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E-grāmata: Transportation and Power Grid in Smart Cities - Communication Networks and Services: Communication Networks and Services [Wiley Online]

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  • Formāts: 688 pages
  • Izdošanas datums: 07-Dec-2018
  • Izdevniecība: John Wiley & Sons Inc
  • ISBN-10: 1119360129
  • ISBN-13: 9781119360124
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Transportation and Power Grid in Smart Cities - Communication Networks and Services: Communication Networks and ServicesPalielināt
  • Formāts: 688 pages
  • Izdošanas datums: 07-Dec-2018
  • Izdevniecība: John Wiley & Sons Inc
  • ISBN-10: 1119360129
  • ISBN-13: 9781119360124
Citas grāmatas par šo tēmu:
Wiley Online E-booksMore info about Wiley Online
Rokasgrāmatas mājas lapa: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119360124

With the increasing worldwide trend in population migration into urban centers, we are beginning to see the emergence of the kinds of mega-cities which were once the stuff of science fiction. It is clear to most urban planners and developers that accommodating the needs of the tens of millions of inhabitants of those megalopolises in an orderly and uninterrupted manner will require the seamless integration of and real-time monitoring and response services for public utilities and transportation systems. Part speculative look into the future of the world’s urban centers, part technical blueprint, this visionary book helps lay the groundwork for the communication networks and services on which tomorrow’s “smart cities” will run.

Written by a uniquely well-qualified author team, this book provides detailed insights into the technical requirements for the wireless sensor and actuator networks required to make smart cities a reality.
List of Contributors xxi
Preface xxvii
Section I: Communication Technologies for Smart Cities 1(170)
1 Energy-Harvesting Cognitive Radios in Smart Cities
3(18)
Mustafa Ozger
Oktay Cetinkaya
Ozgur B. Akan
1.1 Introduction
3(3)
1.1.1 Cognitive Radio
5(1)
1.1.2 Cognitive Radio Sensor Networks
5(1)
1.1.3 Energy Harvesting and Energy-Harvesting Sensor Networks
6(1)
1.2 Motivations for Using Energy-Harvesting Cognitive Radios in Smart Cities
6(2)
1.2.1 Motivations for Spectrum-Aware Communications
7(1)
1.2.2 Motivations for Self-Sustaining Communications
7(1)
1.3 Challenges Posed by Energy-Harvesting Cognitive Radios in Smart Cities
8(1)
1.4 Energy-Harvesting Cognitive Internet of Things
9(5)
1.4.1 Definition
9(1)
1.4.2 Energy-Harvesting Methods in IoT
10(2)
1.4.3 System Architecture
12(1)
1.4.4 Integration of Energy-Harvesting Cognitive Radios with the Internet
13(1)
1.5 A General Framework for EH-CRs in the Smart City
14(4)
1.5.1 Operation Overview
14(1)
1.5.2 Node Architecture
15(1)
1.5.3 Network Architecture
16(1)
1.5.4 Application Areas
17(1)
1.6 Conclusion
18(1)
References
18(3)
2 LTE-D2D Communication for Power Distribution Grid: Resource Allocation for Time-Critical Applications
21(48)
Leonardo D. Oliveira
Taufik Abrao
Ekram Hossain
2.1 Introduction
21(1)
2.2 Communication Technologies for Power Distribution Grid
22(5)
2.2.1 An Overview of Smart Grid Architecture
22(2)
2.2.2 Communication Technologies for SG Applications Outside Substations
24(2)
2.2.3 Communication Networks for SG
26(1)
2.3 Overview of Communication Protocols Used in Power Distribution Networks
27(9)
2.3.1 Modbus
27(2)
2.3.2 IEC 60870
29(2)
2.3.3 DNP3
31(1)
2.3.4 IEC 61850
32(3)
2.3.5 SCADA Protocols for Smart Grid: Existing State-of-the-Art
