of substructure using different evaluation techniques. Then the equivalent reliability models of the substructures are combined to assess the reliability of the whole PMU network using a fault tree analysis method.

In the hierarchical structure, a PDC and multiple PMUs constitute a PMUs-

PDC working group, in which communi-cation is carried through a regional net-work. Multiple PMUs-PDC groups are connected to the control center through a backbone communication network that is composed of fabric links and ring in-terface units.

A PMU device can be divided into seven mod-ules in light of their operational functions for reliability evalu-ation. Each module can be further bro-ken down into sub-components. Mar-kov models for the sub-components and modules, which are based on state space diagrams and transitions between states, are devel-oped first and then these models are con-verted into an equivalent two-state model, which can be used to quantify the reliabil-ity indices of the PMU device and easily incorporated into the reliability evaluation of PMUs-PDC working groups.

A regional communication network transmits information between PMUs and PDC. Regional communication networks can be classified into three categories. In the first category, PMU measurement information is transmitted through the utilitys own existing facili-tieson a carrier wave or microwave communication channels, for example. In the second category, a commercial optic fiber communication network is used. In the third category, a communi-cation network is built by utility specifi-cally for PMU information.

The reliability of a regional commu-nication network is associated with con-nectivity identification between multiple inputs (many PMUs) and a single output (one PDC) under contingency conditions. A network survival mechanism refers to

the way of recovering normal data transfer in the network af-

ter a contingency event such as a link failure.

Network survival mechanisms can be classified into static protection and dy-namic restoration. In the static protec-

tion scenario, a back-up path is pre-estab-

lished together with the primary path for each PMU.

In dynamic restoration, no backup path is pre-specified. When a contin-gency happens, a search process starts to dynamically find a possible backup path. A set of reliability evaluation techniques can be used to quantify the reliability of a regional communication network. These include graph theory, set theory and min-imum cutsets (minimum combinations of component failures that can cause sys-tem failure).

The backbone communication net-work transmits information between PDCs and the control center. It is often designed as a synchronous optical net-work with a synchronous digital hierar-chy ring configuration and dual-passages. In general, there are two optic fiber rings in the network. One is the primary op-tic fiber ring to transmit working digital signals in the normal operation state, and

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the other is a standby optic fiber ring that can transmit the same digital signals only in a contingency situation through successful switching operation. This is called the 1+1 backup mode.

From a reliability evaluation view-point, the backbone communication network can be modeled using commu-nication interfaces in series with an optic fiber system module. A combined meth-od of Markov models and the state enu-meration technique has been developed to quantify the reliability of the optical fiber system and whole PMU network.

Data uncertainty is a challenge for PMU network reliability assessment. PMUs have been installed in power systems only in recent years. The sta-tistical failure data of PMUs are still sparse, which introduces imprecision in estimation of reliability parameters of PMUs components. A solution to take account of the uncertainty is the application of combined statistical and fuzzy Markov methods.

The methods and models described above have been applied to an IEEE

test system and an actual project at BC Hydro, Canada. The applications demon-strated that PMU network reliability can be quantified using the presented meth-ods and models. An equivalent reliabil-ity two-state model for the whole PMU network can be obtained from quantified reliability assessments. Such an equiva-lent model provides flexibility for the reliability evaluation of an integrated smart transmission grid that is composed of a traditional electric power system and PMU network. This is a new topic in smart grid reliability.

ContributorsWenyuan Li, an IEEE fellow, is

a principal engineer at BC Hydro in Canada, a professor with Chongqing University in China and an adjunct pro-fessor with Simon Fraser University in Canada. He has published five books and over 170 papers in power system reliabil-ity, probabilistic applications and system operations. He has received several pres-tigious awards including the IEEE PES Roy Billinton Power System Reliabil-

ity Award (2011), the International Merit Award of the Probabilistic Methods Ap-plied to Power Systems Society (2012) and the Electric Power Medal from the IEEE Canada (2014). He is a fellow of the Canadian Academy of Engineering and the Engineering Institute of Canada, and an editor of the IEEE Transactions on Power Systems and the IEEE Power Engineering Letters. He graduated from Tsinghua University in 1968 and re-ceived his M.Sc. and Ph.D. degrees from Chongqing University in 1982 and 1987.

