Smart Grid Fundamentals of Design PDF

SMART GRID  IEEE Press 445 Hoes Lane Piscataway, NJ 08854 IEEE Press Editorial Board Lajos Hanzo, Editor in Chief R. Abhari M. El-Hawary...

SMART GRID  IEEE Press 445 Hoes Lane Piscataway, NJ 08854 IEEE Press Editorial Board Lajos Hanzo, Editor in Chief R. Abhari M. El-Hawary O. P. Malik J. Anderson B-M. Haemmerli S. Nahavandi G. W. Arnold M. Lanzerotti T. Samad F. Canavero D. Jacobson G. Zobrist Kenneth Moore, Director of IEEE Book and Information Services (BIS) A complete list of titles in the IEEE Press Series on Power Engineering appears at the end of this book.  SMART GRID Fundamentals of Design and Analysis James Momoh IEEE PRESS A JOHN WILEY & SONS, INC., PUBLICATION Copyright © 2012 by the Institute of Electrical and Electronics Engineers. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. All rights reserved. Published simultaneously in Canada. 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TK3226.M588 2012 333.793'2–dc23 2011024774 Printed in the United States of America. 10 9 8 7 6 5 4 3 2 1  CONTENTS Preface xiii 1 SMART GRID ARCHITECTURAL DESIGNS 1 1.1 Introduction 1 1.2 Today’s Grid versus the Smart Grid 2 1.3 Energy Independence and Security Act of 2007: Rationale for the Smart Grid 2 1.4 Computational Intelligence 4 1.5 Power System Enhancement 5 1.6 Communication and Standards 5 1.7 Environment and Economics 5 1.8 Outline of the Book 5 1.9 General View of the Smart Grid Market Drivers 6 1.10 Stakeholder Roles and Function 6 1.10.1 Utilities 9 1.10.2 Government Laboratory Demonstration Activities 9 1.10.3 Power Systems Engineering Research Center (PSERC) 10 1.10.4 Research Institutes 10 1.10.5 Technology Companies, Vendors, and Manufacturers 10 1.11 Working Definition of the Smart Grid Based on Performance Measures 11 1.12 Representative Architecture 12 1.13 Functions of Smart Grid Components 12 1.13.1 Smart Devices Interface Component 13 1.13.2 Storage Component 13 1.13.3 Transmission Subsystem Component 14 1.13.4 Monitoring and Control Technology Component 14 1.13.5 Intelligent Grid Distribution Subsystem Component 14 1.13.6 Demand Side Management Component 14 v vi CONTENTS 1.14 Summary 15 References 15 Suggested Readings 15 2 SMART GRID COMMUNICATIONS AND MEASUREMENT TECHNOLOGY 16 2.1 Communication and Measurement 16 2.2 Monitoring, PMU, Smart Meters, and Measurements Technologies 19 2.2.1 Wide Area Monitoring Systems (WAMS) 20 2.2.2 Phasor Measurement Units (PMU) 20 2.2.3 Smart Meters 21 2.2.4 Smart Appliances 22 2.2.5 Advanced Metering Infrastructure (AMI) 22 2.3 GIS and Google Mapping Tools 23 2.4 Multiagent Systems (MAS) Technology 24 2.4.1 Multiagent Systems for Smart Grid Implementation 25 2.4.2 Multiagent Specifications 25 2.4.3 Multiagent Technique 26 2.5 Microgrid and Smart Grid Comparison 27 2.6 Summary 27 References 27 3 PERFORMANCE ANALYSIS TOOLS FOR SMART GRID DESIGN 29 3.1 Introduction to Load Flow Studies 29 3.2 Challenges to Load Flow in Smart Grid and Weaknesses of the Present Load Flow Methods 30 3.3 Load Flow State of the Art: Classical, Extended Formulations, and Algorithms 31 3.3.1 Gauss–Seidal Method 31 3.3.2 Newton–Raphson Method 32 3.3.3 Fast Decouple Method 33 3.3.4 Distribution Load Flow Methods 33 3.4 Congestion Management Effect 37 3.5 Load Flow for Smart Grid Design 38 3.5.1 Cases for the Development of Stochastic Dynamic Optimal Power Flow (DSOPF) 41 3.6 DSOPF Application to the Smart Grid 41 3.7 Static Security Assessment (SSA) and Contingencies 43 CONTENTS vii 3.8 Contingencies and Their Classification 44 3.8.1 Steady-State Contingency Analysis 46 3.8.2 Performance Indices 47 3.8.3 Sensitivity-Based Approaches 48 3.9 Contingency Studies for the Smart Grid 48 3.10 Summary 49 References 50 Suggested Readings 50 4 STABILITY ANALYSIS TOOLS FOR SMART GRID 51 4.1 Introduction to Stability 51 4.2 Strengths and Weaknesses of Existing Voltage Stability Analysis Tools 51 4.3 Voltage Stability Assessment 56 4.3.1 Voltage Stability and Voltage Collapse 57 4.3.2 Classification of Voltage Stability 58 4.3.3 Static Stability (Type I Instability) 59 4.3.4 Dynamic Stability (Type II Instability) 59 4.3.5 Analysis Techniques for Dynamic Voltage Stability Studies 60 4.4 Voltage Stability Assessment Techniques 62 4.5 Voltage Stability Indexing 65 4.6 Analysis Techniques for Steady-State Voltage Stability Studies 68 4.6.1 Direct Methods for Detecting Voltage Collapse Points 69 4.6.2 Indirect Methods (Continuation Methods) 69 4.7 Application and Implementation Plan of Voltage Stability 70 4.8 Optimizing Stability Constraint through Preventive Control of Voltage Stability 71 4.9 Angle Stability Assessment 73 4.9.1 Transient Stability 75 4.9.2 Stability Application to a Practical Power System 76 4.9.3 Boundary of the Region of Stability 77 4.9.4 Algorithm to Find the Controlling UEP 80 4.9.5 Process Changes in Design of DSA for the Smart Grid 80 4.10 State Estimation 81 4.10.1 Mathematical Formulations for Weighted Least Square Estimation 84 4.10.2 Detection and Identification of Bad Data 86 4.10.3 Pre-Estimation Analysis 86 viii CONTENTS 4.10.4 Postestimation Analysis 88 4.10.5 Robust State Estimation 90 4.10.6 SE for the Smart Grid Environment 94 4.10.7 Real-Time Network Modeling 95 4.10.8 Approach of the Smart Grid to State Estimation 95 4.10.9 Dynamic State Estimation 97 4.10.10 Summary 98 References 98 Suggested Readings 98 5 COMPUTATIONAL TOOLS FOR SMART GRID DESIGN 100 5.1 Introduction to Computational Tools 100 5.2 Decision Support Tools (DS) 101 5.2.1 Analytical Hierarchical Programming (AHP) 102 5.3 Optimization Techniques 103 5.4 Classical Optimization Method 103 5.4.1 Linear Programming 103 5.4.2 Nonlinear Programming 105 5.4.3 Integer Programming 106 5.4.4 Dynamic Programming 107 5.4.5 Stochastic Programming and Chance Constrained Programming (CCP) 107 5.5 Heuristic Optimization 108 5.5.1 Artificial Neural Networks (ANN) 109 5.5.2 Expert Systems (ES) 111 5.6 Evolutionary Computational Techniques 112 5.6.1 Genetic Algorithm (GA) 112 5.6.2 Particle Swarm Optimization (PSO) 113 5.6.3 Ant Colony Optimization 113 5.7 Adaptive Dynamic Programming Techniques 115 5.8 Pareto Methods 117 5.9 Hybridizing Optimization Techniques and Applications to the Smart Grid 118 5.10 Computational Challenges 118 5.11 Summary 119 References 120 6 PATHWAY