35(1)
2.4 Power Distribution System: Distributed Automation Applications and Requirements
36(4)
2.4.1 Distributed Automation Applications
36(1)
2.4.1.1 Voltage/Var Control (VVC)
37(1)
2.4.1.2 Fault Detection, Isolation, and Restoration (FDCIR)
38(1)
2.4.2 Requirements for Distributed Automation Applications
39(1)
2.5 Analysis of Data Flow in Power Distribution Grid
40(7)
2.5.1 Model for Power Distribution Grid
40(2)
2.5.2 IEC 61850 Traffic Model
42(1)
2.5.2.1 Cyclic Data Flow
42(1)
2.5.2.2 Stochastic Data Flow
45(1)
2.5.2.3 Burst Data Flow
46(1)
2.6 LTE-D2D for DA: Resource Allocation for Time-Critical Applications
47(13)
2.6.1 Overview of LTE
47(1)
2.6.2 IEC 61850 Protocols over LTE
48(1)
2.6.2.1 Mapping MMS over LTE
49(1)
2.6.2.2 Mapping GOOSE over LTE
50(1)
2.6.3 Resource Allocation in uplink LTE-D2D for DA Applications
50(1)
2.6.3.1 Problem Formulation
51(1)
2.6.3.2 Scheduler Design
54(1)
2.6.3.3 Numerical Evaluation
55(5)
2.7 Conclusion
60(1)
References
61(8)
3 5G and Cellular Networks in the Smart Grid
69(34)
Jimmy Jessen Nielsen
Ljupco Jorguseski
Haibin Zhang
Herve Ganem
Ziming Zhu
Petar Popovski
3.1 Introduction
69(2)
3.1.1 Massive MTC
70(1)
3.1.2 Mission-Critical MTC
70(1)
3.1.3 Secure Mission-Critical MTC
71(1)
3.2 From Power Grid to Smart Grid
71(3)
3.3 Smart Grid Communication Requirements
74(2)
3.3.1 Traffic Models and Requirements
74(2)
3.4 Unlicensed Spectrum and Non-3GPP Technologies for the Support of Smart Grid
76(6)
3.4.1 IEEE 802.11ah
76(3)
3.4.2 Sigfox's Ultra-Narrow Band (UNB) Approach
79(1)
3.4.3 LoRa™ Chirp Spread Spectrum Approach
80(2)
3.5 Cellular and 3GPP Technologies for the Support of Smart Grid
82(12)
3.5.1 Limits of 3GPP Technologies up to Release 11
82(1)
3.5.2 Recent Enhancements of 3GPP Technologies for IoT Applications (Releases 12-13)
83(1)
3.5.2.1 LTE Cat-0 and Cat-M1 devices
84(1)
3.5.2.2 Narrow-Band Internet of Things (NB-IoT) and Cat-NB1 Devices
85(1)
3.5.3 Performance of Cellular LTE Systems for Smart Grids
86(1)
3.5.4 LTE Access Reservation Protocol Limitations
87(1)
3.5.4.1 LTE Access Procedure
87(1)
3.5.4.2 Connection Establishment
90(1)
3.5.4.3 Numerical Evaluation of LTE Random Access Bottlenecks
91(2)
3.5.5 What Can We Expect from 5G?
93(1)
3.6 End-to-End Security in Smart Grid Communications
94(5)
3.6.1 Network Access Security
95(1)
3.6.2 Transport Level Security
96(1)
3.6.3 Application Level Security
96(1)
3.6.4 End-to-End Security
96(1)
3.6.5 Access Control
97(2)
3.7 Conclusions and Summary
99(1)
References
100(3)
4 Machine-to-Machine Communications in the Smart City-a Smart Grid Perspective
103(44)
Ravil Bikmetov
M. Yasin Akhtar Raja
Khurram Kazi
4.1 Introduction
103(2)
4.2 Architecture and Characteristics of Smart Grids for Smart Cities
105(15)
4.2.1 Definition of a Smart Grid and Its Conceptual Model
106(6)
4.2.2 Standardization Approach in Smart Grids
112(1)
4.2.3 Smart Grid Interoperability Reference Model (SGIRM)
113(1)
4.2.4 Smart Grid Architecture Model
114(1)
4.2.5 Energy Sources in the Smart Grid
115(2)
4.2.6 Energy Consumers in a Smart Grid
117(2)
4.2.7 Energy Service Providers in the Smart Grid
119(1)
4.3 Intelligent Machine-to-Machine Communications in Smart Grids
120(12)
4.3.1 Reference Architecture of Machine-to-Machine Interactions
120(1)
4.3.2 Communication Media and Protocols
121(5)
4.3.3 Layered Structure of Machine-to-Machine Communications
126(6)
4.4 Optimization Algorithms for Energy Production, Distribution, and Consumption
132(2)
4.5 Machine Learning Techniques in Efficient Energy Services and Management
134(1)