Yang Wang, an IEEE member, is a post-doctoral fellow in the De-partment of Electrical and Computer Engineering at the Wayne State Uni-versity, Detroit. His research interests include wide-area measurement sys-tems, voltage stability, photovoltaic power systems, and emission reduc-tion through demand side manage-ment. He received his Ph.D. degree from Chongqing University, Chongq-ing, China in 2009.

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MARKETS

Distributed Energy Resources (DER) encompasses distributed generation including combined heat and power, wind and photovoltaic systems, demand response, energy stor-age, vehicle-to-grid systems and mi-crogrid. DER will have impacts on sys-tem operations and energy markets, which will require grid and energy mar-ket operations to embrace it. But what will be DERs impacts, and how can we model DER economics and adoption from the user point of view?

There are two aspects to integrating distributed energy resources (DER) what is known collectively as combined heat and power, wind and photovol-taic systems, demand response, energy storage, vehicle-to-grid systems and microgrids with wholesale markets and grid operations. One is the impact of DER on the grids physical stability, the other the effects of price responsive DER on wholesale market behavior. These are two very different issues, but both have implications for wholesale operations visibility and retail-level interactions.

Almost all DER is connected to the grid via power electronics, specifically by inverters. Such resources in effect decouple the grids physical dynamics from the dynamics of the DER technol-ogy. That is, inverter-based resources do not generally exhibit frequency response or response to the rate of change of fre-quency; in other words, they do not have inertial or governor response.

This does not seem alarming if DER is thought of only as a type of load. Re-sistive load also does not have inertial or governor response, and loads based on power electronics such as variable speed drives also do not ex-hibit inertial or gov-ernor response. But if we think of DER as substituting for conventional gen-eration, then the question arises as to whether the system still has sufficient iner-tial and governor response. There may also be locational issues (as opposed to interconnection or control area issues) to consider.

Operators of isolated island grids have long worried about these ques-tions, as it is well known that wind generation and distributed PV can pose risks to maintaining sufficient primary frequency response. But large control area operators faced with high renew-ables and DER penetration are starting to look at this as well. Studies assum-ing the 1520 percent penetration typi-cal of renewable portfolio standards indicate there will be no problem in many cases. But at higher penetration levels concerns build about whether NERC performance criteria can be met or whether maximum frequency deviations on large unit outages can be managed.

One tool being increasingly employed for examining system dynamic perfor-mance over the time scales of interest for

this problem is DNV GLs Kermit, which simulates grid, gener-

ation and DER dynamics on a scale of sub-sec-

onds to hours. Some existing studies fo-cus on the theoreti-cal inertia on line from conventional generators as a

function of projected unit commitment fac-

toring in renewable pro-duction. Other studies look

at the aggregate primary response available from conventional units on line based on standard droop speed settings for unit governors.

This latter evaluation works today when there are many conventional units on line and spinning reserve is provided from a handful of units. But in a future scenario where at a given moment renew-able production may displace 50 percent or more of the conventional generation in terms of on line capacity, there may be less than apparent total headroom avail-able from conventional generation for primary or governor response and for au-tomated generation control or secondary response.

Put differently, the primary gover-nor response may eat into the capacity that was thought available for spinning reserves.

Integrating Distributed Resourcesinto Wholesale Markets and Grid OperationsWritten by Ralph Masiello

Market Enablement

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If it can be shown that under some scenarios there is insufficient inertial or governor response available, then market operators have to face increased dispatch costs so as to keep conven-tional units on line for this purpose. And what if conventional plant opera-tors plan or threaten to retire plants due to inadequate revenues? Then market solutions have to be developed for the provision of inertial and governor re-sponse as ancillary services products rather than as conventional unit inter-connection standards. Conceivably, those involved in capacity markets or capacity planning would have to con-sider these factors as well.