FOR DESIGNING SMART GRID 122 6.1 Introduction to Smart Grid Pathway Design 122 6.2 Barriers and Solutions to Smart Grid Development 122 CONTENTS ix 6.3 Solution Pathways for Designing Smart Grid Using Advanced Optimization and Control Techniques for Selection Functions 125 6.4 General Level Automation 125 6.4.1 Reliability 125 6.4.2 Stability 127 6.4.3 Economic Dispatch 127 6.4.4 Unit Commitment 128 6.4.5 Security Analysis 130 6.5 Bulk Power Systems Automation of the Smart Grid at Transmission Level 130 6.5.1 Fault and Stability Diagnosis 131 6.5.2 Reactive Power Control 132 6.6 Distribution System Automation Requirement of the Power Grid 132 6.6.1 Voltage/VAr Control 132 6.6.2 Power Quality 135 6.6.3 Network Reconfiguration 136 6.6.4 Demand-Side Management 136 6.6.5 Distribution Generation Control 137 6.7 End User/Appliance Level of the Smart Grid 137 6.8 Applications for Adaptive Control and Optimization 137 6.9 Summary 138 References 138 Suggested Reading 139 7 RENEWABLE ENERGY AND STORAGE 140 7.1 Renewable Energy Resources 140 7.2 Sustainable Energy Options for the Smart Grid 141 7.2.1 Solar Energy 141 7.2.2 Solar Power Technology 142 7.2.3 Modeling PV Systems 142 7.2.4 Wind Turbine Systems 144 7.2.5 Biomass-Bioenergy 145 7.2.6 Small and Micro Hydropower 147 7.2.7 Fuel Cell 147 7.2.8 Geothermal Heat Pumps 148 7.3 Penetration and Variability Issues Associated with Sustainable Energy Technology 148 7.4 Demand Response Issues 150 7.5 Electric Vehicles and Plug-in Hybrids 151 x CONTENTS 7.6 PHEV Technology 151 7.6.1 Impact of PHEV on the Grid 151 7.7 Environmental Implications 152 7.7.1 Climate Change 153 7.7.2 Implications of Climate Change 153 7.8 Storage Technologies 154 7.9 Tax Credits 158 7.10 Summary 159 References 159 Suggested Reading 159 8 INTEROPERABILITY, STANDARDS, AND CYBER SECURITY 160 8.1 Introduction 160 8.2 Interoperability 161 8.2.1 State-of-the-Art-Interoperability 161 8.2.2 Benefits and Challenges of Interoperability 161 8.2.3 Model for Interoperability in the Smart Grid Environment 162 8.2.4 Smart Grid Network Interoperability 162 8.2.5 Interoperability and Control of the Power Grid 163 8.3 Standards 163 8.3.1 Approach to Smart Grid Interoperability Standards 163 8.4 Smart Grid Cyber Security 166 8.4.1 Cyber Security State of the Art 166 8.4.2 Cyber Security Risks 169 8.4.3 Cyber Security Concerns Associated with AMI 171 8.4.4 Mitigation Approach to Cyber Security Risks 171 8.5 Cyber Security and Possible Operation for Improving Methodology for Other Users 173 8.6 Summary 174 References 174 Suggested Readings 174 9 RESEARCH, EDUCATION, AND TRAINING FOR THE SMART GRID 176 9.1 Introduction 176 9.2 Research Areas for Smart Grid Development 176 9.3 Research Activities in the Smart Grid 178 CONTENTS xi 9.4 Multidisciplinary Research Activities 178 9.5 Smart Grid Education 179 9.5.1 Module 1: Introduction 180 9.5.2 Module 2: Architecture 180 9.5.3 Module 3: Functions 181 9.5.4 Module 4: Tools and Techniques 181 9.5.5 Module 5: Pathways to Design 181 9.5.6 Module 6: Renewable Energy Technologies 181 9.5.7 Module 7: Communication Technologies 182 9.5.8 Module 8: Standards, Interoperability, and Cyber Security 182 9.5.9 Module 9: Case Studies and Testbeds 182 9.6 Training and Professional Development 182 9.7 Summary 183 References 183 10 CASE STUDIES AND TESTBEDS FOR THE SMART GRID 184 10.1 Introduction 184 10.2 Demonstration Projects 184 10.3 Advanced Metering 185 10.4 Microgrid with Renewable Energy 185 10.5 Power System Unit Commitment (UC) Problem 186 10.6 ADP for Optimal Network Reconfiguration in Distribution Automation 191 10.7 Case Study of RER Integration 196 10.7.1 Description of Smart Grid Activity 196 10.7.2 Approach for Smart Grid Application 196 10.8 Testbeds and Benchmark Systems 197 10.9 Challenges of Smart Transmission 198 10.10 Benefits of Smart Transmission 198 10.11 Summary 198 References 199 11 EPILOGUE 200 Index 203  PREFACE The term “smart grid” defines a self-healing network equipped with dynamic optimiza- tion 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 fun- damentals, 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 indus- try 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 random- ness, 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 Founda- tion (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 xiii xiv PREFACE 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 stu- dents 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 genera- tion, transmission, and distribution and supported with controls and devices to maintain reliability, stability, and efficiency. However, system operators are now facing new chal- lenges 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 tech- niques 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 regions Accommodating renewables Optimizing the transfer capability of the transmission and distribution networks and meeting the demand for increased quality and reliable supply Managing and resolving unpredictable events and uncertainties in operations and planning more aggressively. Smart Grid: Fundamentals of Design and Analysis, First Edition. James Momoh. © 2012 Institute of Electrical and Electronics Engineers. Published 2012 by John Wiley & Sons, Inc. 1 2 SMART GRID ARCHITECTURAL DESIGNS TABLE 1.1. Comparison of Today’s Grid vs. Smart Grid Preferred Characteristics Today’s Grid Smart Grid Active Consumer Consumers are uninformed and Informed, involved consumers— Participation do not participate demand response and distributed energy resources Accommodation of all Dominated by central Many distributed energy generation and storage generation—many obstacles resources with plug-and-play options exist for distributed energy convenience focus on resources interconnection renewables New products, services, Limited, poorly integrated Mature, well-integrated and markets wholesale markets; limited wholesale markets; growth of opportunities for consumers new electricity markets for consumers Provision of power Focus on outages—slow Power quality a priority with a quality for the digital response to power quality variety of quality/price economy issues options—rapid resolution of issues Optimization of assets Little integration of operational Greatly expanded data and operates efficiently data with asset acquisition of grid parameters; management—business focus on prevention, process silos minimizing impact to consumers Anticipating responses Responds to prevent further Automatically detects and to system disturbances damage; focus on protecting responds to problems; focus on (self-healing) assets following a fault prevention, minimizing impact to consumers Resiliency against cyber Vulnerable to malicious acts of Resilient to cyber attack and attack and natural terror and natural disasters; natural disasters; rapid disasters slow response restoration capabilities 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. 