Smart Grid E-Book

James Momoh

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 317

Veröffentlichungsjahr: 2012

Beschreibung

The book is written as primer hand book for addressing the fundamentals of smart grid. It provides the working definition the functions, the design criteria and the tools and techniques and technology needed for building smart grid. The book is needed to provide a working guideline in the design, analysis and development of Smart Grid. It incorporates all the essential factors of Smart Grid appropriate for enabling the performance and capability of the power system. There are no comparable books which provide information on the "how to" of the design and analysis. The book provides a fundamental discussion on the motivation for the smart grid development, the working definition and the tools for analysis and development of the Smart Grid. Standards and requirements needed for designing new devices, systems and products are discussed; the automation and computational techniques need to ensure that the Smart Grid guarantees adaptability, foresight alongside capability of handling new systems and components are discussed. The interoperability of different renewable energy sources are included to ensure that there will be minimum changes in the existing legacy system. Overall the book evaluates different options of computational intelligence, communication technology and decision support system to design various aspects of Smart Grid. Strategies for demonstration of Smart Grid schemes on selected problems are presented.

Leseprobe

Table of Contents

Cover

IEEE Press

Title page

Copyright page

PREFACE

1 SMART GRID ARCHITECTURAL DESIGNS

1.1 INTRODUCTION

1.2 TODAY’S GRID VERSUS THE SMART GRID

1.3 ENERGY INDEPENDENCE AND SECURITY ACT OF 2007: RATIONALE FOR THE SMART GRID

1.4 COMPUTATIONAL INTELLIGENCE

1.5 POWER SYSTEM ENHANCEMENT

1.6 COMMUNICATION AND STANDARDS

1.7 ENVIRONMENT AND ECONOMICS

1.8 OUTLINE OF THE BOOK

1.9 GENERAL VIEW OF THE SMART GRID MARKET DRIVERS

1.10 STAKEHOLDER ROLES AND FUNCTION

1.11 WORKING DEFINITION OF THE SMART GRID BASED ON PERFORMANCE MEASURES

1.12 REPRESENTATIVE ARCHITECTURE

1.13 FUNCTIONS OF SMART GRID COMPONENTS

1.14 SUMMARY

2 SMART GRID COMMUNICATIONS AND MEASUREMENT TECHNOLOGY

2.1 COMMUNICATION AND MEASUREMENT

2.2 MONITORING, PMU, SMART METERS, AND MEASUREMENTS TECHNOLOGIES

2.3 GIS AND GOOGLE MAPPING TOOLS

2.4 MULTIAGENT SYSTEMS (MAS) TECHNOLOGY

2.5 MICROGRID AND SMART GRID COMPARISON

2.6 SUMMARY

3 PERFORMANCE ANALYSIS TOOLS FOR SMART GRID DESIGN

3.1 INTRODUCTION TO LOAD FLOW STUDIES

3.2 CHALLENGES TO LOAD FLOW IN SMART GRID AND WEAKNESSES OF THE PRESENT LOAD FLOW METHODS

3.3 LOAD FLOW STATE OF THE ART: CLASSICAL, EXTENDED FORMULATIONS, AND ALGORITHMS

3.4 CONGESTION MANAGEMENT EFFECT

3.5 LOAD FLOW FOR SMART GRID DESIGN

3.6 DSOPF APPLICATION TO THE SMART GRID

3.7 STATIC SECURITY ASSESSMENT (SSA) AND CONTINGENCIES

3.8 CONTINGENCIES AND THEIR CLASSIFICATION

3.9 CONTINGENCY STUDIES FOR THE SMART GRID

3.10 SUMMARY

4 STABILITY ANALYSIS TOOLS FOR SMART GRID

4.1 INTRODUCTION TO STABILITY

4.2 STRENGTHS AND WEAKNESSES OF EXISTING VOLTAGE STABILITY ANALYSIS TOOLS

4.3 VOLTAGE STABILITY ASSESSMENT

4.4 VOLTAGE STABILITY ASSESSMENT TECHNIQUES

4.5 VOLTAGE STABILITY INDEXING

4.6 ANALYSIS TECHNIQUES FOR STEADY-STATE VOLTAGE STABILITY STUDIES

4.7 APPLICATION AND IMPLEMENTATION PLAN OF VOLTAGE STABILITY

4.8 OPTIMIZING STABILITY CONSTRAINT THROUGH PREVENTIVE CONTROL OF VOLTAGE STABILITY

4.9 ANGLE STABILITY ASSESSMENT

4.10 STATE ESTIMATION

5 COMPUTATIONAL TOOLS FOR SMART GRID DESIGN

5.1 INTRODUCTION TO COMPUTATIONAL TOOLS

