Interconnected Modern Multi-Energy Networks and Intelligent Transportation Systems E-Book
96,99 €
Mehr erfahren.
- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Serie: IEEE Press Series on Power Engineering
- Sprache: Englisch
Interconnected Modern Multi-Energy Networks and Intelligent Transportation Systems A timely introduction to the revolutionary technologies reshaping the global energy market The search for more efficient and sustainable ways to meet society's energy requirements has driven recent technological innovation on an unprecedented scale. The energy needs of a growing population coupled with concerns about climate change have posed unique challenges that necessitate novel energy technologies. The transition of modern energy grids towards multi-energy networks, or MENs, promises to be a fundamental transformation in the way we energize our world. Interconnected Modern Multi-Energy Networks and Intelligent Transportation Systems presents an overview of the foundational methodologies and technologies underlying MENs and the groundbreaking vehicle systems that bring them together. With the inclusion of transformative technologies from radically different sectors, the content covered in this book will be of high value for researchers interested in future energy systems. Readers will also find: * In-depth examination of the process of switching from conventional transportation systems to modern intelligent transportation ones * Detailed discussions of topics including self-driving vehicles, hybrid energy technologies, grid-edge, and more * The introduction of a holistic, reconfigurable system adaptable to vastly different conditions and forms of network interaction Interconnected Modern Multi-Energy Networks and Intelligent Transportation Systems is useful for researchers in electrical, mechanical, civil, architectural, or environmental engineering, as well as for telecommunications researchers and for any industry professionals with an interest in energy transportation.
Sie lesen das E-Book in den Legimi-Apps auf:
Seitenzahl: 787
Veröffentlichungsjahr: 2024
Ähnliche
Table of Contents
Cover
Table of Contents
Series Page
Title Page
Copyright Page
List of Contributors
About the Editors
Preface
1 The Necessity for Modernizing the Coupled Structure of Intelligent Transportation Systems and Multi‐Energy Networks
1.1 Introduction
1.2 Applications of Intelligent Transportation Systems
1.3 Coupled Structure of ITSs and Multi‐Energy Networks
1.4 Summary
References
2 Green Transportation Systems
2.1 Introduction
2.2 History of Transportation
2.3 Transportation Expansion Issues
2.4 Definition of Green Transportation
2.5 Advantages of Green Transportation
2.6 International Agreements
2.7 Challenges to GT
2.8 Green Transportation’s Effects on Multi‐Energy Networks
2.9 Implementation Strategies for the Green Transportation System
2.10 New Technologies for Green Transportation
2.11 Intelligent Transportation System
2.12 Conclusion
References
3 Techno‐Economic‐Environmental Assessment of Green Transportation Systems
3.1 Introduction
3.2 Technologies for Green Transportation Systems
3.3 Economic Implications of Green Transportation Systems
3.4 Environmental Implications of Green Transportation Systems
3.5 Conclusion
References
4 Urban Integrated Sustainable Transportation Networks
4.1 Introduction
4.2 Necessity of Sustainable Transportation
4.3 Challenges and Opportunities Associated with the Implementation of Sustainable Transportation
4.4 Modes of Sustainable Transportation
4.5 Sustainable Transportation in Modern Urban Advancement
4.6 Infrastructure for Sustainable Transportation
4.7 Conclusion
References
5 Multi‐Energy Technologies in Green and Integrated Transportation Networks
5.1 Introduction
5.2 Definition of Green Transportation
5.3 Technological Development and Managerial Integration for Green Transportation
5.4 Definition and Features of Integrated Multi‐Energy System
5.5 Electric Vehicle Integration with Renewable Energy Sources
5.6 Hybrid Fuel Cell/Battery Vehicle Systems
5.7 Barriers and Challenges
5.8 Conclusion
References
6 Flexible Operation of Power‐To‐X Energy Systems in Transportation Networks
Table of Acronyms
6.1 Introduction
6.2 Power to Hydrogen
6.3 Power to Methane
6.4 Power to Chemical (P2C)
6.5 Power to Heat (P2H)
6.6 Power to Transport (P2T)
6.7 Power Demand Flexibility
6.8 Conclusion
References
7 Integration of Electric Vehicles into Multi‐energy Systems
Abbreviations
7.1 Introduction
7.2 Multi‐energy Systems Structure
7.3 Integration of EVs in MES
7.4 Conclusion
References
8 Self‐Driving Vehicle Systems in Intelligent Transportation Networks
8.1 Introduction
8.2 Brief History
8.3 Literature Review
8.4 Advantages and Challenges
8.5 Sensing
8.6 Perception
8.7 Planning and Control
8.8 Conclusion
Acknowledgment
References
9 Energy Storage Technologies and Control Systems for Electric Vehicles
Acronyms
9.1 Introduction
9.2 Fuel Cell
9.3 Battery Technologies for Electric Vehicles
9.4 Overview of Brushless Motor
9.5 BLDC Motor Control Strategy for Electric Vehicles
9.6 Simulation Results
9.7 Environnemental Impact of EVs
9.8 EVs and Modern Technologies
9.9 Challenges and Perspectives of EVs
9.10 Conclusion
Acknowledgments
References
10 Electric Vehicle Path Towards Sustainable Transportation: A Comprehensive Structure
Nomenclature
10.1 Introduction
10.2 Optimum Design of EVs
10.3 Characterization of EV Battery System
10.4 Control System of EVs