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 infrastructure that ENERGY INDEPENDENCE AND SECURITY ACT OF 2007 3 Figure 1.1. Rationale for the smart grid. will meet future demand growth. Figure 1.1 illustrates the features needed to facilitate the development of an energy-efficient, reliable system. The Act established a Smart Grid Task Force, whose mission is “to insure aware- ness, coordination and integration of the diverse activities of the DoE Office and else- where in the Federal Government related to smart-grid technologies and practices”. The task force’s activities include research and development; development of widely accepted standards and protocols; the relationship of smart grid technologies and 4 SMART GRID ARCHITECTURAL DESIGNS practices to electric utility regulation; the relationship of smart grid technologies and practices to infrastructure development, system reliability, and security; and the rela- tionship 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 genera- tion, transmission and distribution As Figure 1.2 shows, there are five key aspects of smart grid development and deployment. 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, evolu- tion programming, decision support tools, and adaptive optimization techniques. Power System Enhancement Communication and Standards Testbed Smart Grid Environment and Computational Economics Intelligence Figure 1.2. Five key aspects of smart grid development. OUTLINE OF THE BOOK 5 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 character- istics 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 imple- mented 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 archi- tecture. 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 6 SMART GRID ARCHITECTURAL DESIGNS 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, fol- lowed 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 col- laboration. Figure 1.3 is a schematic of the 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 effi- ciency 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 genera- tion. 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 understand- ing 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 STAKEHOLDER ROLES AND FUNCTION 7 Chapter 1 Introduction to the Smart Grid Working Definition Smart Grid Architecture Chapter 2 Smart Grid Functions GIS and Google mapping tools Multi-agent System MAS Technology Performance Measures for Tool Development Smart Grid Tools and Techniques Chapter 3 Load flow Concepts and New Approach to Smart Grid Optimal Power Flow Contingencies Chapter 4 Voltage, Angle Stability and Estimation Application to Smart Grid Computational Techniques Chapter 5 Communication and Measurement Monitoring PMU, Smart Meters, Measurements Technologies Barriers and Solutions to Smart Grid Development Pathways for Design using Advanced Optimization and Control Generation level Automation Bulk Power Systems Automation Chapter 6 Distribution System Automation End-User/Appliance Level Development and Applications of DSOPF Evaluation of Techniques for Smart Grid Design Market and Pricing Renewable Energy Technologies Storage Technologies Chapter 7 Demand Response Electric Vehicles and Plug Environmental Implications and Climate Change Tax Credit and Incentives Standards Chapter 8 Interoperability Cyber Security Research Areas and Needs for Smart Grid Development Chapter 9 Education Needs for the Smart Grid Environment Training and Professional Development Chapter 10 Case Studies and Test Beds for Smart Grid Figure 1.3. Schematic of chapters. 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 miti- gation of energy prices, reduced dependence on foreign oil, increased efficiency, and reliability of power supply. Figure 1.4 shows the categories of stakeholders. Other participants in the development of the smart grid include government agen- cies, manufacturers, and research institutes. The federal Department of Energy’s (DOE) 8 SMART GRID ARCHITECTURAL DESIGNS SMART GRID: Stakeholders UTILITIES: Installation and implementation of power grid technologies POLICY-MAKERS: Establishment of standards for operation, monitoring, interoperability etc. TECHNOLOGY PROVIDERS: Development of smart grid technologies for the grid enhancement RESEARCHERS: Development of tools and technologies for the smart grid CONSUMERS: Consumer input and participation, consumer buy-in etc. Figure 1.4. Stakeholders and their functions. National Renewable Energy Laboratory (NREL) and state agencies such as the Cali- fornia Energy Commission and the New York State Energy Research and Development Authority are among the pioneers. In the monograph, “The Smart Grid: An Introduc- tion,” the DOE discusses the nature, challenges, opportunities, and necessity for smart grid implementation. It defines the smart grid as technology which “makes this trans- formation 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”. The characteristics of the smart grid are two-way digital com- munication, 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 visual- ization technology to provide wide-area grid awareness, integrating real-time sensor data, weather information, and grid modeling with geographical information. 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 Indepen- dence and Security Act (EISA) and the FERC Reliability Standards. STAKEHOLDER ROLES AND FUNCTION 9 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 technolo- gies: 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 elec- trical 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. 