5.2 DECISION SUPPORT TOOLS (DS)

5.3 OPTIMIZATION TECHNIQUES

5.4 CLASSICAL OPTIMIZATION METHOD

5.5 HEURISTIC OPTIMIZATION

5.6 EVOLUTIONARY COMPUTATIONAL TECHNIQUES

5.7 ADAPTIVE DYNAMIC PROGRAMMING TECHNIQUES

5.8 PARETO METHODS

5.9 HYBRIDIZING OPTIMIZATION TECHNIQUES AND APPLICATIONS TO THE SMART GRID

5.10 COMPUTATIONAL CHALLENGES

5.11 SUMMARY

6 PATHWAY FOR DESIGNING SMART GRID

6.1 INTRODUCTION TO SMART GRID PATHWAY DESIGN

6.2 BARRIERS AND SOLUTIONS TO SMART GRID DEVELOPMENT

6.3 SOLUTION PATHWAYS FOR DESIGNING SMART GRID USING ADVANCED OPTIMIZATION AND CONTROL TECHNIQUES FOR SELECTION FUNCTIONS

6.4 GENERAL LEVEL AUTOMATION

6.5 BULK POWER SYSTEMS AUTOMATION OF THE SMART GRID AT TRANSMISSION LEVEL

6.6 DISTRIBUTION SYSTEM AUTOMATION REQUIREMENT OF THE POWER GRID

6.7 END USER/APPLIANCE LEVEL OF THE SMART GRID

6.8 APPLICATIONS FOR ADAPTIVE CONTROL AND OPTIMIZATION

6.9 SUMMARY

7 RENEWABLE ENERGY AND STORAGE

7.1 RENEWABLE ENERGY RESOURCES

7.2 SUSTAINABLE ENERGY OPTIONS FOR THE SMART GRID

7.3 PENETRATION AND VARIABILITY ISSUES ASSOCIATED WITH SUSTAINABLE ENERGY TECHNOLOGY

7.4 DEMAND RESPONSE ISSUES

7.5 ELECTRIC VEHICLES AND PLUG-IN HYBRIDS

7.6 PHEV TECHNOLOGY

7.7 ENVIRONMENTAL IMPLICATIONS

7.8 STORAGE TECHNOLOGIES

7.9 TAX CREDITS

7.10 SUMMARY

8 INTEROPERABILITY, STANDARDS, AND CYBER SECURITY

8.1 INTRODUCTION

8.2 INTEROPERABILITY

8.3 STANDARDS

8.4 SMART GRID CYBER SECURITY

8.5 CYBER SECURITY AND POSSIBLE OPERATION FOR IMPROVING METHODOLOGY FOR OTHER USERS

8.6 SUMMARY

9 RESEARCH, EDUCATION, AND TRAINING FOR THE SMART GRID

9.1 INTRODUCTION

9.2 RESEARCH AREAS FOR SMART GRID DEVELOPMENT

9.3 RESEARCH ACTIVITIES IN THE SMART GRID

9.4 MULTIDISCIPLINARY RESEARCH ACTIVITIES

9.5 SMART GRID EDUCATION

9.6 TRAINING AND PROFESSIONAL DEVELOPMENT

9.7 SUMMARY

10 CASE STUDIES AND TESTBEDS FOR THE SMART GRID

10.1 INTRODUCTION

10.2 DEMONSTRATION PROJECTS

10.3 ADVANCED METERING

10.4 MICROGRID WITH RENEWABLE ENERGY

10.5 POWER SYSTEM UNIT COMMITMENT (UC) PROBLEM

10.6 ADP FOR OPTIMAL NETWORK RECONFIGURATION IN DISTRIBUTION AUTOMATION

10.7 CASE STUDY OF RER INTEGRATION

10.8 TESTBEDS AND BENCHMARK SYSTEMS

10.9 CHALLENGES OF SMART TRANSMISSION

10.10 BENEFITS OF SMART TRANSMISSION

10.11 SUMMARY

11 EPILOGUE

Index

IEEE Press Series on Power Engineering

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Copyright © 2012 by the Institute of Electrical and Electronics Engineers.

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Library of Congress Cataloging-in-Publication Data:

Momoh, James A., 1950-

 Smart grid : fundamentals of design and analysis / James Momoh.

p. cm.

 ISBN 978-0-470-88939-8 (hardback)

 ISBN 978-1-118-15608-7 (epdf)

 ISBN 978-1-118-15609-4 (mobi)

 ISBN 978-1-118-15610-0 (epub)

 1. Electric power distribution–Automation. I. Title.

 TK3226.M588 2012

 333.793'2–dc23

2011024774

PREFACE

The term “smart grid” defines a self-healing network equipped with dynamic optimization techniques that use real-time measurements to minimize network losses, maintain voltage levels, increase reliability, and improve asset management. The operational data collected by the smart grid and its sub-systems will allow system operators to rapidly identify the best strategy to secure against attacks, vulnerability, and so on, caused by various contingencies. However, the smart grid first depends upon identifying and researching key performance measures, designing and testing appropriate tools, and developing the proper education curriculum to equip current and future personnel with the knowledge and skills for deployment of this highly advanced system.