10.5 Reliability Assessment of EV
10.6 Assessment of EV Charging Station
10.7 Worldwide Policy Framework for EV
10.8 Electric Vehicles on the Sustainability and Reliability of Transportation Network
10.9 Recent Trends and Future Challenges
References
11 Electric Vehicle Charging Management in Parking Structures
11.1 Introduction
11.2 EV Charging Management Schemes
11.3 Fair Charging Management
11.4 Delay‐Fair Charging Management
11.5 QoS‐Fair Charging Management
11.6 Closing Remarks
Acknowledgment
References
12 Multi‐Energy Management Schemes for the Sustainability of Intelligent Interconnected Transportation Systems
Nomenclature
12.1 Introduction
12.2 History of Transportation System – Overview
12.3 Concept of IITS
12.4 Barriers to Successful Implementation of IITS
12.5 Intelligent Modern Energy Transport Systems
12.6 Role of Multi‐Energy Management Schemes for the Sustainability of Transportation Networks
12.7 Result Discussion, Current Challenges, and Future Research Opportunities
12.8 Conclusion
References
13 Blockchain‐Based Financial and Economic Analysis of Green Vehicles: Path Towards Intelligent Transportation
13.1 Introduction
13.2 Country‐Wise Financial Analysis of EVs
13.3 Key Financial Ratio for Financial Analysis of EVs
13.4 Cost Assessment of EVs with Different Parameters
13.5 Financial and Economic Analysis of Green Vehicle Infrastructure by Blockchain
13.6 Applicability of Different Blockchain Cryptocurrencies in EV Transaction
13.7 Challenges and Advantages of Using Blockchain for EVs
13.8 Conclusion
References
14 Unmanned Aerial Vehicles Toward Intelligent Transportation Systems
Abbreviations
14.1 Introduction
14.2 WSN for ITSs: The Energy Supply Issue and Existing Solutions
14.3 UAV‐Based WRSN Charging Scheme for ITSs
14.4 Challenges and Advantages of Using UAVs in WRSN‐Based ITSs
14.5 Simulation Results
14.6 Conclusions
References
15 Autonomous Vehicle Systems in Intelligent Interconnected Transportation Networks
15.1 Introduction
15.2 Related Work
15.3 Reinforcement Learning for Autonomous Driving Personalization
15.4 Federated Reinforcement Learning
15.5 Experimental Evaluation of Driving Personalization Using Federated RL
15.6 Discussion
15.7 Conclusions
Acknowledgment
References
Index
IEEE Press Series on Power and Energy Systems
End User License Agreement
List of Tables
Chapter 2
Table 2.1 Statistics on the emissions of greenhouse gases in some global ci...
Chapter 3
Table 3.1 Overview of features of different technologies for green transpor...
Table 3.2 Job opportunities in the cycling sector in Portland, Oregon, USA....
Table 3.3 Opportunities projected to be provided by green transportation gl...
Table 3.4 Carbon emissions and fuel economy comparison for some vehicle man...
Chapter 6
Table 6.1 Classification of some recent scoping studies in the transportati...
Table 6.2 Key objectives and flexibility purposes of P2H plants in recent s...
Table 6.3 Applications of hydrogen storage and production in the P2H plants...
Table 6.4 Flexibility opportunities and objectives of P2M plants for methan...
Table 6.5 Energy management objectives of power‐to‐chemical plants with key...
Chapter 8
Table 8.1 Level of driving automation proposed by SAE.
Chapter 9
Table 9.1 Comparison between different means of energy production.
Table 9.2 Characteristics of the different battery hybrid cars, their elect...
Table 9.3 BLDC parameters.
Table 9.4 Fuzzy logic controller rules set.
Table 9.5 Speed response characteristics.
Chapter 10
Table 10.1 Different technical aspects of EVs.
Table 10.2 Properties of lead‐acid and lithium‐ion battery.
Table 10.3 Assessment of different charging stations.
Table 10.4 Policy assessment of different countries.
Chapter 11
Table 11.1
W
α
(
u
) results for the optimal (ILP) and algorithmic (ACO) a...
Chapter 13
Table 13.1 Major Automaker Announcements on Electrification, 2021–2022.
Table 13.2 EBITDA of EV company.
Table 13.3 Net profit margin of the EV industry.
Table 13.4 Different parameters of different types of EVs.
Table 13.5 Descriptive analysis of EVs (Audi).
Table 13.6 Descriptive analysis of EVs (BMW).
Table 13.7 Descriptive analysis of EVs (Kia).
Table 13.8 Descriptive analysis of EVs (Mercedes).
Table 13.9 Descriptive analysis of EVs (Nissan).
Table 13.10 Descriptive analysis of EVs (Porsche).
Table 13.11 Descriptive analysis of EVs (Renault).
Table 13.12 Descriptive analysis of EVs (Skoda).
Table 13.13 Descriptive analysis of EVs (Tesla).
Table 13.14 Descriptive analysis of EVs (Volkswagen).
Chapter 14
Table 14.1 Proposed energy framework (hybrid charging) compared to other UA...
List of Illustrations
Chapter 1
Figure 1.1 Different subsystems for the development of ITSs.
Figure 1.2 Main applications of ITSs.
Chapter 2
Figure 2.1 Development of the transportation system across time.
Figure 2.2 (a) Population increase in urban and rural areas and (b) the incr...
Figure 2.3 Average amount of time lost by people in some cities worldwide du...
Figure 2.4 In some cities around the world, traffic has risen as of 2020.
Figure 2.5 Different sectors in the United States that produce greenhouse ga...
Figure 2.6 Various impacts of the transportation system on society.
Figure 2.7 Several benefits of GT.
Figure 2.8 The goals of global agreements to protect the environment.
Figure 2.9 Profitable parts of the transport network.
Figure 2.10 GT’s challenges and barriers.
Figure 2.11 Examples of various types of vehicles and multi‐carrier energy n...