Once market product solutions to en-suring adequate inertial and governor response are on the table, then DER and renewables developers and technology communities will demand access to these markets and revenue streams. This leads to the use of synthetic inertia and synthetic governor response provided by inverter-based DER or wind farms. Depending upon the DER technology, this can be pro-vided by, for instance, limiting the power delivered to the grid to a level below the instantaneous capability of the physical resource. For instance, a set of PV panels could be controlled to deliver less than full potential.

Wind farms without storage may have the ability to provide limited re-sponse by using the inverter to acceler-ate or decelerate the turbines for a brief period, but stress on the turbine blades is a concern.

Today NERC standards would not allow grid operators to make use of synthetic inertial or governor response. And indeed, except for a few special cases, the dynamic performance of synthetic and governor response is not well understood. But as DER pen-etration increases and the capacity to exploit these potential capabilities be-comes more and more attractive, stan-dardization will result.

At the other end of the dynamic spectrum, one of the major advantages

claimed for future smart grid technolo-gies is that end use loads will be able to respond to energy prices autonomously. What is needed here are regulatory and tariff structures allowing retail custom-ers direct access to day-ahead, hour-ahead, or real-time energy prices from the wholesale market. Their development is not a straightforward as one might think.

Under the hood of the price-respon-sive load model is a small matter of price instability in what is called a sequential market in the context of economists cobweb theory. The energy market is sequential in this context in that the sup-ply side (the market operator) clears the market using supply offers and estimated demand (load forecast or actual demand) and then publishes the price. Then the price responsive load reacts to that price. Ignoring the time dynamics of the rela-tive speed of response of generators and end use load for the moment, all is well and prices will converge over time. But if the demand side is more elastic than the supply side, the cobweb expands over time and prices diverge.

This phenomenon is not imaginary. Consider a situation in which large in-dustrial loads that have time flexibility in energy usage are subject to real time pricing. Assume that a generator outage causes the market operator to signal a combustion turbine to come on, and the real time price spikes as a result due to the instantaneous supply-demand imbal-ance. That price spike could cause the industrial load to interrupt its consump-tionand the load could respond more quickly than the generator could come on line. So when the generator does come on, in say 10 minutes, the load has dropped and there is now an imbalance. This leads the operator to decrease the price and signal generation, prompting the load to switch back on.

When we consider the stability of the market process including the different time dynamics of generation and load, the answer is more complex than just the relative elasticities. The relative time

delays matter as well. Without the math, suffice it say that if the load is faster than the generation, watch out.

What does this mean to the market operator? If the market operator man-ages to estimate the load elasticity with reasonable accuracy and clears the price anticipating the price response, then all is well. If load elasticity is ignored, then there can be problems depending upon a host of factors. So the market operator will need short-term and day-ahead load forecasting that incorporates the effects of load elasticity.

One path to being able to estimate elasticity is to gather data from all those price-responsive loads, a formidable task even on the optimistic assumption that all consumers know their price elastici-ties in advance. Another approach is for an aggregator to capture all this informa-tion and pass it on to the market operator. This, however, runs counter to the very idea of autonomous price responsive load and leaves the aggregator with the fore-cast risk.

Yet another solution is for the mar-ket operator to invest in developing big data analytics and data bases to forecast demand elasticity. That is a topic for an-other issue of the newsletter.

ContributorDr. Ralph D. Masiello, a member of

the National Academy of Engineering, an IEEE Smart Grid Technical Expert and an IEEE Life Fellow, is DNV GLs Innovation Director and Senior Vice President. He has served as chairman of the IEEE Power Systems Engineering Committee and serves now on the edito-rial board of the IEEE Power and Energy Magazine. In 2009 he received the IEEE PES Charles Concordia Power Systems Engineering Award. He earned his B.S., M.S. and Ph.D. in electrical engineer-ing from the Massachusetts Institute of Technology, where he worked on the very early applications of modern control and estimation theory of power systems.