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 analyti- cal 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. In January 2006, four years after its first presentation, PNNL unveiled the GridWise Initiative whose objective was the testing of new electric grid technologies. 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 Elec- tric; American Electric Power, Bonneville Power Administration, ConEd, the PJM Interconnection; Battelle, RDS, SAIC, Nexgen, and RockPort Capital Partners. The GridWise Architecture Council , a primary advocate for the smart grid, promotes the 10 SMART GRID ARCHITECTURAL DESIGNS 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) consists of 13 universi- ties 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 meth- odology, 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, Michi- gan 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. 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. WORKING DEFINITION OF THE SMART GRID 11 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. 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 time Predict behavior, anticipate Adapt to new environments like distributed resources and renewable energy resources Handle stochastic demand and respond to smart appliances Provide self-correction, reconfiguration, and restoration Handle randomness of loads and market participants in real time Create more complex interactive behavior with intelligent devices, communica- tion protocols, and standard and smart algorithms to improve smart communica- tion and transportation systems. In this environment, smart control strategies will handle congestion, instability, or reli- ability 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 inter- ested 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. 12 SMART GRID ARCHITECTURAL DESIGNS Transmission System Coordination, Automation Situation Assessment Distribution Automation System Operations Renewables Integration Energy Efficiency Demand Participation Signals & Options Distributed Generation & Storage Smart Appliances, PHEVs, & Storage Figure 1.5. DOE representative architecture of the smart grid design (architecture 1). 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 1.6 shows how the second architectural framework is partitioned into sub- systems 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. 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. FUNCTIONS OF SMART GRID COMPONENTS 13 Figure 1.6. The intelligent grid (architecture 2). 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 bat- teries, 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, distrib- uted generation, environmental impact and pollution has to be introduced in the design of smart grid component at the generation level. 14 SMART GRID ARCHITECTURAL DESIGNS 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 disrup- tions. 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 trans- mission 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 effec- tive means of modifying the consumer demand to cut operating expenses from expen- sive generators and defer capacity addition. DSM options provide reduced emissions in fuel production, lower costs, and con- tribute 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. SUGGESTED READINGS 15 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 “The Smart Grid: An Introduction and Smart Grid System Report.” Litos Strategic Com- munication, U.S. Department of Energy, 2009. 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. “Overview of the Smart Grid: Policies, Initiatives and Needs.” ISO New England, 2009. “The Modern Grid Initiative.” GridWise Architecture Council, Pacific Northwest National Laboratory, 2008. “Our Blueprint for the Future.” PEPCO Holdings, 2009. “PSERC Overview, 2008.” PSERC, 2008. J. Taft. “The Intelligent Power Grid.” IBM Global Services, 2006. “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) and SCADA, are under development as well as innovative tools and software that will communicate with appliances in the home. Ultimately, high-speed, fully integrated, two-way communication technologies will allow the smart grid to be a dynamic, inter- active 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 interop- Smart Grid: Fundamentals of Design and Analysis, First Edition. James Momoh. © 2012 Institute of Electrical and Electronics Engineers. Published 2012 by John Wiley & Sons, Inc. 16 COMMUNICATION AND MEASUREMENT 17 erability (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 telecom- munication technology for point to multipoint data transmission utilizing Inter- net 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 geographi- cal spread of 1–10 km. LAN may also access other LANs or tap into Wide Area Net- works. 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. 18 SMART GRID COMMUNICATIONS AND MEASUREMENT TECHNOLOGY 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 users Area covered: LAN is normally restricted to a small geographical area, for example, office building, utility, campus Cost and availability: application software and interface devices are affordable and off-the-shelf High channel speed: ability to transfer data at rates between 1 and 10 million bits per second Flexibility: 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 des- tination (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 unidirec- tional 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. Tree topology: identical to the bus topology except that branches with multiple nodes are also possible The devices and software used in LAN utilize a standard protocol such as Ethernet/ IEEE 802.3, Token Ring/IEEE 802.5 or 880.2 (available through IEEE Press). Home Access Network [2,3] is a LAN confined to an individual home. It enables remote control of automated digital devices and appliances throughout the house. Smart meters, smart appliances and Web-based monitoring can be integrated into this level. MONITORING, PMU, SMART METERS, AND MEASUREMENTS TECHNOLOGIES 19 Neighborhood Area Network (NAN) is a wireless community currently used for wireless local distribution applications. Ideally, it will cover an area larger than a LAN. Some architectural structures will focus on the integration and interoperability of the various domains within the smart grid. Domains consist of groups of buildings, systems, individuals, or devices which