Figure 2.12 Approaches to overcoming the encountered barriers include avoid‐...
Figure 2.13 Some examples of fuels that can be used in green vehicles, inclu...
Figure 2.14 Examples of communication in GT.
Chapter 3
Figure 3.1 An overview of benefits offered by green transportation systems....
Figure 3.2 An overview of popular modes of green transportation systems.
Chapter 4
Figure 4.1 Significant aspects of sustainable transportation networks.
Figure 4.2 Schematic representing the social, environmental, and economic be...
Figure 4.3 Schematic of some of the key features connecting smart cities and...
Figure 4.4 Different infrastructure for the transition toward sustainable tr...
Figure 4.5 Difference between resilience and sustainability of the transport...
Chapter 5
Figure 5.1 Stages involved in integrated management system for green transpo...
Figure 5.2 Schematic diagram of PEM fuel cell vehicle system (a) and SOFC ve...
Figure 5.3 Schematics of PEMFC vehicle systems fueled with hydrogen (a), met...
Chapter 6
Figure 6.1 General energy structure of power‐to‐X facilities with different ...
Figure 6.2 Energy paradigm of P2H plants with the flexibility potential.
Figure 6.3 Energy paradigm of P2M facilities.
Figure 6.4 Integration of formic acid into the transportation sector, “FA st...
Figure 6.5 Integration of flexibility of buildings heating system to the P2H...
Figure 6.6 General flexibility potentials of the mobility sector.
Figure 6.7 General flexibility potentials of four sectors of electricity con...
Chapter 7
Figure 7.1 The typical configuration of SMES.
Figure 7.2 Configuration of EH with all‐available components.
Figure 7.3 Overall framework for EV charging and energy infrastructure.
Figure 7.4 Advantages and disadvantages of integrating EVs into the power gr...
Figure 7.5 Consequences of uncoordinated EV charging on grid.
Figure 7.6 Advanced smart charging mechanisms.
Figure 7.7 Diverse flexibility capabilities of EVs.
Figure 7.8 REVOLVE EV charging/discharging optimization model diagram.
Chapter 8
Figure 8.1 A brief summary of the developments of autonomous vehicles.
Figure 8.2 Representative sensor fusion diagram.
Figure 8.3 Lane tracking.
Figure 8.4 Traffic sign detection.
Figure 8.5 Vehicle/Pedestrian detection.
Figure 8.6 Schematic representation of SLAM.
Figure 8.7 An example of route planning.
Figure 8.8 AV framework diagram.
Chapter 9
Figure 9.1 Proton exchange membrane fuel cell (PEMFC).
Figure 9.2 Phosphoric acid fuel cell (PAFC).
Figure 9.3 Alkaline fuel cell (AFC).
Figure 9.4 Molten carbonate fuel cell (MCFC).
Figure 9.5 Solid‐oxide fuel cell (SOFC).
Figure 9.6 Direct methanol fuel cell (DMFC).
Figure 9.7 Block diagram of a PID controller (parallel form).
Figure 9.8 Block diagram of a PID controller (serial form).
Figure 9.9 Block diagram of a PID controller (ideal form).
Figure 9.10 Speed and current for the PI control: (a) speed and (b) current....
Figure 9.11 Speed and current for the PID control: (a) speed and (b) current...
Figure 9.12 Speed and current for the fuzzy logic: (a) speed and (b) current...
Chapter 10
Figure 10.1 Top country's battery EV market by volume till 2019.
Figure 10.2 Arrangement of different components of EV.
Figure 10.3 Series‐parallel integrated mechanism.
Figure 10.4 Design Parameters of EVs.
Figure 10.5 Types of battery cooling system.
Figure 10.6 Different Battery Parameters.
Figure 10.7 Control mechanism of the EV system.
Figure 10.8 Control variable for electric vehicle.
Chapter 11
Figure 11.1 Illustration of a simple charging station comprised of multiple ...
Figure 11.2
CV
α
vs.
α
. Results obtained for both the optimal (ILP)...
Figure 11.3 Total delay vs.
α
. Results obtained for both the optimal (I...
Figure 11.4
CV
α
vs.
α
. Results obtained for both the optimal (ILP)...
Figure 11.5
E
α
(
u
) vs.
α
. Results obtained for both the optimal (IL...
Chapter 12
Figure 12.1 Overview of IITS.
Figure 12.2 Components of IITS.
Figure 12.3 Major divisions of barriers related to IITS.
Figure 12.4 Spatial‐based multi‐energy management system.
Figure 12.5 Service‐based multi‐energy management system.
Figure 12.6 Fuel‐based multi‐energy management system.
Figure 12.7 Network‐based multi‐energy management system.
Chapter 13
Figure 13.1 List of countries with the highest share of plug‐in EVs in new p...
Figure 13.2 Forecasting of the price (euro) of the EVs.
Figure 13.3 Forecasting of the fast charge (kmh) of EVs.
Figure 13.4 Blockchain‐based EV transaction.
Figure 13.5 Framework of R3 corda‐based EV transaction.
Figure 13.6 Merkle tree of different financial parameters of EVs.
Chapter 14
Figure 14.1 System model: a network consisting of a UAV, user equipments (UE...
Figure 14.2 UAV's energy consumption as a function of (a) flying speed and (...
Figure 14.3 Optimal amount of energy to be procured or transferred at each t...
Figure 14.4 Optimal amount of energies to be procured or transferred to mini...
Chapter 15
Figure 15.1 Various aspects of autonomous vehicle systems in intelligent tra...
Figure 15.2 Reinforcement Learning mechanism.
Figure 15.3 Models exchanging workflow.