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TRANSMISSION


For most Americans, President Obamas mention of a self-healing grid was probably the first they had ever heard about a power system that could identify and fix its own problems, without direct human intervention. But the concept of a self-healing grid goes back twenty years and by now is well developed.

At one point in his 2013 State of the Union address, President Obama aroused excitement and also some confusion re-garding a self-healing grid.

What the president said was: Amer-icas energy sector is just one part of an aging infrastructure badly in need of re-pair. Ask any CEO where theyd rather locate and hire: a country with deterio-rating roads and bridges, or one with high-speed rail and internet; high-tech schools and self-healing power grids?

Since the presidents speech, I have been asked the following questions:

What is a self-healing infrastructure?

A self-healing grid uses digital compo-nents and real-time se-cure communications technologies installed throughout to monitor its electrical character-istics at all times and constantly tune itself so it operates at an opti-mum state. It has the in-

telligence to constantly look for potential problems caused by storms, catastrophes, human error or even sabotage. It will re-act to real or potential abnormali-ties within a fraction of a second, just as a military fighter jet reconfigures itself to stay aloft af-ter it is damaged. The self-healing grid isolates prob-lems immediately as they occur, be-fore they cascade into major blackouts, and reorganizes the grid and reroutes energy trans-missions so services continue for all customers while the problem is physi-cally repaired by line crews.

A self-healing smarter grid can pro-vide a number of benefits that lead to a more stable and efficient system. Three

of its primary functions include: real-time moni-toring and reaction, which allows the sys-tem to constantly tune itself to an optimal state; anticipation, which en-ables the system to auto-matically look for prob-lems that could trigger larger disturbances; and rapid isolation, which allows the system to iso-late parts of the network that experience failure

from the rest of the system, to avoid the spread of disruption and enable a more rapid restoration.

As a result of these functions, a self-healing smart grid

system is able to re-duce power outages

and minimize their length when they do occur. The smart grid is able to detect abnormal signals, make adaptive re-

configurations and isolate disturbances,

eliminating or minimiz-ing electrical disturbances

during storms or other catastrophes. And, because the sy stem is self-heal-ing, it has an end-to-end resilience that detects and overrides human errors that result in some of the power outages, such as when a worker error left millions of California residents without electricity in September 2011.

Beyond managing power disturbanc-es, a smart grid system has the ability to measure how and when consumers use the most power. This information allows utility providers to charge consumers variable rates for energy based upon sup-ply and demand. Ultimately, this variable rate will incentivize consumers to shift their heavy use of electricity to times of the day when demand is low and will contribute to a healthier environment by helping consumers better manage and more efficiently use energy.

The Self-healing Grid: A Concept Two Decades in the MakingWritten by Massoud Amin

Transmission Automation

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A self-healing smarter grid can provide a number of benefits that lead to a more stable and efficient system.

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How can we set about building a self-healing grid?

To transform our current infrastruc-ture into a self-healing smart grid, sev-eral technologies must be deployed and integrated.

The ideal smart grid system consists of microgrids, which are small, mostly self-sufficient power systems, and a stronger, smarter high-voltage power grid, which serves as the backbone of the overall system. Where do we begin?

The first step is to build a processor into each switch, circuit breaker, trans-former and busbar, which are the huge conductors that transport electricity from generators. The processors will allow transmission lines to securely commu-nicate with each other and monitor their individual pieces of the grid.

From there, the millions of electro-mechanical switches currently in use will need to be replaced with solid-state, power-electronic circuits to handle the highest transmission voltages of 345 kilo -volts and beyond. This upgrade from analog to secure digital will allow the entire network to be digitally controlled, making the smart grids key functions of real-time self-monitoring and self-heal-ing possible.

