Smart Grid Communication Infrastructures

FENG YE, Assistant Professor, Department of Electrical and Computer Engineering, University of Dayton, USA. YI QIAN, Professor, Department of Electrical and Computer Engineering, University of Nebraska-Lincoln (UNL), USA. ROSE QINGYANG HU, Professor, Department of Electrical and Computer Engineering, Utah State University, USA.

• 1 Background of the Smart Grid 11.1 Motivations and Objectives of the Smart Grid 11.1.1 Better Renewable Energy Resource Adaption 21.1.2 Grid Operation Efficiency Advancement 31.1.3 Grid Reliability and Security Improvement 41.2 Smart Grid Communications Architecture 51.2.1 Conceptual Domain Model 61.2.2 Two-Way Communications Network 71.3 Applications and Requirements 91.3.1 Demand Response 91.3.2 Advanced Metering Infrastructure 101.3.3 Wide-Area Situational Awareness and Wide-Area Monitoring Systems 111.3.4 Communication Networks and Cybersecurity 121.4 The Rest of the Book 132 Smart Grid Communication Infrastructures 152.1 An ICT Framework for the Smart Grid 152.1.1 Roles and Benefits of an ICT Framework 152.1.2 An Overview of the Proposed ICT Framework 162.2 Entities in the ICT Framework 182.2.1 Internal Data Collectors 182.2.2 Control Centers 202.2.3 Power Generators 222.2.4 External Data Sources 232.3 Communication Networks and Technologies 232.3.1 Private and Public Networks 232.3.2 Communication Technologies 242.4 Data Communication Requirements 302.4.1 Latency and Bandwidth 312.4.2 Interoperability 322.4.3 Scalability 322.4.4 Security 322.5 Summary 333 Self-Sustaining Wireless Neighborhood-Area Network Design 353.1 Overview of the Proposed NAN 353.1.1 Background and Motivation of a Self-Sustaining Wireless NAN 353.1.2 Structure of the Proposed NAN 373.2 Preliminaries 383.2.1 Charging Rate Estimate 393.2.2 Battery-Related Issues 403.2.3 Path Loss Model 423.3 Problem Formulations and Solutions in the NAN Design 443.3.1 The Cost Minimization Problem 443.3.2 Optimal Number of Gateways 483.3.3 Geographical Deployment Problem for Gateway DAPs 513.3.4 Global Uplink Transmission Power Efficiency 543.4 Numerical Results 563.4.1 Evaluation of the Optimal Number of Gateways 563.4.2 Evaluation of the Global Power Efficiency 563.4.3 Evaluation of the Global Uplink Transmission Rates 583.4.4 Evaluation of the Global Power Consumption 593.4.5 Evaluation of the Minimum Cost Problem 593.5 Case Study 633.6 Summary 654 Reliable Energy-Efficient Uplink Transmission Power Control Scheme in NAN 674.1 Background and Related Work 674.1.1 Motivations and Background 674.1.2 Related Work 694.2 System Model 704.3 Preliminaries 714.3.1 Mathematical Formulation 724.3.2 Energy Efficiency Utility Function 734.4 Hierarchical Uplink Transmission Power Control Scheme 754.4.1 DGD Level Game 764.4.2 BGD Level Game 774.5 Analysis of the Proposed Schemes 784.5.1 Estimation of B and D 784.5.2 Analysis of the Proposed Stackelberg Game 804.5.3 Algorithms to Approach NE and SE 844.6 Numerical Results 854.6.1 Simulation Settings 854.6.2 Estimate of D and B 864.6.3 Data Rate Reliability Evaluation 874.6.4 Evaluation of the Proposed Algorithms to Achieve NE and SE 884.7 Summary 905 Design and Analysis of a Wireless Monitoring Network for Transmission Lines in the Smart Grid 915.1 Background and Related Work 915.1.1 Background and Motivation 915.1.2 Related Work 935.2 Network Model 945.3 Problem Formulation 965.4 Proposed Power Allocation Schemes 995.4.1 Minimizing Total Power Usage 1005.4.2 Maximizing Power Efficiency 1015.4.3 Uniform Delay 