Figure 15.4 Day route.
Figure 15.5 Night route.
Figure 15.6 Day Task.
Figure 15.7 Night Task.
Figure 15.8 Day Task Mean and Std.
Figure 15.9 Night Task Mean and Std.
Figure 15.10 Combined Tasks Mean and Std.
Guide
Cover Page
Table of Contents
Series Page
Title Page
Copyright Page
List of Contributors
About the Editors
Preface
Begin Reading
Index
IEEE Press Series on Power and Energy Systems
WILEY END USER LICENSE AGREEMENT
Pages
ii
iii
iv
xv
xvi
xvii
xviii
xix
xx
xxi
xxiii
xxiv
xxv
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
437
IEEE Press445 Hoes LanePiscataway, NJ 08854
IEEE Press Editorial BoardSarah Spurgeon, Editor-in-Chief
Moeness AminJón Atli BenediktssonAdam DrobotJames Duncan
Ekram HossainBrian JohnsonHai LiJames LykeJoydeep Mitra
Desineni Subbaram NaiduTony Q. S. QuekBehzad RazaviThomas RobertazziDiomidis Spinellis
Interconnected Modern Multi‐Energy Networks and Intelligent Transportation Systems
Towards a Green Economy and Sustainable Development
Edited by
Mohammadreza Daneshvar
University of TabrizIran
Behnam Mohammadi-Ivatloo
LUT University, FinlandUniversity of Tabriz, Iran
Amjad Anvari-Moghaddam
Aalborg UniversityDenmark
Reza Razzaghi
Monash UniversityAustralia
Copyright © 2024 by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.
No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per‐copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750‐8400, fax (978) 750‐4470, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748‐6011, fax (201) 748‐6008, or online at http://www.wiley.com/go/permission.
Trademarks: Wiley and the Wiley logo are trademarks or registered trademarks of John Wiley & Sons, Inc. and/or its affiliates in the United States and other countries and may not be used without written permission. All other trademarks are the property of their respective owners. John Wiley & Sons, Inc. is not associated with any product or vendor mentioned in this book.
Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
For general information on our other products and services or for technical support, please contact our Customer Care Department within the United States at (800) 762‐2974, outside the United States at (317) 572‐3993 or fax (317) 572‐4002.
Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic formats. For more information about Wiley products, visit our web site at www.wiley.com.
Library of Congress Cataloging-in-Publication Data
Names: Daneshvar, Mohammadreza, editor. | Mohammadi-Ivatloo, Behnam, editor. | Anvari-Moghaddam, Amjad, editor. | Razzaghi, Reza, author.Title: Interconnected modern multi-energy networks and intelligent transportation systems : towards a green economy and sustainable development / Mohammadreza Daneshvar, Behnam Mohammadi‐Ivatloo, Amjad Anvari‐Moghaddam, Reza Razzaghi.Description: Hoboken, New Jersey : Wiley, [2024] | Includes index.Identifiers: LCCN 2023049029 (print) | LCCN 2023049030 (ebook) | ISBN 9781394188758 (hardback) | ISBN 9781394188765 (adobe pdf) | ISBN 9781394188772 (epub)Subjects: LCSH: Intelligent transportation systems. | Renewable energy sources. | Sustainable development.Classification: LCC TE228.3 .D346 2024 (print) | LCC TE228.3 (ebook) | DDC 625.7/94–dc23/eng/20240116LC record available at https://lccn.loc.gov/2023049029LC ebook record available at https://lccn.loc.gov/2023049030
Cover Design: WileyCover Image: © TK
List of Contributors
Saman AhmadiSchool of EngineeringSTEM College, RMIT UniversityMelbourne, Australia
Syed Muhammad Nawazish AliSchool of EngineeringSTEM College, RMIT UniversityMelbourne, Australia
Ali Moradi AmaniSchool of EngineeringSTEM College, RMIT UniversityMelbourne, Australia
Amjad Anvari‐MoghaddamDepartment of Energy (AAU Energy)Aalborg UniversityAalborg, Denmark
M. Imran AzimDepartment of Electrical andComputer Systems EngineeringMonash UniversityMelbourne, Victoria, Australia
Mariem Ahmed BabaEngineering for Smart and SustainableSystems Research CenterMohammadia School of EngineersMohammed V University in RabatRabat, Morocco
Miraj Ahmed BhuiyanFaculty Member School of EconomicsGuangdong University of Finance andEconomicsGuangzhou, China
Mohamed CherkaouiEngineering for Smart and SustainableSystems Research CenterMohammadia School of EngineersMohammed V University in RabatRabat, Morocco
Christos ChronisDepartment of Informatics andTelematics, HarokopioUniversity of AthensAthens, Greece
Mohammadreza DaneshvarDepartment of Electrical andComputer EngineeringUniversity of TabrizTabriz, Iran
Rahman DashtiClinical‐Laboratory Center of PowerSystem & ProtectionFaculty of Intelligent SystemsEngineering and Data SciencePersian Gulf UniversityBushehr, Iran
M. EdwinDepartment of MechanicalEngineering, University College ofEngineering, NagercoilAnna University Constituent CollegeNagercoil, Tamilnadu, India
Georgios EllinasKIOS Research and InnovationCenter of ExcellenceDepartment of Electrical andComputer EngineeringUniversity of CyprusNicosia, Cyprus
M. C. EniyanDepartment of MechanicalEngineering, University Collegeof EngineeringNagercoilAnna University Constituent CollegeNagercoil, Tamilnadu, India
Reza GharibiClinical‐Laboratory Center ofPower System & ProtectionFaculty of Intelligent SystemsEngineering and Data SciencePersian Gulf UniversityBushehr, Iran
Hessam GolmohamadiDepartment of Computer ScienceAalborg UniversityAalborg, Denmark
Ankita JainPrestige Institute of GlobalManagementIndore, Madhya PradeshIndia
Mahdi JaliliSchool of EngineeringSTEM College, RMIT UniversityMelbourne, Australia
Vikas KhareSchool of Technology Managementand Engineering, NMIMSIndore, Madhya Pradesh, India
Mohsen KhorasanyDepartment of Electrical andComputer Systems EngineeringMonash UniversityMelbourne, VictoriaAustralia