The objective of this book is to equip readers with a working knowledge of fundamentals, design tools, and current research, and the critical issues in the development and deployment of the smart grid. The material presented in its eleven chapters is an outgrowth of numerous lectures, conferences, research efforts, and academic and industry debate on how to modernize the grid both in the United States and worldwide. For example, Chapter 3 discusses the optimization tools suited to managing the randomness, adaptive nature, and predictive concerns of an electric grid. The general purpose Optimal Power Flow, which takes advantage of a learning algorithm and is capable of solving the optimization scheme needed for the generation, transmission, distribution, demand response, reconfiguration, and the automation functions based on real-time measurements, is explained in detail.

I am grateful to several people for their help during the course of writing this book. I acknowledge Keisha D’Arnaud, a dedicated recent graduate student at the Center for Energy Systems and Control, for her perseverance and support in the several iterations needed to design the text for a general audience. I thank David Owens, Senior Executive Vice President of the Edison Electric Institute, and Dr. Paul Werbos, Program Director of the Electrical, Communication and Cyber Systems (ECCS), National Science Foundation (NSF), for encouraging and supporting my interest in unifying my knowledge of systems through computational intelligence to address complex power system problems where traditional techniques have failed. Their support was especially valuable during my stint at NSF as a Program Director in ECCS from 2001 to 2004. I am also grateful for the Small Grant Expository Research award granted by the NSF to develop the first generation of Dynamic Stochastic Optimal Power flow, a general purpose tool for use in smart grid design and development.

I thank my family for their encouragement and support. I am grateful to my students and colleagues at the Center for Energy Systems and Control, who, as audience and enthusiasts, let me test and refine my ideas in the smart grid, and also for honorary invited presentations to top utility executive management in addressing the emergence of the smart grid across the country. All these exposures rekindled my interest in the design and development of the grid for the future.

JAMES MOMOH

1

SMART GRID ARCHITECTURAL DESIGNS

1.1 INTRODUCTION

Today’s electric grid was designed to operate as a vertical structure consisting of generation, transmission, and distribution and supported with controls and devices to maintain reliability, stability, and efficiency. However, system operators are now facing new challenges including the penetration of RER in the legacy system, rapid technological change, and different types of market players and end users. The next iteration, the smart grid, will be equipped with communication support schemes and real-time measurement techniques to enhance resiliency and forecasting as well as to protect against internal and external threats. The design framework of the smart grid is based upon unbundling and restructuring the power sector and optimizing its assets. The new grid will be capable of:

Handling uncertainties in schedules and power transfers across regionsAccommodating renewablesOptimizing the transfer capability of the transmission and distribution networks and meeting the demand for increased quality and reliable supplyManaging and resolving unpredictable events and uncertainties in operations and planning more aggressively.

1.2 TODAY’S GRID VERSUS THE SMART GRID

As mentioned, several factors contribute to the inability of today’s grid to efficiently meet the demand for reliable power supply. Table 1.1 compares the characteristics of today’s grid with the preferred characteristics of the smart grid.

TABLE 1.1. Comparison of Today’s Grid vs. Smart Grid [4]

Preferred CharacteristicsToday’s GridSmart GridActive Consumer ParticipationConsumers are uninformed and do not participateInformed, involved consumers—demand response and distributed energy resourcesAccommodation of all generation and storage optionsDominated by central generation—many obstacles exist for distributed energy resources interconnectionMany distributed energy resources with plug-and-play convenience focus on renewablesNew products, services, and marketsLimited, poorly integrated wholesale markets; limited opportunities for consumersMature, well-integrated wholesale markets; growth of new electricity markets for consumersProvision of power quality for the digital economyFocus on outages—slow response to power quality issuesPower quality a priority with a variety of quality/price options—rapid resolution of issuesOptimization of assets and operates efficientlyLittle integration of operational data with asset management—business process silosGreatly expanded data acquisition of grid parameters; focus on prevention, minimizing impact to consumersAnticipating responses to system disturbances (self-healing)Responds to prevent further damage; focus on protecting assets following a faultAutomatically detects and responds to problems; focus on prevention, minimizing impact to consumersResiliency against cyber attack and natural disastersVulnerable to malicious acts of terror and natural disasters; slow responseResilient to cyber attack and natural disasters; rapid restoration capabilities

1.3 ENERGY INDEPENDENCE AND SECURITY ACT OF 2007: RATIONALE FOR THE SMART GRID

The Energy Independence and Security Act of 2007 (EISA) signed into law by President George W. Bush vividly depicts a smart grid that can predict, adapt, and reconfigure itself efficiently and reliably. The objective of the modernization of the U.S. grid as outlined in the Act is to maintain a reliable and secure electricity [2] infrastructure that will meet future demand growth. Figure 1.1 illustrates the features needed to facilitate the development of an energy-efficient, reliable system.