have similar communications characteristics: Bulk generation: includes market services interface, plant control system, and generators; this domain interacts with the market operations and transmission domains through wide area networks, substation LANs, and the Internet Transmission: includes substation devices and controllers, data collectors, and electric storage; this domain interacts with bulk generation and operations through WANs and substation LANs; integrated with the distribution domain Distribution: this domain interacts with operations and customers through Field Area Networks Customer: includes customer equipment, metering, Energy Management Systems (EMS), electric storage, appliances, PHEVs, and so on Service Providers: includes utility and third party providers which handle billing customer services, and so on; this domain interacts with operations and customers primarily through the Internet Operations: includes EMS, Web Access Management System (WAMS), and SCADA; this domain can be sub-divided into ISO/RTO, transmission, and distribution Market: includes /ISOs/RTOs, aggregators, and other market participants 2.2 MONITORING, PMU, SMART METERS, AND MEASUREMENTS TECHNOLOGIES The smart grid environment requires the upgrade of tools for sensing, metering, and measurements at all levels of the grid. These components will provide the data neces- sary for monitoring the grid and the power market. Sensing provides outage detection and response, evaluates the health of equipment and the integrity of the grid, eliminates meter estimations, provides energy theft protection, enables consumer choice, DSM, and various grid monitoring functions. With regard to metering and measurement, new digital technologies using two-way communications, a variety of inputs (pricing signals, time-of-day tariff, regional trans- mission organization (RTO) curtailments for congestion relief), a variety of outputs (real time consumption data, power quality, electric parameters), the ability to connect and disconnect, and interfaces with generators, grid operators, and customer portals to enhance power measurement. This is facilitated by the increased utilization of digital electronics for metering and measurements, advancement of the electric meter at the customer level, and installation of wide area monitoring system for advanced utility monitoring and protection [11,12]. Details of these measurements are discussed in later sections. 20 SMART GRID COMMUNICATIONS AND MEASUREMENT TECHNOLOGY New digital technologies will employ two-way communication, a variety of inputs (pricing signals, time-of-day tariffs, RTO) curtailments for congestion relief), a variety of outputs (real-time consumption data, power quality, electric parameters), the ability to connect and disconnect, and interfaces with generators, grid operators, and customer portals to enhance power measurement. This introduces the increased utiliza- tion of digital electronics for metering and measurements, advancement of the electric meter at the customer level, and installation of wide area monitoring systems (WAMs) for advanced utility monitoring and protection [11,12]. Details of these measurements are discussed in later sections. 2.2.1 Wide Area Monitoring Systems (WAMS) WAMS are designed by the utilities for optimal capacity of the transmission grid and to prevent the spread of disturbances. By providing real-time information on stability and operating safety margins, WAMS give early warnings of system disturbances for the prevention and mitigation of system-wide blackouts. WAMS utilize sensors distrib- uted throughout the network in conjunction with GPS satellites for precise time stamp- ing of measurements in the transmission system. The integrated sensors will interface with the communication network. Phasor Measurements are a current technology that is a component of most smart grid designs. 2.2.2 Phasor Measurement Units (PMU) Phasor Measurement Units or Synchrophasors give operators a time-stamped snapshot of the power system. The PMUs consist of bus voltage phasors and branch current phasors, in addition to information such as locations and other network parameters [9,10]. Phasor measurements are taken with high precision from different points of the power system at the same instant, allowing an operator to visualize the exact angular difference between different locations. PMUs are equipped with GPS receivers which allow synchronization of readings taken at distant points. Microprocessor-based instrumentation such as protection relays and Disturbance Fault Recorders (DFRs) incorporate the PMU module with other existing functionalities as an extended feature. The IEEE standard on Synchrophasors specifies the protocol for communicating the PMU data to the Phasor Data Concentrator. Figure 2.1 illustrates the PMU measurement system from Reference 8. PMUs ensure voltage and current with high accuracy at a rate of 2.88 kHz. They can calculate real power, reactive power, frequency, and phase angle 12 times per 60 hertz cycle. The actual sampling rate used to achieve this output is 1.4 MHz. Recent trends now require fast controls and online implementations for mitigating voltage collapse in the shortest, least-cost time. Over the years, researchers and engineers have found PMUs are suitable for monitoring and control of voltage stability PMUs) [6–9]. Offering wide-area situational awareness, phasor measurement work to ease con- gestion, bottlenecks and mitigate—or even prevent—blackouts. When integrated with Smart Grid communications technologies, the measurements taken will provide dynamic MONITORING, PMU, SMART METERS, AND MEASUREMENTS TECHNOLOGIES 21 Control Center Figure 2.1. Conceptual diagram of a synchronized phasor measuring system. visibility into the power system. Adoption of the Smart Grid with real time measure- ment will enhance every facet of the electric delivery system including generation, transmission, distribution, and consumption. It will increase the possibilities of distrib- uted generation, bringing generation closer to those it serves. Additional utility monitoring systems include dynamic line rating technology, conductor sensors, insulation contamination leakage current, backscatter radios tech- nology, electronic instrument transformers, and