4.6 Future Perspectives
135(1)
4.7 Appendix
136(2)
References
138(9)
5 5G and D2D Communications at the Service of Smart Cities
147(24)
Muhammad Usman
Muhammad Rizwan Asghar
Fabrizio Granelli
5.1 Introduction
147(3)
5.2 Literature Review
150(3)
5.3 Smart City Scenarios
153(7)
5.3.1 Public Health
154(1)
5.3.2 Transportation and Environment
155(2)
5.3.3 Energy Efficiency
157(1)
5.3.4 Smart Grid
157(1)
5.3.5 Water Management
158(1)
5.3.6 Disaster Response and Emergency Services
159(1)
5.3.7 Public Safety and Security
159(1)
5.4 Discussion
160(3)
5.4.1 Multiple Radio Access Technologies (Multi-RAT)
160(1)
5.4.2 Virtualization
160(1)
5.4.3 Distributed/Edge Computing
161(1)
5.4.4 D2D Communication
161(1)
5.4.5 Big Data
162(1)
5.4.6 Security and Privacy
163(1)
5.5 Conclusion
163(1)
References
163(8)
Section II: Emerging Communication Networks for Smart Cities 171(120)
6 Software Defined Networking and Virtualization for Smart Grid
173(18)
Hakki C. Cankaya
6.1 Introduction
173(1)
6.2 Current Status of Power Grid and Smart Grid Modernization
174(3)
6.2.1 Smart Grid
174(3)
6.3 Network Softwarerization in Smart Grids
177(6)
6.3.1 Software Defined Networking (SDN) as Next-Generation Software-Centric Approach to Telecommunications Networks
177(2)
6.3.2 Adaptation of SDN for Smart Grid and City
179(1)
6.3.3 Opportunities for SDN in Smart Grid
179(4)
6.4 Virtualization for Networks and Functions
183(2)
6.4.1 Network Virtualization
183(1)
6.4.2 Network Function Virtualization
184(1)
6.5 Use Cases of SDN/NFV in the Smart Grid
185(2)
6.6 Challenges and Issues with SDN/NFV-Based Smart Grid
187(1)
6.7 Conclusion
187(1)
References
188(3)
7 GHetNet: A Framework Validating Green Mobile Femtocells in Smart-Grids
191(26)
Fadi Al-Turjman
7.1 Introduction
191(1)
7.2 Related Work
192(5)
7.2.1 Static Validation Techniques
194(1)
7.2.2 Dynamic Validation Techniques
195(2)
7.3 System Models
197(4)
7.3.1 Markov Model
199(1)
7.3.2 Service-Rate Model
199(1)
7.3.3 Communication Model
200(1)
7.4 The Green HetNet (GHetNet) Framework
201(5)
7.5 A Case Study: E-Mobility for Smart Grids
206(7)
7.5.1 Performance metrics and parameters
207(1)
7.5.2 Simulation Setups and Baselines
208(1)
7.5.3 Results and Discussion
208(1)
7.5.3.1 The Impact of Velocity on FBS Performance
209(1)
7.5.3.2 The Impact of the Grid Load on Energy Consumption
211(2)
7.6 Conclusion
213(1)
References
213(4)
8 Communication Architectures and Technologies for Advanced Smart Grid Services
217(30)
Francois Lemercier
Guillaume Habault
Georgios Z. Papadopoulos
Patrick Maille
Nicolas Montavont
Periklis Chatzimisios
8.1 Introduction
217(2)
8.2 The Smart Grid Communication Architecture and Infrastructure
219(12)
8.2.1 DSO-Based Communications
220(1)
8.2.1.1 The Existing AMI Organization
220(1)
8.2.1.2 Communication Technologies used in the AMI
222(1)
8.2.1.3 AMI Limitations
223(1)
8.2.2 Internet-Based Architectures
224(1)
8.2.2.1 IP-Based Architecture Limitations
225(1)
8.2.3 Next-Generation Smart Grid Architecture
225(1)
8.2.3.1 Technical Issues for Next-Generation Smart Grids
227(1)
8.2.3.2 Handing Back the Keys to the User: Energy Management Should Be Separated from the Smart Meter
227(1)
8.2.3.3 To Build an Open Market, Use an Open Network
228(1)
8.2.3.4 Multi-Level Aggregation
228(1)
8.2.3.5 Security Concerns
229(1)
8.2.3.6 Ongoing Research Efforts
229(2)
8.3 Routing Information in the Smart Grid
231(11)
8.3.1 Routing Family of Protocols
231(1)
8.3.1.1 Proactive Routing Protocol
232(1)
8.3.1.2 Topology Management under RPL
232(1)
8.3.1.3 Routing Table Maintenance under RPL
233(1)