Yigit Cagatay KuyuR&D department, Karsan OtomotivSanayi ve Tic., Bursa, Turkey
Michalis MavrovouniotisKIOS Research and InnovationCenter of ExcellenceDepartment of Electrical andComputer EngineeringUniversity of CyprusNicosia, Cyprus
G. Antony MiraculasDepartment of MechanicalEngineering, St. Xavier's CatholicCollege of EngineeringChunkankadaiNagercoil, Tamilnadu, India
Behnam Mohammadi‐IvatlooLUT University, FinlandUniversity of Tabriz, Iran
M. Saranya NairSchool of Electronics Engineering,Vellore Institute of TechnologyChennai, Tamilnadu, India
Mohamed NaouiResearch Unit of Energy ProcessesEnvironment and Electrical SystemsNational Engineering School of GabesUniversity of GabésGabés, Tunisia
Farzad H. PanahiDepartment of Electronics andCommunication EngineeringUniversity of KurdistanSanandaj, Iran
Fereidoun H. PanahiDepartment of Electronics andCommunication EngineeringUniversity of KurdistanSanandaj, Iran
Tania PanayiotouKIOS Research and InnovationCenter of ExcellenceDepartment of Electrical andComputer EngineeringUniversity of CyprusNicosia, Cyprus
Reza RazzaghiDepartment of Electrical andComputer Systems EngineeringMonash UniversityMelbourne, VictoriaAustralia
Samaneh Sadat SajjadiSchool of EngineeringSTEM College, RMIT UniversityMelbourne, Australia
S. Joseph SekharDepartment of EngineeringUniversity of Technology andApplied Sciences‐ShinasAl‐Aqar, Oman
Konstantinos TserpesDepartment of Informaticsand TelematicsHarokopio University of AthensAthens, Greece
Behrooz VahidiDepartment of Electrical EngineeringAmirkabir University of Technology(Tehran Polytechnic)Tehran, Iran
Iraklis VarlamisDepartment of Informatics andTelematicsHarokopio University of AthensAthens, Greece
About the Editors
Mohammadreza Daneshvar, PhD, is an Assistant Professor at the Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran. Prior to that he was a postdoctoral research fellow in the field of modern multi‐energy networks at the Smart Energy Systems Lab of the University of Tabriz. He obtained his MSc and PhD in Electrical Power Engineering from the University of Tabriz, Tabriz, Iran, all with honors. He has (co)authored more than 50 technical journal and conference articles, 6 books, and 26 book chapters in the field. Dr. Daneshvar is a member of the Early Career Editorial Board of the Sustainable Cities and Society Journal and also serves as a guest editor for the Sustainable Cities and Society, and Sustainable Energy Technologies and Assessments journals. Moreover, he serves as an active reviewer with more than 45 top journals of the IEEE, Elsevier, Springer, Wiley, Taylor & Francis, and IOS Press, and was ranked among the top 1% of reviewers in Engineering and Cross‐Field based on Publons global reviewer database. His research interests include Smart Grids, Transactive Energy, Energy Management, Renewable Energy Sources, Integrated Energy Systems, Grid Modernization, Electrical Energy Storage Systems, Microgrids, Energy Hubs, Machine Learning and Deep Learning, and Optimization Techniques.
Dr. Behnam Mohammadi‐Ivatloo, currently holds the position of Professor specializing in sector coupling within power systems at LUT University in Finland. He began his academic journey at the University of Tabriz in 2012 as an Assistant Professor and was later elevated to the rank of Professor in 2019. He also has research experience at Aalborg University, Aalborg, Denmark, and the Institute for Sustainable Energy, Environment and Economy, University of Calgary, Canada. He obtained his MSc and PhD in electrical engineering from the Sharif University of Technology, Tehran, Iran. He has a mix of high‐level experience in research, teaching, administration, and voluntary jobs at the national and international levels. He was PI or CO‐PI in 20 externally funded research projects. He has been a Senior Member of IEEE since 2017 and a Member of the Governing Board of Iran Energy Association since 2013, where he was elected as President in 2019. His main areas of interest are integrated energy systems, renewable energies, energy storage systems, microgrid systems, and smart grids.
Amjad Anvari‐Moghaddam (S'10 ‐M'14 ‐SM'17) received his PhD (Hons.) in Power Systems Engineering in 2015 from the University of Tehran, Tehran, Iran. Currently, he is an Associate Professor and Leader of the Intelligent Energy Systems and Flexible Markets (iGRIDS) Research Group at the Department of Energy (AAU Energy), Aalborg University where he is also acting as the Vice‐Leader of Power Electronic Control, Reliability and System Optimization (PESYS) and the coordinator of Integrated Energy Systems Laboratory (IES‐Lab). His research interests include planning, control, and operation management of microgrids, renewable/hybrid power systems, and integrated energy systems with appropriate market mechanisms. He has (co)authored more than 300 technical articles, 7 books, and 17 book chapters in the field. Dr. Anvari‐Moghaddam is the Editor‐in‐Chief of Academia Green Energy journal and serves as an Associate Editor of several leading journals such as the IEEE Transactions on Power Systems, IEEE Systems Journal, IEEE Open Access Journal of Power and Energy, and IEEE Power Engineering Letters. He is the Chair of IEEE Denmark, a Member of IEC SC/8B‐ Working Group (WG3 & WG6) as well as Technical Committee Member of several IEEE PES/IES/PELS and CIGRE WGs. He was the recipient of 2020 and 2023 DUO–India and SPARC Fellowship Awards, DANIDA Research Fellowship grant from the Ministry of Foreign Affairs of Denmark in 2018 and 2021, IEEE‐CS Outstanding Leadership Award 2018 (Halifax, Nova Scotia, Canada), and the 2017 IEEE‐CS Outstanding Service Award (Exeter‐UK).