monitors for circuit breaker, cables, batteries, temperature, and current frequency and so on [10, 11]. Research into the application and integration of these measurements into the smart grid is particularly important and continuing work. 2.2.3 Smart Meters Smart meters have two functions: providing data on energy usage to customers (end- users) to help control cost and consumption; sending data to the utility for load factor control, peak-load requirements, and the development of pricing strategies based on consumption informationand so on Automated data reading is an additional 22 SMART GRID COMMUNICATIONS AND MEASUREMENT TECHNOLOGY component of both smart meters and two-way communication between customers and utilities. The development of smart meters is planned for electricity, water, and gas consumption. Smart meters equip utility customers with knowledge about how much they pay per kilowatt hour and how and when they use energy. This will result in better pricing information and more accurate bills in addition to ensuring faster outage detection and restoration by the utility. Additional features will allow for demand-response rates, tax credits, tariff options, and participation in voluntary rewards programs for reduced consumption. Still other features will include remote connect/disconnect of users, appli- ance control and monitoring, smart thermostat, enhanced grid monitoring, switching, and prepaid metering. With governmental assistance, large-scale deployment of smart meters has begun throughout the United States. Academic participation in the research and development of metering tools and techniques for network analysis enhancement and the use of smart meter outputs for voltage stability and security assessment and enhancement have been proposed. 2.2.4 Smart Appliances Smart appliances cycle up and down in response to signals sent by the utility. The applicances enable customers to participate in voluntary demand response programs which award credits for limiting power use in peak demand periods or when the grid is under stress. An override function allows customers to control their appliances using the Internet. Air conditioners, space heaters, water heaters, refrigerators, washers, and dryers represent about 20% of total electric demand during most of the day and throughout the year. Grid-friendly appliances use a simple computer chip that can sense dis- turbances in the grid’s power frequency and can turn an appliance off for a few minutes to allow the grid to stabilize during a crisis. 2.2.5 Advanced Metering Infrastructure (AMI) AMI is the convergence of the grid, the communication infrastructure, and the support- ing information infrastructure. The network-centric AMI coupled with the lack of a composite set of cross industry AMI security requirements and implementation guid- ance, is the primary motivation for its development. The problem domains to be addressed within AMI implementations are relatively new to the utility industry; however, precedence exists for implementing large-scale, network-centric solutions with high information assurance requirements. The defense, cable, and telecom indus- tries offer many examples of requirements, standards, and best practices that are directly applicable to AMI implementations. The functions of AMI can be subdivided into three major categories: Market applications: serve to reduce/eliminate labor, transportation, and infra- structure costs associated with meter reading and maintenance, increase accuracy GIS AND GOOGLE MAPPING TOOLS 23 of billing, and allow for time-based rates while reducing bad debts; facilitates informed customer participation for energy management Customer applications: serves to increase customer awareness about load reduction, reduces bad debt, and improves cash flow, and enhances customer convenience and satisfaction; provides demand response and load management to improve system reliability and performance Distribution operations: curtails customer load for grid management, optimizes network based on data collected, allows for the location of outages and restora- tion of service, improves customer satisfaction, reduces energy losses, improves performance in event of outage with reduced outage duration and optimization of the distribution system and distributed generation management, provides emergency demand response An extension of AMI will be smart meters which handle customers’ gas and water usage data. The issues associated with ensuring network and data security are discussed in Chapter 8. 2.3 GIS AND GOOGLE MAPPING TOOLS GIS is useful for managing traditional electric transmission and distribution and telecom networks. It can also help to manage information about utility assets for data collection and maintenance. Google’s free downloadable Google Earth software offers geographical contextual information in an updated user-friendly platform that facilitates inquiry-based study and analysis. Users can create and share many types of dynamically-updating data over the Internet. Keyhole Markup Language (KML) allows them to overlay basic data types such as images, point data, lines, and polygons. Through satellite imagery, maps are available from space to street-level. The integration of GIS with Google Earth or other mapping tools will aid in understanding the relationship of the grid network to its surroundings, for example, determining the optimal location of rights of way, place- ment of sensors and poles, and so on. GIS technology will provide partial context to operators and planners, for example, real-time sensors that collect the data needed to reconfigure networks for reducing outages and equipment failures. The trends in the development of the electric power system and the expectation of future demand suggest the following needs: 1. Reducing outage time 2. Preventing power theft which causes significant unaccounted losses 3. Effective system for collection and billing system 4. Expanding services for customers 5. Effective asset management 6. Improving reliability such as SAIDI (System Average Interruption Duration Index) and SAIFI (System Average Interruption Frequency Index) for distribu- tion networks 24 SMART GRID COMMUNICATIONS AND MEASUREMENT TECHNOLOGY 7. Improving analysis of customer complaint logs 8. Enhancing