Upgrading the grid infrastructure for self-healing capabilities requires replac-ing traditional analog technologies with digital components, software proces-sors and power electronics technologies. These must be installed throughout a system so it can be digitally controlled, which is the key ingredient to a self-mon-itoring and self-healing grid.

Does the smart grid need to have a self-healing infrastructure?

It needs a self-healing infrastructure to ensure it can continue to operate reli-ably for businesses and consumers who depend on it. A smart grid that is overlaid with the various sensors, communica-tions, automation and control features that allow it to deal with unforeseen events and minimize their impacts will be resilient and secure.

As I mentioned previously, the annual business losses in the U.S. from electri-cal failures average about $100 billion. Much of this is from short power inter-ruptions. On any day in the U.S., about a half million people are with-out power for two or more hours.

Not only can a self-healing grid avoid or minimize blackouts and associated costs, it can minimize the impacts of deliberate attempts by terrorists or others to sabotage the power grid. Its ability to seam-lessly maintain services under all of these types of conditions makes our country more secure. And overall, it improves the quality of electricity services for end users.

Where did the concept of a self-healing grid come from?

It was first formu-lated in the context of the Complex In-teractive Networks/Systems Initiative (CIN/SI), which was launched as a joint project of the Electric Power Research Institute and the U.S. Department of Defense in 1998, which involved six university research consortia, com-prised of 240 graduate students and 108 professors in 28 U.S. Universities along with 52 utilities and ISOs and the U.S. DoD, to address security and re-liability challenges posed by intercon-nected and complex critical infrastruc-tures. The key goal was to develop new tools and techniques to enable large national infrastructures to self-heal in response to threats, material failures and other destabilizers. Among the deliverables was the development and deployment of layers of secure sens-ing, high-confidence communications

and automation that enabled a smart gridan integrated, self-healing and electronically controlled secure and resilient power system.

ContributorMassoud Amin,

a senior member of IEEE, Chairman of the IEEE Smart Grid, a fellow of ASME, Chair-man of the Texas RE, an independent Direc-tor of the MRO, holds the Honeywell/H.W. Sweatt Chair in Tech-nological Leadership at the University of Min-nesota. He directs the universitys Technologi-cal Leadership Institute (TLI), is a University Distinguished Teaching Professor and professor of electrical and com-puter engineering. He received a B.S. degree with honors and the M.S. degree in electri-cal and computer engi-neering from the Uni-

versity of Massachusetts-Amherst, and the M.S. degree and the D.Sc. degree in systems science and mathematics from Washington University in St. Louis, Mis-souri. Before joining the University of Minnesota in 2003, he held positions of increasing responsibility at the Electric Power Research Institute (EPRI) in Palo Alto. After 9/11, he directed EPRIs In-frastructure Security R&D and served as area manager for Infrastructure Se-curity & Protection, Grid Operations/Planning, and Energy Markets. Prior to that, he served as manager of mathemat-ics and information sciences, leading the development of more than 24 technolo-gies that transferred to industry, and pio-neered R&D in self-healing infrastruc-tures and smart grids.

Not only can a self-healing grid avoid or minimize blackouts and associated costs, it can minimize the impacts of deliberate attempts by terrorists or others to sabotage the power grid.

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BULK GENERATION

G iven changes in how people are using electricity, is an AC-only electrical system still the right option for a residence of the future? Con-version losses already are growing with wide use of consumer electronics, and they will get bigger still as photovoltaic and car-charging systems evolve. This is why experts are starting to seriously consider the prospect of hybrid AC/DC residential electrical systems.

According to the Energy Information Agency (EIA), the fastest growing por-tion of residential electricity use is con-sumer electronics and small appliances. In 1993, the EIA did not even bother to measure the consumption in either cat-egory; eight years later it counted over a dozen types of devices that fit in this category. By 2013, when a group of IEEE members audited their houses to get a snapshot of what they had, the list of cat-egories expanded to over 50 small appli-ances and consumer electronics devices.