1045.4.4 Uniform Transmission Rate 1045.5 Distributed Power Allocation Schemes 1055.6 Numerical Results and A Case Study 1075.6.1 Simulation Settings 1075.6.2 Comparison of the Centralized Schemes 1085.6.3 Case Study 1135.7 Summary 1136 A Real-Time Information-Based Demand-Side Management System 1156.1 Background and Related Work 1156.1.1 Background 1156.1.2 Related Work 1176.2 System Model 1186.2.1 The Demand-Side Power Management System 1186.2.2 Mathematical Modeling 1206.2.3 Energy Cost and Unit Price 1226.3 Centralized DR Approaches 1246.3.1 Minimize Peak-to-Average Ratio 1246.3.2 Minimize Total Cost of Power Generation 1256.4 Game Theoretical Approaches 1286.4.1 Formulated Game 1286.4.2 Game Theoretical Approach 1: Locally Computed Smart Pricing 1296.4.3 Game Theoretical Approach 2: Semifixed Smart Pricing 1316.4.4 Mixed Approach: Mixed GA1 and GA2 1326.5 Precision and Truthfulness of the Proposed DR System 1326.6 Numerical and Simulation Results 1326.6.1 Settings 1326.6.2 Comparison of P1, P2 and GA1 1356.6.3 Comparison of Different Distributed Approaches 1366.6.4 The Impact from Energy Storage Unit 1416.6.5 The Impact from Increasing Renewable Energy 1436.7 Summary 1457 Intelligent Charging for Electric Vehicles—Scheduling in Battery Exchanges Stations 1477.1 Background and Related Work 1477.1.1 Background and Overview 1477.1.2 Related Work 1497.2 System Model 1507.2.1 Overview of the Studied System 1507.2.2 Mathematical Formulation 1517.2.3 Customer Estimation 1527.3 Load Scheduling Schemes for BESs 1547.3.1 Constraints for a BES si 1547.3.2 Minimizing PAR: Problem Formulation and Analysis 1567.3.3 Problem Formulation and Analysis for Minimizing Costs 1567.3.4 Game Theoretical Approach 1597.4 Simulation Analysis and Results 1617.4.1 Settings for the Simulations 1617.4.2 Impact of the Proposed DSM on PAR 1637.4.3 Evaluation of BESs Equipment Settings 1647.4.3.1 Number of Charging Ports 1647.4.3.2 Maximum Number of Fully Charged Batteries 1647.4.3.3 Preparation at the Beginning of Each Day 1657.4.3.4 Impact on PAR from BESs 1667.4.4 Evaluations of the Game Theoretical Approach 1677.5 Summary 1698 Big Data Analytics and Cloud Computing in the Smart Grid 1718.1 Background and Motivation 1718.1.1 Big Data Era 1718.1.2 The Smart Grid and Big Data 1738.2 Pricing and Energy Forecasts in Demand Response 1748.2.1 An Overview of Pricing and Energy Forecasts 1748.2.2 A Case Study of Energy Forecasts 1768.3 Attack Detection 1798.3.1 An Overview of Attack Detection in the Smart Grid 1798.3.2 Current Problems and Techniques 1808.4 Cloud Computing in the Smart Grid 1828.4.1 Basics of Cloud Computing 1828.4.2 Advantages of Cloud Computing in the Smart Grid 1838.4.3 A Cloud Computing Architecture for the Smart Grid 1848.5 Summary 1859 A Secure Data Learning Scheme for Big Data Applications in the Smart Grid 1879.1 Background and Related Work 1879.1.1 Motivation and Background 1879.1.2 Related Work 1899.2 Preliminaries 1909.2.1 Classic Centralized Learning Scheme 1909.2.2 Supervised Learning Models 1919.2.2.1 Supervised Regression Learning Model 1919.2.2.2 Regularization Term 1919.2.3 Security Model 1929.3 Secure Data Learning Scheme 1939.3.1 Data Learning Scheme 1939.3.2 The Proposed Security Scheme 1949.3.2.1 Privacy Scheme 1949.3.2.2 Identity Protection 1959.3.3 Analysis of the Learning Process 1979.3.4 Analysis of the Security 1979.4 Smart Metering Data Set Analysis—A Case Study 1989.4.1 Smart Grid AMI and Metering Data Set 1989.4.2 Regression Study 2009.5 Conclusion and Future