8.3.1.4 Routing Strategy: Metrics and Constraints
234(1)
8.3.1.5 Path Computation under RPL
234(1)
8.3.1.6 Summary of the RPL DODAG construction
235(1)
8.3.1.7 Reactive Routing Protocol
236(1)
8.3.1.8 Topology Management under AODV
237(1)
8.3.2 Reactive Routing Protocol in a Constrained Network
238(1)
8.3.2.1 Performance Evaluation
239(1)
8.3.2.2 Summary on Routing Protocols
241(1)
8.4 Conclusion
242(1)
References
243(4)
9 Wireless Sensor Networks in Smart Cities: Applications of Channel Bonding to Meet Data Communication Requirements
247(22)
Syed Hashim Raza Bukhari
Sajid Siraj
Mubashir Husain Rehmani
9.1 Introduction, Basics, and Motivation
247(1)
9.2 WSNs in Smart Cities
248(5)
9.2.1 WSNs in Underground Transportation
249(1)
9.2.2 WSNs in Smart Cab Services
249(1)
9.2.3 WSNs in Waste Management Systems
249(1)
9.2.4 WSNs in Atmosphere Health Monitoring
249(3)
9.2.5 WSNs in Smart Grids
252(1)
9.2.6 WSNs in Weather Forecasting
252(1)
9.2.7 WSNs in Home Automation
252(1)
9.2.8 WSNs in Structural Health Monitoring
252(1)
9.3 Channel Bonding
253(5)
9.3.1 Channel Bonding Schemes in Traditional Networks
253(1)
9.3.2 Channel Bonding Schemes in Wireless Sensor Networks
254(1)
9.3.3 Channel Bonding Schemes in Cognitive Radio Networks
255(2)
9.3.4 Channel Bonding for Cognitive Radio Sensor Networks
257(1)
9.4 Applications of Channel Bonding in CRSN-Based Smart Cities
258(1)
9.4.1 CRSNs in Smart Health Care
258(1)
9.4.2 CRSNs in M2M Communications
258(1)
9.4.3 CRSNs Multiple Concurrent Deployments in Smart Cities
259(1)
9.4.4 CRSNs in Smart Home Applications
259(1)
9.4.5 CRSNs Smart Environment Control
259(1)
9.4.6 CRSNs-Based IoT
259(1)
9.5 Issues and Challenges Regarding the Implementation of Channel Bonding in Smart Cities
259(2)
9.5.1 Privacy of Citizens
260(1)
9.5.2 Energy Conservation
260(1)
9.5.3 Data Storage and Aggregation
260(1)
9.5.4 Geographic Awareness and Adaptation
260(1)
9.5.5 Interference and Spectrum Issues
260(1)
9.6 Conclusion
261(1)
References
261(8)
10 A Prediction Module for Smart City loT Platforms
269(22)
Sema F. Oktug
Yusuf Yaslan
Halil Gulacar
10.1 Introduction
269(2)
10.2 IoT Platforms for Smart Cities
271(6)
10.2.1 ARM Mbed
271(1)
10.2.2 Cumulocity
271(2)
10.2.3 DeviceHive
273(1)
10.2.4 Digi
273(1)
10.2.5 Digital Service Cloud
274(1)
10.2.6 FiWare
274(1)
10.2.7 Global Sensor Networks (GSN)
274(1)
10.2.8 IoTgo
274(1)
10.2.9 Kaa
275(1)
10.2.10 Nimbits
275(1)
10.2.11 RealTime.io
275(1)
10.2.12 SensorCloud
275(1)
10.2.13 SiteWhere
276(1)
10.2.14 TempoIQ
276(1)
10.2.15 Thinger.io
276(1)
10.2.16 Thingsquare
276(1)
10.2.17 ThingWorx
277(1)
10.2.18 VITAL
277(1)
10.2.19 Xively
277(1)
10.3 Prediction Module Developed
277(4)
10.3.1 The VITAL IoT Platform
278(1)
10.3.2 VITAL Prediction Module
278(3)
10.4 A Use Case Employing the Traffic Sensors in Istanbul
281(7)
10.4.1 Prediction Techniques Employed
282(1)
10.4.1.1 Data Preprocessing
284(1)
10.4.1.2 Feature Vectors
284(1)
10.4.2 Results
285(1)
10.4.2.1 Regression Results
286(2)
10.5 Conclusion
288(1)
Acknowledgment
288(1)
References
289(2)
Section III: Renewable Energy Resources and Microgrid in Smart Cities 291(120)
11 Integration of Renewable Energy Resources in the Smart Grid: Opportunities and Challenges
293(34)
Mohammad Upal Mahfuz
Ahmed O. Nasif
Md Maruf Hossain
Md. Abdur Rahman
11.1 Introduction
293(1)
11.2 The Smart Grid Paradigm
294(4)
11.2.1 The Smart Grid Concept
294(2)
11.2.2 System Components of the SG
296(2)
11.3 Renewable Energy Integration in the Smart Grid
298(1)
11.3.1 Resource Characteristics and Distributed Generation
298(1)