load flow power quality analysis and fault study for current and anticipated problems 9. Scheduling of actions such as load shedding and vegetation control 2.4 MULTIAGENT SYSTEMS (MAS) TECHNOLOGY MAS are a computational system in which several agents cooperate to achieve a desired task. The performance of MAS can be decided by the interactions among various agents. Agents cooperate to achieve more than if they act individually. Increasingly, MAS are the preferential choice for developing distributed systems. The development of monitoring and measurement schemes within the smart grid envi- ronment can be enhanced through the use of MAS architecture (Fig. 2.2). As an example, MAS have been utilized as a detection and diagnosis device and in system monitoring. Such architectures utilize a collection of agents such as Arbitrator Agents (AA), System Monitoring Agents (SMA), Fault Detection Agents (FDA), Diagnosis Agents (DA), a Judgment Index Agent (JIA), and a Scheduling Agent (SA). Information passes between the agents about the appropriate actions to be taken. When imple- mented, the process repeats itself to constantly monitor the system so that management of system conditions can be implemented instantaneously. Arbitrator MAS Structure for Shared Enforced MAS Behavior and Ontology Assessment Control Agent Function Organization of Agent Fault Tolerant Observer Programming Diagnose Computing Platform / Cost Effectiveness language Decide Computation Act Agent Diagnosis and Report Adaptability and Reporting Flexibility Communication Layer – Language and Protocols Network Layer (System Under Control) Figure 2.2. Simplified multiagent architecture. MULTIAGENT SYSTEMS (MAS) TECHNOLOGY 25 2.4.1 Multiagent Systems for Smart Grid Implementation As mentioned in Chapter 1, the DOE’s Modern Grid Initiative explains that a smart grid integrates advanced sensing technologies, control methods, and integrated com- munications into the present electricity grid at both transmission and distribution levels. The smart grid is expected to have the following key characteristics: 1. self-healing 2. consumer friendly 3. attack resistant 4. provide power quality for 21st-century needs 5. accommodate all generation and storage options 6. enable markets 7. optimize assets and operate efficiently Central to the operation of any power system is its control architecture consisting of hardware and software protocols for exchanging system status and control signals. In conventional electric power systems, this is accomplished by SCADA [4, 5]. Current trends to control and monitor system operations are moving toward the use of MAS. A multiagent system is a combination of several agents working in collaboration pursu- ing assigned tasks to achieve the overall goal of the system. The multiagent system has become an increasingly powerful tool in developing complex systems that take advan- tages of agent properties: autonomy, sociality, reactivity and pro-activity. The multiagent system is autonomous in that they operate without human interven- tions. The multiagent system is sociable in that they interact with other agents via some kind of agent communication language. The agents also perceive and react to their environment. Lastly, the multiagent system is proactive in that they are able to exhibit goal oriented behavior by taking initiatives. 2.4.2 Multiagent Specifications In this section, the specifications of a control agent, a distributed energy resource (DER) agent, a user agent, and a database agent in the Intelligent Distributed Autonomous Power System (IDAPS) MAS are defined. 1. Control agent: responsibilities include monitoring system voltage and frequency to detect contingency situations or grid failures, and sending signals to the main circuit breaker to isolate the IDAPS microgrid from the utility when an upstream outage is detected; receiving electricity price ($/kWh) signal from the main grid, which may be obtained from AMI, and publishing them to the IDAPS entities 2. DER agent: responsibilities include storing associated DER information, moni- toring and controlling DER power levels and connect/disconnect status; DER information to be stored may include DER identification number, type (solar 26 SMART GRID COMMUNICATIONS AND MEASUREMENT TECHNOLOGY cells, microturbines, fuel cells), power rating (kW), local fuel availability, cost function or price at which users agree to sell, DER availability, that is, planned maintenance schedule 3. User agent: acts as a customer gateway that makes features of an IDAPS microgrid accessible to users; responsibilities include providing users with real- time information on entities residing in the IDAPS system; monitors electricity consumption by each critical and noncritical load; allows users to control the status of loads based on user ’s predefined priority 4. Database agent: serves as a data access point for other agents as well as users; responsibilities include storing system information, recording messages and data shared among agents. 2.4.3 Multiagent Technique An agent of a MAS may be defined as an entity with attributes considered useful in a particular domain. In this framework, an agent is an information processor that performs autonomous actions based on information. Common agent attributes include: Autonomy: goal-directedness, proactive and self-starting behavior Collaborative behavior: the ability to work with other agents to achieve a common goal Knowledge-level communication ability: the ability to communicate with other agents with language resembling human speech acts rather than typical symbol- level program-to-program protocols Reactivity: the ability to selectively sense and act Temporal continuity: persistence of identity and state over long periods MAS can be characterized by: Each agent has incomplete capabilities to solve a problem No global system control Decentralized data Asynchronous computation For instance, the system outage of a ship could be caused by an internal system error or any external contingency from battle. To pursue the best ship performance, it is very important to restore the electric power supply as much as possible. When a fault occurs on the ship power system, the protection systems will isolate the fault from the remaining power grid. Then the system should restore the electric power to a target configuration after the outage. An example of MAS architecture in action is a power failure on board a ship that is caused by an internal system error, an external contingency from battle, and so on. REFERENCES 27 Clearly, the goal is rapid restoration of the onboard power supply; hence, when a fault occurs, the protection system will isolate the fault, allowing the system to restore power to a target configuration after the outage. 