Work 20310 Security Challenges in the Smart Grid Communication Infrastructure 20510.1 General Security Challenges 20510.1.1 Technical Requirements 20510.1.2 Information Security Domains 20710.1.3 Standards and Interoperability 20710.2 Logical Security Architecture 20710.2.1 Key Concepts and Assumptions 20710.2.2 Logical Interface Categories 20910.3 Network Security Requirements 21010.3.1 Utility-Owned Private Networks 21010.3.2 Public Networks in the Smart Grid 21210.4 Classification of Attacks 21310.4.1 Component-Based Attacks 21310.4.2 Protocol-Based Attacks 21410.5 Existing Security Solutions 21510.6 Standardization and Regulation 21610.6.1 Commissions and Considerations 21710.6.2 Selected Standards 21710.7 Summary 21911 Security Schemes for AMI Private Networks 22111.1 Preliminaries 22111.1.1 Security Services 22111.1.2 Security Mechanisms 22211.1.3 Notations of the Keys Used in This Chapter 22311.2 Initial Authentication 22311.2.1 An Overview of the Proposed Authentication Process 22311.2.1.1 DAP Authentication Process 22411.2.1.2 Smart Meter Authentication Process 22511.2.2 The Authentication Handshake Protocol 22611.2.3 Security Analysis 22911.3 Proposed Security Protocol in Uplink Transmissions 23011.3.1 Single-Traffic Uplink Encryption 23111.3.2 Multiple-Traffic Uplink Encryption 23211.3.3 Decryption Process in Uplink Transmissions 23311.3.4 Security Analysis 23511.4 Proposed Security Protocol in Downlink Transmissions 23511.4.1 Broadcast Control Message Encryption 23611.4.2 One-to-One Control Message Encryption 23611.4.3 Security Analysis 23711.5 Domain Secrets Update 23811.5.1 AS Public/Private Keys Update 23811.5.2 Active Secret Key Update 23811.5.3 Preshared Secret Key Update 23911.6 Summary 23912 Security Schemes for Smart Grid Communications over Public Networks 24112.1 Overview of the Proposed Security Schemes 24112.1.1 Background and Motivation 24112.1.2 Applications of the Proposed Security Schemes in the Smart Grid 24212.2 Proposed ID-Based Scheme 24412.2.1 Preliminaries 24412.2.2 Identity-Based Signcryption 24512.2.2.1 Setup 24512.2.2.2 Keygen 24512.2.2.3 Signcryption 24612.2.2.4 Decryption 24612.2.2.5 Verification 24612.2.3 Consistency of the Proposed IBSC Scheme 24712.2.4 Identity-Based Signature 24712.2.4.1 Signature 24812.2.4.2 Verification 24812.2.5 Key Distribution and Symmetrical Cryptography 24812.3 Single Proxy Signing Rights Delegation 24912.3.1 Certificate Distribution by the Local Control Center 24912.3.2 Signing Rights Delegation by the PKG 25012.3.3 Single Proxy Signature 25012.4 Group Proxy Signing Rights Delegation 25112.4.1 Certificate Distribution 25112.4.2 Partial Signature 25112.4.3 Group Signature 25112.5 Security Analysis of the Proposed Schemes 25212.5.1 Assumptions for Security Analysis 25212.5.2 Identity-Based Encryption Security 25312.5.2.1 Security Model 25312.5.2.2 Security Analysis 25312.5.3 Identity-Based Signature Security 25512.5.3.1 Security Models 25512.5.3.2 Security Analysis 25612.6 Performance Analysis of the Proposed Schemes 25812.6.1 Computational Complexity of the Proposed Schemes 25812.6.2 Choosing Bilinear Paring Functions 25912.6.3 Numerical Results 26012.7 Conclusion 26113 Open Issues and Possible Future Research Directions 26313.1 Efficient and Secure Cloud Services and Big Data Analytics 26313.2 Quality-of-Service Framework 26313.3 Optimal Network Design 26413.4 Better Involvement of Green Energy 26513.5 Need for Secure Communication Network Infrastructure 26513.6 Electrical Vehicles 265Reference 267Index 287