Figure 1.1. Rationale for the smart grid.

The Act established a Smart Grid Task Force, whose mission is “to insure awareness, coordination and integration of the diverse activities of the DoE Office and elsewhere in the Federal Government related to smart-grid technologies and practices” [1]. The task force’s activities include research and development; development of widely accepted standards and protocols; the relationship of smart grid technologies and practices to electric utility regulation; the relationship of smart grid technologies and practices to infrastructure development, system reliability, and security; and the relationship of smart grid technologies and practices to other facets of electricity supply, demand, transmission, distribution, and policy. In response to the legislation, the U.S. research and education community is actively engaged in:

1. Smart grid research and development program

2. Development of widely accepted smart grid standards and protection

3. Development of infrastructure to enable smart grid deployment

4. Certainty of system reliability and security

5. Policy and motivation to encourage smart grid technology support for generation, transmission and distribution

As Figure 1.2 shows, there are five key aspects of smart grid development and deployment.

Figure 1.2. Five key aspects of smart grid development.

1.4 COMPUTATIONAL INTELLIGENCE

Computational intelligence is the term used to describe the advanced analytical tools needed to optimize the bulk power network. The toolbox will include heuristic, evolution programming, decision support tools, and adaptive optimization techniques.

1.5 POWER SYSTEM ENHANCEMENT

Policy-makers assume that greatly expanded use of renewable energy [4,5] resources in the United States will help to offset the impacts of carbon emissions from thermal and fossil energy, meet demand uncertainty, and to some extent, increase reliability of delivery.

1.6 COMMUNICATION AND STANDARDS

Since planning horizons can be short as an hour ahead, the smart grid’s advanced automations will generate vast amounts of operational data in a rapid decision-making environment. New algorithms will help it become adaptive and capable of predicting with foresight. In turn, new rules will be needed for managing, operating, and marketing networks.

1.7 ENVIRONMENT AND ECONOMICS

Based on these desired features, an assessment of the differences in the characteristics of the present power grid and the proposed smart grid is needed to highlight characteristics of the grid and the challenges. When fully developed the smart grid system will allow customer involvement, enhance generation and transmission with tools to allow minimization of system vulnerability, resiliency, reliability, adequacy and power quality. The training tools and capacity development to manage and operate the grids and hence crate new job opportunities is part of the desired goals of the smart grid evolution which will be tested using test-bed. To achieve the rapid deployment of the grids test bed and research centers need to work across disciplines to build the first generation of smart grid.

By focusing on security controls rather than individual vulnerabilities and threats, utility companies and smart-grid technology vendors can remediate the root causes that lead to vulnerabilities. However, security controls are more difficult and sometimes impossible to add to an existing system, and ideally should be integrated from the beginning to minimize implementation issues. The operating effectiveness of the implemented security controls-base will be assessed routinely to protect the smart grid against evolving threats.

1.8 OUTLINE OF THE BOOK

This book is organized into 10 chapters. Following this chapter’s introduction, Chapter 2 presents the smart grid concept, fundamentals, working definitions, and system architecture. Chapter 3 describes the tools using load flow concepts, optimal power flows, and contingencies and Chapter 4 describes those using voltage stability, angle stability, and state estimation. Chapter 5 evaluates the computational intelligence approach as a feature of the smart grid. Chapter 6 explains the pathways design of the smart grid using general purpose dynamic stochastic optimization. Chapter 7 reviews renewable supply and the related issues of variability and probability distribution functions, followed by a discussion of storage technologies, capabilities, and configurations. Demand side managemen (DSM) and demand response, climate change, and tax credits are highlighted for the purpose of evaluating the economic and environmental benefit of renewable energy sources. Chapter 8 discusses the importance of developing national standards, followed by a discussion of interoperability such that the new technologies can easily be adapted to the legacy system without violating operational constraints. The chapter also discusses cyber security to protect both RER and communication infrastructure. Chapter 9 explains the significant research and employment training for attaining full performance and economic benefits of the new technology. Chapter 10 discusses case studies on smart grid development and testbeds to aid deployment. The chapter outlines the grand challenges facing researchers and policy-makers before the smart grid can be fully deployed, and calls for investment and multidisciplinary collaboration. Figure 1.3 is a schematic of the chapters.

Figure 1.3. Schematic of chapters.