Reza Razzaghi (Senior Member, IEEE) received his PhD in electrical engineering from the Swiss Federal Institute of Technology of Lausanne (EPFL), Lausanne, Switzerland in 2016. In 2017, he joined Monash University, Melbourne, Australia, where he is currently a Senior Lecturer with the Department of Electrical and Computer Systems Engineering and an Australian Research Council DECRA fellow. His research interests include distributed energy resources, power system protection, dynamics, and transients. He has been the recipient of the 2019 Best Paper Award from the IEEE Transactions on EMC and the 2013 Basil Papadias Best Paper Award from the IEEE PowerTech Conference.
Preface
Modern grids aim at enabling modern functionalities (e.g., self‐healing systems, smart transportation systems, sustainable energy networks, and multi‐dimensional community of intelligence agents) and integrating smart technologies in the body of multi‐energy networks (MENs) aiming to supply more reliable and efficient energy. In this context, transportation networks have recently experienced significant growth in terms of vehicle systems, physical infrastructures, public transit system management, autonomous vehicles, traveler information systems, and traffic management, to name a few. In this area, emerging new intelligent and hybrid energy systems, along with the substantial development in energy conversion technologies, as well as increasing demand for secure, comfortable, and reliable vehicle systems declare the fact that modern grids need to include intelligent interconnected transportation systems. Herein, diverse and intelligent transportation devices play a pivotal role in meeting the growing demand for vehicle systems that can be operated in a collaborative manner to make the modern structure of the energy network more efficient, reliable, resilient, and stable. However, how intelligent transportation systems (ITSs) can be interconnectedly operated for maintaining the sustainability of cleaner modern MENs is a key question that needs to be addressed in deep detail. As reliable transportation services are critical for future modern energy grids, a great need is felt for sustainable intelligent interconnected transportation systems to support the system in realizing modern energy services goals under the cleaner and modern structure of energy networks. As a pioneering book that presents the fundamental technologies and solutions for real‐world problems in the context of intelligent interconnected transportation systems, it covers a conceptual introduction to modern transportation systems, highlights potential technologies and vehicle systems in this area, and discusses requirements for coordinated exploitation of modern transportation systems. Moreover, the current book presents innovative ways for interconnecting ITSs to ensure the sustainability of modern MENs with a high/full share of renewable energy sources.
The current book consists of 15 chapters. Chapter 1 aims to inspect the necessity for modernizing the coupled structure of ITSs and MENs. Moreover, it clarifies the different applications of ITSs as well as the coupled structure of ITSs and MENs. Chapter 2 provides a review of the development of green transportation (GT). It also states the concept of GT, current transportation issues such as traffic congestion and greenhouse gas emissions, and the relationship between various GT components. Chapter 3 presents an overview of techno‐economic‐environmental approaches and the benefits of GT systems to emphasize their applicability in today's world. Further, green transports are assessed from both economic and environmental points of view in this chapter. Chapter 4 emphasizes on the necessity of sustainable transportation by highlighting the catastrophic effects of greenhouse gas emissions from conventional transportation on climate change and public health while discussing some potential approaches for mitigating these emissions. It also presents some key modes of sustainable transportation along with their benefits and existing cases around the globe as well as elaborates the sustainable transportation in modern urban advancement. Chapter 5 examines various aspects of multi‐energy technologies in developing GT for global sustainability. It also investigates novel technologies to promote GT systems as well as describes limitations and challenges related to present travel needs that are impeding GT adoption. Chapter 6 surveys the flexibility potentials of power‐To‐X (P2X) plants including the power‐to‐hydrogen, ‐methane, ‐heat, ‐mobility, and ‐chemical systems. It also investigates the flexibility opportunities of electric vehicles and hydrogen fuel cell fleets along with the flexibility opportunities of electricity demands in residential, industrial, agricultural, and commercial sectors. Chapter 7 aims to review original research works about modeling, management, and intelligent controls of the multi‐energy system (MES) integrating EV routing and charging. It also clarifies unavoidable interdependences between the energy and transport infrastructure in the MES. Chapter 8 provides a systematic review to cover key fundamentals that make vehicles autonomous and their applications in intelligent transportation networks. Chapter 9 focuses on the brushless motor's storage technologies and control systems in an electric vehicle. It also discusses the different types of batteries used in electric vehicles, generally made from lead acid, nickel, lithium metal, silver, and sodium‐sulfur. Chapter 10 presents a review of the different aspects of EVs, including the design and control features of EVs, in a comprehensive way. It also shows the need for several technological developments to grow the EV market and create a pollution‐free environment. Chapter 11 investigates the interconnection between energy networks and ITSs by presenting the management of electric vehicle charging in parking structures. It also discusses the main related challenges along with various optimization targets and technologies. Chapter 12 highlights the role of multi‐energy management schemes in the sustainable development of interconnected ITS. It also examines the sustainability of interconnected ITS in the view of energy management and describes the challenges in its implementation. Chapter 13 presents a blockchain‐based financial and economic analysis of green vehicles as a path toward the ITS. It also provides financial and economic analysis as well as an analysis of the speed and range of EVs by using statistical software. Chapter 14 proposes a consistent and cost‐aware energy procurement framework for an unmanned aerial vehicle powered concurrently by laser beams emitted by locally deployed laser beam directors and local renewable energy sources. Finally, Chapter 15 explores the problem of the personalization of the autonomous driving experience, leveraging the existing advanced driving assistance systems through a combination of reinforcement learning algorithms and federated learning techniques.