11.3.2 Why Is Integration Necessary?
299(1)
11.4 Opportunities and Challenges
299(15)
11.4.1 Energy Storage (ES)
300(1)
11.4.1.1 Key Energy Storage Technologies
300(1)
11.4.1.2 Key Energy Storage Challenges in SG
301(1)
11.4.2 Distributed Generation (DG)
302(1)
11.4.2.1 Key DG Sources and Generators
303(1)
11.4.2.2 Key Parts and Functions of a DG System and Its Distribution
303(1)
11.4.2.3 DG and Dispatch Challenges
304(1)
11.4.3 Resource Forecasting, Modeling, and Scheduling
305(1)
11.4.3.1 Resource Modeling and Scheduling
305(1)
11.4.3.2 Resource Forecasting (RF)
307(1)
11.4.4 Demand Response
308(1)
11.4.5 Demand-Side Management (DSM)
309(1)
11.4.6 Monitoring
310(1)
11.4.7 Transmission Techniques
311(1)
11.4.8 System-Related Challenges
311(1)
11.4.9 V2G Challenges
312(2)
11.4.10 Security Challenges in the High Penetration of RE Resources
314(1)
11.5 Case Studies
314(1)
11.6 Conclusion
315(1)
References
316(11)
12 Environmental Monitoring for Smart Buildings
327(28)
Petros Spachos
Konstantinos Plataniotis
12.1 Introduction
327(2)
12.2 Wireless Sensor Networks in Monitoring Applications
329(1)
12.3 Application Requirements and Challenges
330(8)
12.3.1 Monitoring Area
330(2)
12.3.2 Application Scenario and Design Goal
332(1)
12.3.3 Requirements
333(1)
12.3.3.1 Sensor Type
333(1)
12.3.3.2 Real-Time Data Aggregation
335(1)
12.3.3.3 Scalability
335(1)
12.3.3.4 Usability, Autonomy, and Reliability
336(1)
12.3.3.5 Remote Management
336(1)
12.3.4 Challenges
336(1)
12.3.4.1 Power Management
336(1)
12.3.4.2 Wireless Network Coexistence
337(1)
12.3.4.3 Mesh Routing
337(1)
12.3.4.4 Robustness
337(1)
12.3.4.5 Dynamic Changes
337(1)
12.3.4.6 Flexibility
337(1)
12.3.4.7 Size and cost
337(1)
12.4 Wireless Sensor Network Architecture
338(5)
12.4.1 Framework
338(1)
12.4.2 Hardware Infrastructure
339(2)
12.4.3 Data Processing
341(1)
12.4.3.1 Noise Reduction, Data Smoothing, and Calibration
341(1)
12.4.3.2 Packet formation process
342(1)
12.4.3.3 Information Processing and Storage
343(1)
12.4.4 Indoor Monitoring System
343(1)
12.5 Experiments and Results
343(7)
12.5.1 Experimental Setup
343(4)
12.5.2 Results Analysis
347(3)
12.6 Conclusions
350(1)
References
350(5)
13 Cooperative Energy Management in Microgrids
355(16)
Ioannis Zenginis
John Vardakas
Prodromos-Vasileios Mekikis
Christos Verikoukis
13.1 Introduction
355(2)
13.2 The Cooperative Energy Management System Model
357(5)
13.2.1 PV Panel Modeling
359(1)
13.2.2 Energy Storage System
360(1)
13.2.3 Inverter
361(1)
13.2.4 Microgrid Energy Exchange
361(1)
13.3 Evaluation and Discussion
362(4)
13.4 Conclusion
366(1)
Acknowledgment
367(1)
References
368(3)
14 Optimal Planning and Performance Assessment of Multi-Microgrid Systems in Future Smart Cities
371(40)
Shouxiang Wang
Lei Wu
Qi Liu
Shengxia Cai
14.1 Optimal Planning of Multi-Microgrid Systems
372(12)
14.1.1 Introduction
372(1)
14.1.2 Optimal Structure Planning
373(1)
14.1.2.1 Definition of Indices
373(1)
14.1.2.2 Structure Planning Method
375(2)
14.1.3 Optimal Capacity Planning
377(1)
14.1.3.1 Definition of Indexes
377(1)
14.1.3.2 Capacity Planning Method
381(3)
14.1.4 Conclusions
384(1)
14.2 Performance Assessment of Multi-Microgrid System
384(22)
14.2.1 Introduction
384(2)
14.2.2 Comprehensive Evaluation Indexes
386(1)
14.2.2.1 MMGS Source-Charge Capacity Index
386(1)
14.2.2.2 MMGS Energy Interaction Index
388(1)
14.2.2.3 MMGS Reliability Index
390(1)
14.2.2.4 MMGS Economics Index
395(1)
14.2.2.5 Energy Utilization Efficiency Index
398(1)
14.2.2.6 Energy Saving and Emission Reduction Index
398(1)
14.2.2.7 Renewable Energy Utilization Index
399(1)
14.2.3 Performance Assessment
400(1)
14.2.3.1 Performance Assessment of Grid-Connected MMGS