1.9 GENERAL VIEW OF THE SMART GRID MARKET DRIVERS

To improve efficiency and reliability, several market drivers and new opportunities suggest that the smart grid must:

1. Satisfy the need for increased integration of digital systems for increased efficiency of the power system. In the restructured environment, the deregulated electric utility industry allows a renovation of the market to be based on system constraints and the seasonal and daily fluctuations in demand. Competitive markets increase the shipment of power between regions, which further strains today’s aging grid and requires updated, real-time controls.

2. Handle grid congestion, increase customer participation, and reduce uncertainty for investment. This requires the enhancement of the grid’s capability to handle demand reliably.

3. Seamlessly integrate renewable energy systems (RES) and distributed generation. The drastic increase in the integration of cost-competitive distributed generation technologies affects the power system.

In addition to system operators and policy-makers, stakeholders are contributing to the development of the smart grid. Their specific contributions and conceptual understanding of the aspects to be undertaken are discussed below.

1.10 STAKEHOLDER ROLES AND FUNCTION

As in the legacy system, critical attention must be paid to the identification of the stakeholders and how they function in the grid’s development. Stakeholders range from utility and energy producers to consumers, policy-makers, technology providers, and researchers. An important part of the realization of the smart grid is the complete buy-in or involvement of all stakeholders.

Policy-makers are the federal and state regulators responsible for ensuring the cohesiveness of policies for modernization efforts and mediating the needs of all parties. The primary benefit of smart grid development to these stakeholders concerns the mitigation of energy prices, reduced dependence on foreign oil, increased efficiency, and reliability of power supply. Figure 1.4 shows the categories of stakeholders.

Figure 1.4. Stakeholders and their functions.

Other participants in the development of the smart grid include government agencies, manufacturers, and research institutes. The federal Department of Energy’s (DOE) National Renewable Energy Laboratory (NREL) and state agencies such as the California Energy Commission and the New York State Energy Research and Development Authority are among the pioneers. In the monograph, “The Smart Grid: An Introduction,” the DOE discusses the nature, challenges, opportunities, and necessity for smart grid implementation. It defines the smart grid as technology which “makes this transformation of the electric industry possible by bringing the philosophies, concepts and technologies that enabled the internet to the utility and the electric grid and enables the grid modernization” [1]. The characteristics of the smart grid are two-way digital communication, plug-and-play capabilities, advanced metering infrastructure for integrating customers, facilities for increased customer involvement, interoperability based on standards, and low-cost communication and electronics.

Additional features identified include integration and advancement of grid visualization technology to provide wide-area grid awareness, integrating real-time sensor data, weather information, and grid modeling with geographical information [1].

However, the DOE’s definitions in our opinion do not provide measures for addressing uncertainty, predictivity, and foresight. Another federal entity, the Federal Energy Regulatory Commission (FERC), has mandated the development of:

1. Cyber Security: require NIST define standard and protocol consistent with the overarching cyber security and reliability requirements of the Energy Independence and Security Act (EISA) and the FERC Reliability Standards.

2. Intersystem Communications: Identify standards for common information models for communication among all elements of the bulk power system regional market operators, utilities, demand response aggregators, and customers

3. Wide-Area Situational Awareness: Ensure that operators of the nation’s bulk power system have the equipment that gives them a complete view of their systems so they can monitor and operate their systems.

4. Coordination of the bulk power systems with new and emerging technologies: Identify standards development that help to accommodate the introduction and expansion of renewable resources, demand response, and electricity storage to address several bulk power system challenges. Also identify standards development that help to accommodate another emerging technology, electric transportation.

1.10.1 Utilities

South California Edison (SCE) and other utility companies undertook to reinvent electrical metering. Vendors are migrated to an open standards–based advanced metering infrastructure. These contributions have led to the continual improvement of associated features such as customer service, energy conservation, and economic efficiency.

PEPCO Holdings has been working on an Advanced Metering Infrastructure (AMI). The technology is an integral component of the smart grid [5]. The features proposed include investment in and implementation of innovative, customer-focused technologies and initiatives for efficient energy management, increased pricing options and demand response, reduction of total energy cost and consumption, and reduction of the environmental impacts of electric power consumption.

1.10.2 Government Laboratory Demonstration Activities

Much of the fundamental thinking behind the smart grid concept arose from the DOE’s Pacific Northwest National Laboratory (PNNL) more than 20 years ago. In the middle 1980s researchers at PNNL were already designing first-generation data collection systems that were installed in more than 1000 buildings to monitor near real time electricity consumption for every appliance. PNNL developed a broad suite of analytical tools and technologies that resulted in better sensors, improved diagnostics, and enhanced equipment design and operation, from phasor measurement and control at the transmission level to grid-friendly appliances [2]. In January 2006, four years after its first presentation, PNNL unveiled the GridWise Initiative whose objective was the testing of new electric grid technologies [3]. This demonstration project involved 300 homeowners in Washington and Oregon.