These devices primarily run on DC power. Even with improvements in pow-er supplies, many of these devices have a conversion efficiency of no better than 80 percent and some low-end devices have efficiencies as low as 65 percent in con-verting power. Such devices now account for between 15 and 30 percent of a resi-dences consumption, depending on de-mographics, country and weather zone.

In terms of electricity used, in 2012 the average U.S. home consumed 11,252 Kilowatt-hours (kWh). Assuming the av-erage home used 20 percent of electric-ity for these devices, that translates into

2,250 kWh consumed by each residence. With an average efficiency of power con-version of 75 percent, that means 562 kWh were lost in power conversion in an average home.

If this were the only loss from power conversion, it might be ignored, but this is not the case. On the pro-duction side of the equation, residen-tial photovoltaic systems are com-ing into wider use, producing DC power that also involves sig-nificant losses. The smallest PV system typically installed has a capacity of about 1 kilowatt (KW) and produces 5250 kWh annually.

According to the National Renewable Energy Labs (NREL) PVWatts tool, the losses associated with converting DC to AC in a typical system come to 23 per-cent, or 241 kWh. The average size in-stalled is 5 KW, so the annual conversion loss amounts to 1,200 kWh for the aver-age system.

Then there are electric vehicles, a third major DC element. According to GM, the Chevy Volt needs to have 10.4 kWh fed into the battery for a full charge because of losses and battery condition-ing, doing that actually requires 12.9 kWh of electricity. Assuming the Volt is driven the 35-miles-a-day national average, which is roughly the number of miles the car gets per charge, it will con-

sume 4,700 kWh of electricity per year, of which 912 kWh is lost in conversion and charging the batteries.

So, if current trends continue, more renewables, electric vehicles and

consumer electronics will be installed, leading

to growing conver-sion losses. Today, a home with photo-voltaic and electric vehicles will see conversion losses of 2,674 kWh annually

on a consumption of 15,952 kWh, or 16 per-

cent. This means more electricity is lost within the

home than in delivering that homes power across the distribution and trans-mission grids.

While there are still few homes with photovoltaic and electric vehicles, the question is, should conversion of DC to AC and AC to DC continue in the fu-ture? Should a resident be able to plug a DC-based device into a DC outlet and an AC-based device into an AC outlet? Or should we continue to make all the con-versions? In 2004, CEATI published one of the first reports that asked the question of what it would take to mix AC and DC on the same distribution system. Over the last seven years some efforts have been made in the laboratory to under-stand what it would take to mix, either on the distribution system or just within the home, AC and DC power. Addition-ally the impact of different outlets for AC

Is DCs Place in the Home?Written by Doug Houseman

Generation Advancements

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and DC power has been discussed. This is not a trivial problem; safety of the user, breakers, switches, reactive power and other issues all need to be sorted out. In short, it is a big change that will take ma-jor research to sort out. IEEE will start a formal effort this spring to look at the challenges of DC power in the home and potentially mixing AC and DC there.

A small group of IEEE members working with the IEEE Power & En-ergy Society (PES) and IEEE Standards Association (SA) will launch a work-ing group from the IEEE PES General Meeting. This working group may be the core for the potential revolution. Right now no one knows whether it will be cost effective to mix AC and DC in a household, how fast EV use will growrecent history is not very encouraging or how fast renewables will be installed. Another uncertainty concerns penetra-tion of battery storage, which may be installed to back up building-based re-newable energy systems.

What is completely unknown at this point is what the impact of this will be

on the implementation of smart grid and the overall design of distribution systems in the future. Is this an important part of the future, a flash in the pan, a special-ized system for high-end consumers, or completely nuts?