400(1)
14.2.3.2 Performance Assessment of Islanded MMGS
401(1)
14.2.3.3 Annual Performance Assessment of the MMGS
402(1)
14.2.4 Case Studies
403(1)
14.2.4.1 System Description
403(1)
14.2.4.2 Numerical Results
403(3)
14.3 Conclusions
406(1)
Acknowledgment
407(1)
References
407(4)
Section IV: Smart Cities, Intelligent Transportation System and Electric Vehicles 411(96)
15 Wireless Charging for Electric Vehicles in the Smart Cities: Technology Review and Impact
413(14)
Alicia Trivino-Cabrera
Jose A. Aguado
15.1 Introduction
413(2)
15.2 Review of the Wireless Charging Methods
415(3)
15.2.1 Technologies Supporting Wireless Power Transfer for EVs
415(1)
15.2.2 Operation Modes for Wireless Power Transfer in EVs
416(2)
15.3 Electrical Effect of Charging Technologies on the Grid
418(3)
15.3.1 Harmonics Control in EV Wireless Chargers
418(1)
15.3.2 Power Factor Control in EV Wireless Chargers
419(1)
15.3.3 Implementation of Bidirectionality in EV Wireless Chargers
420(1)
15.3.4 Discussion
421(1)
15.4 Scheduling Considering Charging Technologies
421(2)
15.5 Conclusions and Future Guidelines
423(1)
References
424(3)
16 Channel Access Modelling for EV Charging/Discharging Service through Vehicular ad hoc Networks (VANETs) Communications
427(16)
Dhaou Said
Hussein T. Mouftah
16.1 Introduction
428(1)
16.2 Technical Environment of the EV Charging/Discharging Process
428(2)
16.2.1 EVSE Overview
429(1)
16.2.2 Inductive Chargers: Opportunities and Potential
429(1)
16.3 Overview of Communication Technologies in the Smart Grid
430(2)
16.3.1 Power Line Communication
430(1)
16.3.2 Wireless Communications for EV-Smart Grid Applications
431(1)
16.4 Channel Access Model for EV Charging Service
432(8)
16.4.1 Overview of VANET and LTE
432(1)
16.4.2 Case Study: Access Channel Model
433(5)
16.4.3 Simulations Results
438(2)
16.5 Conclusions
440(1)
References
440(3)
17 Intelligent Parking Management in Smart Cities
443(42)
Sanket Gupte
Mohamed Younis
17.1 Introduction
443(2)
17.2 Design Issues and Taxonomy of Parking Solutions
445(2)
17.2.1 Design Issues for Autonomous Parking Systems
445(1)
17.2.2 Taxonomy of Parking Solutions
445(2)
17.3 Classification of Existing Parking Systems
447(18)
17.3.1 Sensing Infrastructure
447(10)
17.3.2 Communication Infrastructure
457(3)
17.3.3 Storage Infrastructure
460(1)
17.3.4 Application Infrastructure
461(2)
17.3.5 User Interfacing
463(2)
17.3.6 Comparison of Existing Parking Systems
465(1)
17.4 Participatory Sensing-Based Smart Parking
465(14)
17.4.1 The Components
467(1)
17.4.1.1 Users
467(1)
17.4.1.2 IoT Devices
467(1)
17.4.1.3 Server
468(1)
17.4.1.4 Parking Spots
468(1)
17.4.2 Parking Management Application
469(1)
17.4.2.1 User Interface
469(1)
17.4.2.2 Smart Reporting System
470(1)
17.4.2.3 Leaderboard
470(1)
17.4.2.4 Rewards Store
471(1)
17.4.2.5 Enforcement and Compliance
472(1)
17.4.2.6 External Integration
472(1)
17.4.3 Data Processing and Cloud Support
472(1)
17.4.3.1 Availability Computation
472(1)
17.4.3.2 Reputation System
473(1)
17.4.3.3 Scoring System
474(1)
17.4.3.4 Reservation Model
474(1)
17.4.3.5 Analysis and Learning
474(1)
17.4.4 Implementation and Performance Evaluation
474(1)
17.4.4.1 Prototype Application
474(1)
17.4.4.2 Experiment Setup
475(1)
17.4.4.3 Simulation Results
475(2)
17.4.5 Features and Benefits
477(2)
17.5 Conclusions and Future Advancements
479(1)
References
480(5)
18 Electric Vehicle Scheduling and Charging in Smart Cities
485(22)
Muhammmad Amjad
Mubashir Husain Rehmani
Tariq Umer
18.1 Introduction
485(3)
18.1.1 Integration of EVs into Smart Cities
486(1)
18.1.1.1 Enhancing the Existing Power Capacity
486(1)