The GridWise Alliance manages the GridWise Program in the DOE’s Office of Electricity and Energy Assurance. Members include Areva, GE, IBM, Schneider Electric; American Electric Power, Bonneville Power Administration, ConEd, the PJM Interconnection; Battelle, RDS, SAIC, Nexgen, and RockPort Capital Partners [2]. The GridWise Architecture Council [4], a primary advocate for the smart grid, promotes the benefits of improving interoperability between the automation systems needed to enable smart grid applications.

1.10.3 Power Systems Engineering Research Center (PSERC)

The Power Systems Engineering Research Center (PSERC) [6] consists of 13 universities and industrial collaborators involved in research aimed at solving grid problems using state-of-the-art technologies. The direction of PSERC is the development of new strategies, technologies, analytical capabilities, and computational tools for operating and planning practices that will support an adaptive, reliable, and stable power grid.

1.10.4 Research Institutes

The Electric Power Research Institute (EPRI) and university consortium groups have developed software architecture for smart grid development. These tools focus on the development of the grid’s technical framework through the integration of electricity systems, communications, and computer controls. The Intelligrid software from EPRI, an open-standard, requirements-based approach for integrating data networks and equipment, enables interoperability between products and systems. It provides methodology, tools, and recommendations for standards and technologies for utility use in planning, specifying, and procuring IT-based systems.

1.10.5 Technology Companies, Vendors, and Manufacturers

IBM is a major player in the provision of information technology (IT) equipment for the smart grid on a global level. In 2008, IBM was chosen to spearhead IT support and services for smart-grid energy-efficiency programs by American Electric Power, Michigan Gas and Electric, and Consumers Energy. IBM serves as the systems integrator for its GridSmart program that displays energy usage and participate in energy-efficiency program. Its Intelligent Power Grid is characterized by increased grid observability with modern data integration and analytics to support advanced grid operation and control, power delivery chain integration, and high-level utility strategic planning functions [7]. Some key characteristics of the Intelligent Power Grid are:

Grid equipment and assets contain or are monitored by intelligent IP-enabled devices (digital processors).Digital communication networks permit the intelligent devices to communicate securely with the utility enterprise and possibly with each other.Data from the intelligent devices and many other sources are consolidated to support the transformation of raw data into useful information through advanced analytics.Business intelligence and optimization tools provide advanced decision support at both the automatic and human supervisory level.

The data base and architecture consist of five major components: data sources, data transport, data integration, analytics, and optimization. In addition there are means for data distribution which includes publish-and-subscribe middleware, portals, and Web-based services [8].

CISCO has also contributed with its IP architecture. CISCO describes the smart grid as a data communication network integrated with the electrical grid that collects and analyzes data captured in near-real time about power transmission, distribution, and consumption. Predictive information and recommendations to stakeholders are developed based on the data for power management. Integration of the generation, transmission, distribution, and end user components is a critical feature.

There is no one acceptable or universal definition for the smart grid; rather it is function-selected. Below we give a working definition to encompass the key issues of stakeholders and developers.

1.11 WORKING DEFINITION OF THE SMART GRID BASED ON PERFORMANCE MEASURES

A working definition should include the following attributes:

Assess grid health in real timePredict behavior, anticipateAdapt to new environments like distributed resources and renewable energy resourcesHandle stochastic demand and respond to smart appliancesProvide self-correction, reconfiguration, and restorationHandle randomness of loads and market participants in real timeCreate more complex interactive behavior with intelligent devices, communication protocols, and standard and smart algorithms to improve smart communication and transportation systems.

In this environment, smart control strategies will handle congestion, instability, or reliability problems. The smart grid will be cyber-secure, resilient, and able to manage shock to ensure durability and reliability. Additional features include facilities for the integration of renewable and distribution resources, and obtaining information to and from renewable resources and plug-in hybrid vehicles. New interface technologies will make data flow patterns and information available to investors and entrepreneurs interested in creating goods and services.

Thus, the working definition becomes:

The smart grid is an advanced digital two-way power flow power system capable of self-healing, and adaptive, resilient, and sustainable, with foresight for prediction under different uncertainties. It is equipped for interoperability with present and future standards of components, devices, and systems that are cyber-secured against malicious attack.

It is enabled to perform with robust and affordable real-time measurements and enhanced communication technology for data/information transmission. It allows smart appliances and facilitates the deployment of advanced storage technologies including plug-in electric and hybrid vehicles and control options, and supports DSM and demand response schemes.

1.12 REPRESENTATIVE ARCHITECTURE

Several types of architecture have been proposed by the various bodies involved in smart grid development. We present two: one from the DOE and one illustrated by Figure 1.5, which shows how the DOE’s proposed smart grid divides into nine areas: transmission automation, system coordination situation assessment, system operations, distribution automation, renewable integration, energy efficiency, distributed generation and storage, demand participation signals and options, and smart appliances, PHEVs, and storage.