2.5 MICROGRID AND SMART GRID COMPARISON Research has been conducted to understand the differences between a microgrid and a smart grid. Basically, a microgrid is a local island grid that can operate as a stand-alone or as a grid-connected system. It is powered by gas turbines or renewable energy and includes special purpose inverters and a link for plug-and-play to the legacy grid. Special purpose filters overcome harmonics problems while improving power quality and efficiency. Several demonstration projects and a testbed are operating in university and government facilities. In summary, think of the microgrid as a local power provider with limited advanced control tools and the smart grid is a wide area provider with sophisticated automated decision support capabilities. 2.6 SUMMARY This chapter has focused on various communication aspects of the smart grid. The measurement techniques described included PMUs and smart meters. GIS was intro- duced as a planning tool to facilitate locating important components. The relationship of MAS to the smart grid developmental process was also described. REFERENCES J.A. Momoh. Electric Power System Application of Optimization. Marcel Dekker, New York, 2001. J.L. Marinho and B. Stott. “Linear Programming for Power System Network Security Applications.” IEEE Transactions on Power Apparatus and Systems 1979, PAS-98, 837–848. R.C. Eberhart and J. Kennedy. “A New Optimizer Using Particle Swarm Theory.” In Pro- ceedings on the Sixth International Symposium on Micromachine and Human Science 1995, 39–31. G. Riley and J. Giarratano. Expert Systems: Principles and Programming. PWS Publisher, Boston, 2003. A. Englebrecht. Computational Intelligence: An Introduction, John Wiley & Sons, 2007. M. Dorigo and T. Stuzle. Ant Colony Optimization. Massachusetts Institute of Technology, Cambridge, 2004. A.G. Barto, W.B. Powell, D.C. Wunsch, and J. Si. Handbook of Learning and Approximate Dynamic Programming. IEEE Press Series on Computational Intelligence, 2004. J.A. Momoh. Electrical Power System Applications of Optimization, CRC Press, 2008. 28 SMART GRID COMMUNICATIONS AND MEASUREMENT TECHNOLOGY W.H. Zhange and T. Gao. “A Min-Max Method with Adaptive Weightings for Uniformly Spaced Pareto Optimum Points.” Computers and Structures 2006, 84, 1760–1769. P.K. Skula and K. Deb. “On Finding Multiple Pareto-Optimal Solutions Using Classical and Evolutional Generating Methods.” European Journal of Operational Research 2007, 181, 1630–1652. M. Dorigo and T. Stutzle. “The Ant Colony Optimization Metaheuristic: Algorithms, Appli- cations and Advances.” In F. Glover and G. Kochenberger, eds.: Handboook of Metaheuris- tics. Norwell, MA, Kluwer, 2002. A.G. Phadhke. “Synchronized Phasor Measurements in Power Systems.” IEEE Comput. Appl. Power 1993, 6, 10–15.  3 PERFORMANCE ANALYSIS TOOLS FOR SMART GRID DESIGN 3.1 INTRODUCTION TO LOAD FLOW STUDIES Load flow studies are critical to system planning and system operation. For example, data on peak load conditions assists planners in determining the size of components (conductors, transformers, reactors, and shunt capacitors), siting new generation and transmission, and planning interties with neighboring systems to meet predicted demand consistent with the North American Electric Reliability Corporation’s (NERC) reli- ability requirements. Load flow studies identify line loads and bus voltages out of range, inappropriately large bus phase angles (and the potential for stability problems), com- ponent loads (principally transformers), proximity to Q-limits at generation buses, and other parameters having the potential to create operating difficulties. Intermediate load and off-peak (minimum) load studies are also useful, since off-peak loads can result in high voltage conditions that are not identified during peak loads. Load flow studies assist system operators in calculating power levels at each generating unit for economic dispatch, analyzing outages and other forced operating conditions (contingency analysis ), and coordinating power pools. In most instances, load flow studies are used to assess system performance and operations under a given condition. Smart Grid: Fundamentals of Design and Analysis, First Edition. James Momoh. © 2012 Institute of Electrical and Electronics Engineers. Published 2012 by John Wiley & Sons, Inc. 29 30 PERFORMANCE ANALYSIS TOOLS FOR SMART GRID DESIGN 3.2 CHALLENGES TO LOAD FLOW IN SMART GRID AND WEAKNESSES OF THE PRESENT LOAD FLOW METHODS Current legacy methods have weaknesses that need to be addressed prior to their use in analyzing smart grid performance and operations. Four fundamental questions should be answered: 1. What are the special features of the smart grid compared to the legacy system? 2. What computations are needed in the case of smart grid? 3. What specific directions are needed for developing a new power flow? 4. What new features of the load flow make it suitable for smart grid performance and evaluation? Table 3.1 compares the old and desired load flow techniques. Other features to be considered in the development of the new load flow include: 1. Condition adaptiveness [9–11] of transmission and distribution to accommodate load flows comprising renewable generation 2. Self-adaptiveness to ensure proper coordination 3. High impedance topology matching for distribution network with randomness and uncertainty requiring intelligence analytical tools 4. Since reverse power flow technique is possible, the use of FACTs devices to power electronics building blocks is essential. Existing load flow performance tools capable of determining voltage, angle, flows, MW/MVAr, and scheduling dispatch are mostly offline although a few can give real- time results. To enhance load flow capabilities, the smart grid load flow process consists of the following st