18.1.1.2 Designing the Communication Protocols to Support the Smart Recharging Structure
486(1)
18.1.1.3 Development of a Well-designed Recharging Architecture
486(1)
18.1.1.4 Considering the Expected Load on the Smart Grid
486(1)
18.1.1.5 Need for Scheduling Approaches for EVs Recharging
486(1)
18.1.2 Main Contributions
487(1)
18.1.3 Organization of the
Chapter
487(1)
18.2 Smart Cities and Electric Vehicles: Motivation, Background, and Application Scenarios
488(3)
18.2.1 Smart Cities: An Overview
488(1)
18.2.1.1 Provision of Smart Transportation
488(1)
18.2.1.2 Energy Management in Smart cities
488(1)
18.2.1.3 Integration of the Economic and Business Model
488(1)
18.2.1.4 Wireless Communication Needs/Communication Architectures for Smart Cities
489(1)
18.2.1.5 Traffic Congestion Avoidance in Smart Cities
489(1)
18.2.1.6 Support of Heterogeneous Technologies in Smart Cities
489(1)
18.2.1.7 Green Applications Support in Smart Cities
489(1)
18.2.1.8 Security and Privacy in Smart Cities
490(1)
18.2.2 Motivation of Using EVs in Smart cities
490(1)
18.2.3 Application Scenarios
490(1)
18.2.3.1 Avoiding Spinning Reserves
490(1)
18.2.3.2 V2G and G2V Capability
491(1)
18.2.3.3 CO2 Minimization
491(1)
18.2.3.4 Load Management on the Local Microgrid
491(1)
18.3 EVs Recharging Approaches in Smart Cities
491(2)
18.3.1 Centralized EVs Recharging Approach
491(1)
18.3.1.1 Main Contributions and Limitations of Centralized EVs-Recharging Approach
492(1)
18.3.2 Distributed EVs Recharging Approach
493(1)
18.3.2.1 Main Contributions and Limitations of the Distributed EVs-recharging Approach
493(1)
18.4 Scheduling EVs Recharging in Smart Cities
493(5)
18.4.1 Objectives Achieved via Different Scheduling Approaches
494(1)
18.4.1.1 Reduction of Power Losses
494(1)
18.4.1.2 Minimizing Total Cost of Energy for Users
495(1)
18.4.1.3 Maximizing Aggregator Profit
496(1)
18.4.1.4 Frequency Regulation
497(1)
18.4.1.5 Voltage regulation
497(1)
18.4.1.6 Support for Renewable Energy Sources for Recharging of EVs
497(1)
18.4.2 Resource Allocation for EVs Recharging in Smart Cities (Optimization Approaches)
498(1)
18.5 Open Issues, Challenges, and Future Research Directions
498(2)
18.5.1 Support of Wireless Power Charger
499(1)
18.5.2 Vehicle-to-Anything
499(1)
18.5.3 Energy Management for Smart Grid via EVs
499(1)
18.5.4 Advance Communication Needs for Controlled EVs Recharging
499(1)
18.5.5 EVs Control Applications
499(1)
18.5.6 Standardization for Communication Technologies Used for EVs Recharging
500(1)
18.6 Conclusion
500(1)
References
500(7)
Section V: Security and Privacy Issues and Big Data in Smart Cities 507(128)
19 Cyber-Security and Resiliency of Transportation and Power Systems in Smart Cities
509(20)
Seyedamirabbas Mousavian
Melike Erol-Kantarci
Hussein T. Mouftah
19.1 Introduction
509(1)
19.2 EV Infrastructure and Smart Grid Integration
510(2)
19.3 System Model
512(1)
19.3.1 Model Definition and Assumptions
512(1)
19.4 Estimating the Threat Levels in the EVSE Network
513(1)
19.5 Response Model
514(1)
19.6 Propagation Impacts on Power System Operations
515(10)
19.6.1 Cyberattack Propagation in PMU Networks
515(1)
19.6.2 Threat Level Estimation in PMU Networks
515(3)
19.6.3 Response Model in PMU Networks
518(3)
19.6.4 PMU Networks: Experimental Results
521(4)
19.7 Conclusion and Open Issues
525(1)
References
525(4)
20 Protecting the Privacy of Electricity Consumers in the Smart City
529(26)
Binod Vaidya
Hussein T. Mouftah
20.1 Introduction
529(1)
20.2 Privacy in the Smart Grid
530(2)
20.2.1 Privacy Concerns over Customer Electricity Data Collected by the Utility
531(1)
20.2.2 Privacy Concerns on Energy Usage Information Collected by a Non-Utility-Owned Metering Device