Figure 1.5. DOE representative architecture of the smart grid design (architecture 1).

Figure 1.6 shows how the second architectural framework is partitioned into subsystems with layers of intelligence and technology and new tools and innovations. It involves bulk power generation, transmission, distribution, and end user level of the electric power system. The function of each component is explained in the next section.

Figure 1.6. The intelligent grid (architecture 2).

1.13 FUNCTIONS OF SMART GRID COMPONENTS

For the generation level of the power system, smart enhancements will extend from the technologies used to improve the stability and reliability of the generation to intelligent controls and the generation mix consisting of renewable resources.

1.13.1 Smart Devices Interface Component

Smart devices for monitoring and control form part of the generation components’ real time information processes. These resources need to be seamlessly integrated in the operation of both centrally distributed and district energy systems.

1.13.2 Storage Component

Due to the variability of renewable energy and the disjoint between peak availability and peak consumption, it is important to find ways to store the generated energy for later use. Options for energy storage technologies include pumped hydro, advance batteries, flow batteries, compressed air, super-conducting magnetic energy storage, super-capacitors, and flywheels. Associated market mechanisms for handling renewable energy resources, distributed generation, environmental impact and pollution are other components necessary at the generation level.

Associated market mechanism for handling renewable energy resources, distributed generation, environmental impact and pollution has to be introduced in the design of smart grid component at the generation level.

1.13.3 Transmission Subsystem Component

The transmission system that interconnects all major substation and load centers is the backbone of an integrated power system. Efficiency and reliability at an affordable cost continue to be the ultimate aims of transmission planners and operators. Transmission lines must tolerate dynamic changes in load and contingency without service disruptions. To ensure performance, reliability and quality of supply standards are preferred following contingency. Strategies to achieve smart grid performance at the transmission level include the design of analytical tools and advanced technology with intelligence for performance analysis such as dynamic optimal power flow, robust state estimation, real-time stability assessment, and reliability and market simulation tools. Real-time monitoring based on PMU, state estimators sensors, and communication technologies are the transmission subsystem’s intelligent enabling tools for developing smart transmission functionality.

1.13.4 Monitoring and Control Technology Component

Intelligent transmission systems/assets include a smart intelligent network, self-monitoring and self-healing, and the adaptability and predictability of generation and demand robust enough to handle congestion, instability, and reliability issues. This new resilient grid has to withstand shock (durability and reliability), and be reliable to provide real-time changes in its use.

1.13.5 Intelligent Grid Distribution Subsystem Component

The distribution system is the final stage in the transmission of power to end users. Primary feeders at this voltage level supply small industrial customers and secondary distribution feeders supply residential and commercial customers. At the distribution level, intelligent support schemes will have monitoring capabilities for automation using smart meters, communication links between consumers and utility control, energy management components, and AMI. The automation function will be equipped with self-learning capability, including modules for fault detection, voltage optimization and load transfer, automatic billing, restoration and feeder reconfiguration, and real-time pricing.

1.13.6 Demand Side Management Component

Demand side management options and energy efficiency options developed for effective means of modifying the consumer demand to cut operating expenses from expensive generators and defer capacity addition.

DSM options provide reduced emissions in fuel production, lower costs, and contribute to reliability of generation. These options have an overall impact on the utility load curve. A standard protocol for customer delivery with two-way information highway technologies as the enabler is needed. Plug-and-play, smart energy buildings and smart homes, demand-side meters, clean air requirements, and customer interfaces for better energy efficiency will be in place.

1.14 SUMMARY

This chapter has discussed the progress made by different stakeholders in the design and development of the smart grid. A working definition of the smart grid was given. Two design architectures and the specific aspects of prospective smart grid function were provided. The next chapters discuss the tools and techniques needed for smart grid analysis and development.

REFERENCES

[1] “The Smart Grid: An Introduction and Smart Grid System Report.” Litos Strategic Communication, U.S. Department of Energy, 2009.

[2] L.D. Kinter-Meyer, M.C. Chassin, D.P. Kannberg, et al. “GridWiseTM: The Benefits of a Transformed Energy System.” Pacific Northwest National Laboratory, PNNL-14396, 2003.

[3] “Overview of the Smart Grid: Policies, Initiatives and Needs.” ISO New England, 2009.

[4] “The Modern Grid Initiative.” GridWise Architecture Council, Pacific Northwest National Laboratory, 2008.

[5] “Our Blueprint for the Future.” PEPCO Holdings, 2009.

[6] “PSERC Overview, 2008.” PSERC, 2008.

[7] J. Taft. “The Intelligent Power Grid.” IBM Global Services, 2006.

[8] “A National Vision for Electricity’s Second 100 Years.” Office of Electric Transmission and Distribution, U.S. Department of Energy, 2003.