With 132,000,000 households in the United States, losses from conver-sion are more than 70 terawatt hours (billion kWh) annually for small appli-ances and consumer electronics. These losses equate to 700 trillion BTUs of primary energy that is lost with these conversions in the United States alone. As the rest of the world catches up with the US in using electricity for en-tertainment (there are over 1.4 billion more households in the world), what is the right thing to do? Without research and engineering, we dont have the ba-sis to make a good decision. The ball is clearly in our court to decide. Wont you join the effort?

ContributorDoug Houseman, an IEEE senior

Member, is Vice President for Tech-

nical Innovation at EnerNex and has served as Chief Technology Officer at Capgemini. With extensive experi-ence in the energy and utility indus-try, he has been involved in projects in more than 30 countries. He was designated part of the World Genera-tion Class of 2007, one of 30 people in the global utility and energy indus-try so named by World-Generation Magazine and the World Generation Forum. He was the lead investigator on one of the largest studies on the future of distribution companies pub-lished by CEATI, and for the last five years has been working with more than 100 utilities and manufacturers, 50 governments, and five interna-tional agencies/NGOs on a wide range of industry issues. He was one of the primary authors of the IEEE Power & Energy Societys GridVision 2050. He obtained his bachelors degree at the U.S. Naval Academy and did graduate work at the University of Michigan.

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NON-BULK GENERATION

The paradigm of future power systems described here offers a method of standardizing the inter-face of all electrical supplies, including conventional power plants and new add-ons, such as wind/solar farms, electrical vehicles and energy storage systems, and a majority of loads with the transmission and distribution networks, by exploiting the synchronisation principle of synchro-nous machines. This model opens the prospect of achieving completely autono-mous operation of power systems.

Due to civilisation and economic de-velopment, demand for electricity is con-stantly growing, leading directly to supply issues and environmental cri-sis. Large-scale utilisa-tion of renewables is regarded as a promis-ing means of lessening those problems, and as a result, power systems are going through a paradigm change from centralised generation to distributed genera-tion, and further on to smart grids.

In current power systems, the generation of electricity is domi-nated by centralised fa-cilities. The lions share of power is provided in China, for example, by just 1500 or so gen-

erators rated at 200 MW and above. It is relatively easy to regulate a limited num-ber of generators in a power system so as to achieve system stability and to meet the balance between generation and demand.

When a large num-ber of new add-onswind or solar farms, electrical vehicles and energy storage systemsare inte-grated into a power system, the number of players on the sup-

ply side will increase considerably. More-over, a lot of players on the demand side are ex-pected to actively take part in the system regu-lation as well. Hence, the total number of active players in a power sys-tem could easily reach millions, hundreds of millions or even billions. How to make sure that all these players are able to work together to main-tain the system stability is a great challenge. A simple mechanism is needed to facilitate the organic growth and au-tonomous operation of power systems.

Adding a communication and infor-mation system into power systems would help: hence the birth of smart grids, pow-

er systems with communication and information systems added

to operate in parallel. With the introduction

of smart power, sys-tems will become more efficient and more resilient in the face of threats, and friendlier to

the environment. Naturally, the added

communication systems are expected to provide the

infrastructure needed for all power system players to work together, even at the low-level controls. This standard scenario, however, brings with it serious concerns about reliability. If the com-munication system breaks down then the whole power system could crash. More-over, when the number of players reaches a certain level, how to manage the com-munication system is itself a challenge.

A vision of next-generation smart grids I have devised would allow all active players to communicate with each other at the bottom level of the power system, without relying on a communication net-work. The function of communication is achieved through control, that is to say, the measurement of local voltage or frequency and the execution of control algorithms, based on the underlying synchronisation mechanism of synchronous machines. As

How to Achieve Completely Autonomous Power in the Next Generation of Smart GridsWritten by Qing-Chang Zhong

Distributed Energy Resources

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Due to civilisation and economic development, demand for electricity is constantly growing, leading directly to supply issues and environmental crisis.

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