532(1)
20.2.3 Privacy Protection
532(1)
20.3 Privacy Principles
532(3)
20.4 Privacy Engineering
535(5)
20.4.1 Privacy Protection Goals
535(3)
20.4.2 Privacy Engineering Framework and Guidelines
538(2)
20.5 Privacy Risk and Impact Assessment
540(2)
20.5.1 System Privacy Risk Model
540(1)
20.5.2 Privacy Impact Assessment (PIA)
541(1)
20.6 Privacy Enhancing Technologies
542(5)
20.6.1 Anonymization
544(1)
20.6.2 Trusted Computation
545(1)
20.6.3 Cryptographic Computation
545(1)
20.6.4 Perturbation
546(1)
20.6.5 Verifiable Computation
547(1)
Acknowledgment
547(1)
References
548(7)
21 Privacy Preserving Power Charging Coordination Scheme in the Smart Grid
555(22)
Ahmed Sherif
Muhammad Ismail
Marbin Pazos-Revilla
Mohamed Mahmoud
Kemal Akkaya
Erchin Serpedin
Khalid Qaraqe
21.1 Introduction
555(3)
21.1.1 Smart Grid Security Requirements
555(1)
21.1.2 Charging Coordination Security Requirement
556(2)
21.2 Charging Coordination and Privacy Preservation
558(2)
21.3 Privacy-Preserving Charging Coordination Scheme
560(7)
21.3.1 Network and Threat Models
560(1)
21.3.2 The Proposed Scheme
561(1)
21.3.2.1 Anonymous Data Submission
561(1)
21.3.2.2 Charging Coordination
565(2)
21.4 Performance Evaluation
567(5)
21.4.1 Privacy/Security Analysis
567(1)
21.4.2 Experimental Study
568(1)
21.4.2.1 Setup
568(1)
21.4.2.2 Metrics and Baselines
568(1)
21.4.2.3 Simulation Results
569(3)
21.5 Summary
572(1)
Acknowledgment
573(1)
References
573(4)
22 Securing Smart Cities Systems and Services: A Risk-Based Analytics-Driven Approach
577(14)
Mahmoud Gad
Ibrahim Abualhaol
22.1 Introduction to Cybersecurity for Smart Cities
577(2)
22.2 Smart Cities Enablers
579(1)
22.3 Smart Cities Attack Surface
580(2)
22.3.1 Attack Domains
580(1)
22.3.1.1 Communications
580(1)
22.3.1.2 Software
580(1)
22.3.1.3 Hardware
580(1)
22.3.1.4 Social Engineering
580(1)
22.3.1.5 Supply Chain
581(1)
22.3.1.6 Physical Security
581(1)
22.3.2 Attack Mechanisms
582(1)
22.4 Securing Smart Cities: A Design Science Approach
582(1)
22.5 NIST Cybersecurity Framework
583(2)
22.6 Cybersecurity Fusion Center with Big Data Analytics
585(2)
22.7 Conclusion
587(1)
22.8 Table of Abbreviations
587(1)
References
588(3)
23 Spatiotemporal Big Data Analysis for Smart Grids Based on Random Matrix Theory
591(44)
Robert Qiu
Lei Chu
Xing He
Zenan Ling
Haichun Liu
23.1 Introduction
591(5)
23.1.1 Perspective on Smart Grids
591(3)
23.1.2 The Role of Data in the Future Power Grid
594(1)
23.1.3 A Brief Account for RMT
595(1)
23.2 RMT: A Practical and Powerful Big Data Analysis Tool
596(12)
23.2.1 Modeling Grid Data using Large Dimensional Random Matrices
596(2)
23.2.2 Asymptotic Spectrum Laws
598(2)
23.2.3 Transforms
600(1)
23.2.4 Convergence Rate
601(2)
23.2.5 Free Probability
603(5)
23.3 Applications to Smart Grids
608(18)
23.3.1 Hypothesis Tests in Smart Grids
609(1)
23.3.2 Data-Driven Methods for State Evaluation
609(3)
23.3.3 Situation Awareness based on Linear Eigenvalue Statistics
612(9)
23.3.4 Early Event Detection Using Free Probability
621(5)
23.4 Conclusion and Future Directions
626(3)
References
629(6)
Index 635
HUSSEIN T. MOUFTAH, PHD, is Canada Research Chair and Distinguished University Professor, School of Electrical Engineering and Computer Science, University of Ottawa, Canada.

MELIKE EROL-KANTARCI, PHD, is Assistant Professor, School of Electrical Engineering and Computer Science, University of Ottawa, Canada.

MUBASHIR HUSAIN REHMANI, PHD, is Assistant Professor, Department of Electrical Engineering, COMSATS Institute of Information Technology, Wah Cantt, Pakistan.
Permanent link: https://www.kriso.lv/db/9781119360124_pe.html
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