As any research achievement may not be free of gaps, the Editors kindly welcome any suggestions and comments from the respectful readers for improving the quality of this work. The interested readers can share their valuable comments with the Editors via [email protected].
1The Necessity for Modernizing the Coupled Structure of Intelligent Transportation Systems and Multi‐Energy Networks
Mohammadreza Daneshvar1, Amjad Anvari‐Moghaddam2, and Reza Razzaghi3
1 Department of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran
2 Department of Energy (AAU Energy), Aalborg University, Aalborg, Denmark
3 Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, Victoria, Australia
1.1 Introduction
In recent years, the growing need for all carriers of energy has driven energy networks to be reconstructed in a way to effectively match energy supply and demand [1]. In this transformation, grid modernization is introduced to pave the realization of required changes that make the energy structure cleaner, more efficient, affordable, sustainable, flexible, stable, and secure than the previous paradigm [2]. One of the prominent features of modernized energy networks is the adoption of renewable energy sources (RESs) in energy generation premises [3]. This evolution is intended to facilitate the decarbonization plans for an energy transition toward a carbon‐free and green energy structure. However, such a development was not only accompanied by economic and environmental benefits, but also critical challenges have emerged, especially concerning uncertain outputs of RESs [4]. Multi‐energy systems along with other energy storage, management, and energy trading technologies are proposed to address such challenges in the modern energy grid [5]. However, effectively responding to such concerns requires more than just using the mentioned solutions. Indeed, dynamic energy balancing is more difficult from the network viewpoint when it is equipped with 100% RESs given the stochastic nature of energy production. In such a circumstance, interconnecting different sectors of energy grids can make an appropriate multi‐energy coupling that supports the whole structure of the system in continuous energy serving. One of these important sectors is transportation. The transportation network encompasses different parts such as power lines, air routes, railways, and road networks that possess diverse energy‐consumed systems like electric vehicles (EVs), buses, boats, etc. [6]. By including various energy‐dependent devices, the transportation network plays a vital role in energy interactions across the grid. As future energy networks are planned to be eco‐friendly infrastructure with fully clean energy production [7], the transportation sector is also not exempt from this green economy movement. Hence, exploiting carbon‐free energy systems is necessary for realizing a green transportation network. In this regard, recent advances in the technology of multi‐carrier energy devices offer great opportunities for generating, storing, and converting different carriers of energy to each other [8]. Therefore, the operation of coupled intelligent transportation networks and multi‐carrier energy units can procure appropriate conditions for implementing net‐zero emission plans and realizing a green transportation network. This issue highlights the necessity for developing the application of multi‐energy systems to their usage in the transportation network. This chapter aims to further clarify various dimensions of this necessity.
1.2 Applications of Intelligent Transportation Systems
Recent years have witnessed a considerable rise in energy demand along with the rapid development in the technologies of smart devices for smart grids. The deployment of intelligent systems is not only limited to the residential sector, but also the transportation premise has benefited in controlling a variety of energy interactions. Such evolutions have driven the system to face huge volumes of data generated by smart devices across the grid. This data is taken into account as valuable information for the decision‐making process of the transportation network. How the mentioned information needs to be used for managing various processes as well as completing different duties is the main reason for creating transportation management systems (TMSs). The TMS is from the area of transportation that sets up for improving flexibility, load optimization, and effective route planning [9]. The utilization of machine learning (ML) techniques along with artificial intelligence (AI) has made TMSs more intelligent, enabling them to achieve accurate performance. The emergence of intelligent devices in recent decades has resulted in the development of diverse information systems for planning, mapping, routing, and logistics. The exploitation of such systems has significantly increased the capabilities of data processing leading to the appearance of intelligent transportation systems (ITSs) [10]. Indeed, ITS is a system with the ability to take appropriate decisions for different states of the transportation network using the data from vehicles with smart devices. The received data from the sensors and intelligent devices are monitored by ITSs to extract useful information that can be effectively used by businesses and governments for taking purposeful decisions. The used feedback mechanism enables ITSs to continuously improve the performance of different systems across the transportation network. ITSs consist of a set of subsystems to achieve such improvements that are indicated in Figure 1.1[11].
As one of the ITSs’ subsystems, intelligent public transportation systems are for controlling the public transportation network, maintaining the performance of the transportation structure, and providing up‐to‐date information regarding the network operation and trips for the decision‐makers and passengers [12]. As a context‐aware solution to effectively control and manage the traffic challenges of the transportation network, the intelligent traffic control and management system has been developed that uses real‐time data coming from predictive analytics as well as connected road infrastructure [13]. The intelligent parking management system relies on satisfying the requirements of the Internet of things (IoT) device management, vehicle management, and user information management for managing vehicle parking [14]. The intelligent traffic information system is responsible for effectively monitoring traffic by using IoT to create interoperability among heterogeneous interconnected devices to avoid vehicle traffic congestion [15]. The application of IoT is not just limited to the mentioned ITSs’ subsystems, but its integration with AI also procures appropriate platforms for safety management and emergency conditions. Given the significant role of pavement maintenance in megacities, the intelligent pavement management system pursues the key goal of scheduling road reviews as well as managing complaints [16]. Indeed, such systems can be most efficient in improving management capability, driving economic growth, and supporting the sustainability of the transportation network when accurate data is available from sensors. In this regard, different applications of ITSs can be classified into four main classes that are illustrated in Figure 1.2[17].