SUGGESTED READINGS

American Recovery and Reinvestment Act of 2009. Public Law No. 111-5, 2009.

P. Van Doren and J. Taylor. “Rethinking Electricity Restructuring.” Policy Analysis 2004, 530, 1–8.

EPRI Intelligrid. Electric Power Research Institute, 2001–2010.

“Smart Grid System Report.” U.S. Department of Energy, 2009.

The Energy Independence and Security Act of 2007. S. 1419, 90d Congress, 2007.

“The Smart Grid: An Introduction and Smart Grid System Report.” U.S. Department of Energy, 2009.

2

SMART GRID COMMUNICATIONS AND MEASUREMENT TECHNOLOGY

2.1 COMMUNICATION AND MEASUREMENT

Because much of the existing transmission and distribution systems in the United States still uses older digital communication and control technology, advanced communication systems for distribution automation, such as Remote Terminal Unit (RTU) [3] and SCADA, are under development as well as innovative tools and software that will communicate with appliances in the home [1]. Ultimately, high-speed, fully integrated, two-way communication technologies will allow the smart grid to be a dynamic, interactive mega-infrastructure for real-time information and power exchange.

The technology exists for the measure, monitor, and control in real time in the Smart Grid, and this technology plays an essential role in the functioning of the Smart Grid. Issues of standards, cyber security, and interoperability which are dealt with more extensively in Chapter 8 impact most definitely on communication. There is need for the formalization of the standards and protocols which will be enforced for the secured transmission of critical and highly sensitive information within the communications scheme.

Obviously, existing measuring, monitoring, and control technology will have a role in smart grid capability. Establishing appropriate standards, cyber security, and interoperability (discussed in Chapter 8) requires careful study, for example, formalizing the standards and protocols for the secure transmission of critical and highly sensitive information within the proposed communication scheme. Moreover, open architecture’s plug-and-play environment will provide secure network smart sensors and control devices, control centers, protection systems, and users. Possible wired and wireless communications technologies can include:

1. Multiprotocol Label Switching (MPLS): high-performance telecommunications networks for data transmission between network nodes

2. Worldwide Interoperability for Microwave Access (WiMax): wireless telecommunication technology for point to multipoint data transmission utilizing Internet technology

3. Broadband over Power Lines (BPL): power line communication with Internet access

4. Wi-Fi: commonly used wireless local area network

Additional technologies include optical fiber, mesh, and multipoint spread spectrum.

The five characteristics of smart grid communications technology are:

1. High bandwidth

2. IP-enabled digital communication (IPv6 support is preferable)

3. Encryption

4. Cyber security

5. Support and quality of service and Voice over Internet Protocol (VoIP)

Reliable intercommunication of hardware and software will require configuring several types of network topologies. Below is a summary of the most likely candidates.

Local Area Network [5,6] consists of two or more components and high-capacity disk storage (file servers), which allow each computer in a network to access a common set of rules. LAN has operating system software which interprets input, instructs network devices, and allows users to communicate with each other. Each hardware device (computer, printer, and so on) on a LAN is a node. The LAN can operate or integrate up to several hundred computers. LAN combines high speed with a geographical spread of 1–10 km. LAN may also access other LANs or tap into Wide Area Networks. LAN with similar architectures are bridges which act as transfer points, while LAN with different architectures are gateways which convert data as it passes between systems.

LAN is a shared access technology, meaning that all of the attached devices share a common medium of communication such as coaxial, twisted pair, or fiber optics cable. A physical connection device, the Network Interface Card (NIC), connects to the network. The network software manages communication between stations on the system.

The special attributes and advantages of LAN include:

Resource sharing: allows intelligent devices such as storage devices, programs, and data files to share resources, that is, LAN users can use the same printer on the network; the installed database and the software can be shared by multiple usersArea covered: LAN is normally restricted to a small geographical area, for example, office building, utility, campusCost and availability: application software and interface devices are affordable and off-the-shelfHigh channel speed: ability to transfer data at rates between 1 and 10 million bits per secondFlexibility: grow/expand with low probability of error; easy to maintain and operate

LAN has three categories of data transmission:

1. Unicast transmission: a single data packet is sent from a source node to a destination (address) on the network

2. Multicast transmission: a single data packet is copied and sent to a specific subset of nodes on the network; the source node addresses the packet by using the multicast addresses

3. Broadcast transmission: a single data packet is copied and sent to all nodes on the network; the source node addresses the packet by using the broadcast address

LAN topologies define how network devices are organized. The four most common architectural structures are:

1. Bus topology: linear LAN architecture in which transmission from network station propagates the length of the medium and is received by all other stations connected to it

2. Ring bus topology: a series of devices connected to one another by unidirectional transmission links to form a single closed loop

3. Star topology: the end points on a network are connected to a common central hub or switch by dedicated links

4.