Figure 1.1 Different subsystems for the development of ITSs.
Source: Adapted from [11].
All presented applications for ITSs in Figure 1.2 are based on using the collected data from vehicles aiming to improve the transportation process, facilitate public transportation services, and increase driver safety. Thus, ITSs not only ease the decision‐making process for government authorities, but they can also manage and control planning for the transportation network in an appropriate manner, resulting in efficient road management, better driver experience, and a proper degree of passenger comfort [9].
Figure 1.2 Main applications of ITSs.
Source: Adapted from [17].
1.3 Coupled Structure of ITSs and Multi‐Energy Networks
The described applications of ITSs highlight their undeniable place in the future energy network infrastructure. The rise in transport demand has substantially increased for different types of transportation services in recent years. In this respect, vehicles with traditional fossil fuels were mainly responsible for satisfying the transport demand in the transportation network. However, considerable advancements in the technology of clean energy systems have changed the mentioned trend in the usage of fossil fuel‐based devices in the transportation sector. The environmental problems caused by traditional systems have driven the transportation sector to operate carbon‐free devices in both personal vehicles and public transport services. Moreover, recent endeavors have been focused on significantly declining the carbon emissions in the transportation premise and actualizing green transportation more than ever before. However, rapid developments in energy technologies do not accept such a reduction degree and define ambitious goals in constructing zero‐emission transportation networks. Therefore, the modernization of the transportation network is accompanied by realizing 100% RES goals in the grid modernization process. However, uncertainties in clean energy production by RESs have procured difficult conditions for making such decarbonization plans reliably implementable in the practice. Indeed, most clean energy production systems rely on climate‐dependent systems whose outputs vary simultaneously with climate changes. Hence, incorporating RESs in the transportation sector donates the challenge of their uncontrollable energy generation, which is already a great concern for energy networks. In this circumstance, although ITSs can pave the successful adoption of diverse technologies for providing an acceptable degree of safety and services in the transportation network, reliable exploitation of the transportation sector still remains a considerable challenge when planning to realize zero‐emission goals through full usage of RESs. Herein, given the great achievements of deploying multi‐energy systems in boosting the ability of energy grids in coping with the intermittences of RESs, their utilization in the transportation network can open new doors for this sector to act most flexibly in making green transportation. Indeed, multi‐energy networks offer a set of multi‐energy interactions using different technologies such as power‐to‐X to enable renewable‐dominant structures for supplying energy. The aforementioned benefits are a key portion of opportunities that the transportation grid with RESs requires to keep its sustainability in the green economy. Therefore, the considerable advantages of multi‐energy systems in easing the adoption of a high level of RESs highlight the necessity of interconnected exploitation of the transportation network with multi‐energy grids. Indeed, coupling them is an essential step for facilitating the implementation of decarbonization plans as well as realizing green transportation infrastructure.
1.4 Summary
Recent evolutions in technology development along with the rapid growth in multi‐energy demand have affected different sectors across the globe. The transportation network has also not been spared from these transformations and has witnessed widespread changes in different layers of transportation management. One of the affected parts is ITSs which are developed in a way to improve synergies while promoting interoperability between various participants of the transportation network. In this respect, ITSs cannot satisfy the modernization expectations of transportation alone. On the other hand, multi‐energy systems render attractive privileges for utilizing RESs and efficiently constructing green transportation. Thus, there is a great necessity for coupling ITSs and multi‐energy networks to easily reach the grid modernization goals. This chapter highlights this necessity by mostly focusing on the grid modernization viewpoint. Moreover, it also clarified the different applications of ITSs in the transportation network.
References
1
Daneshvar, M., Mohammadi‐Ivatloo, B., and Zare, K. (2023). An innovative transactive energy architecture for community microgrids in modern multi‐carrier energy networks: a Chicago case study.
Scientific Reports
13 (1): 1529.
2
Daneshvar, M., Mohammadi‐Ivatloo, B., and Zare, K. (2022). A novel transactive energy trading model for modernizing energy hubs in the coupled heat and electricity network.
Journal of Cleaner Production
344: 131024.
3
Daneshvar, M., Mohammadi‐Ivatloo, B., and Zare, K. (2022). A fair risk‐averse stochastic transactive energy model for 100% renewable multi‐microgrids in the modern power and gas incorporated network.
IEEE Transactions on Smart Grid
14: 1933–1945.
4
Daneshvar, M., Mohammadi‐ivatloo, B., Asadi, S., and Galvani, S. (2020). Short term optimal hydro‐thermal scheduling of the transmission system equipped with pumped storage in the competitive environment.
Majlesi Journal of Electrical Engineering
14 (1): 77–84.
5
Huang, W., Zhang, X., Li, K. et al. (2021). Resilience oriented planning of urban multi‐energy systems with generalized energy storage sources.
IEEE Transactions on Power Systems
37 (4): 2906–2918.
6
Shao, C., Li, K., Qian, T. et al. (2022). Generalized user equilibrium for coordination of coupled power‐transportation network.
IEEE Transactions on Smart Grid
14: 2140–2151.
7
Daneshvar, M., Mohammadi‐Ivatloo, B., Zare, K., and Anvari‐Moghaddam, A. (2022). Transactive energy strategy for energy trading of proactive distribution company with renewable systems: a robust/stochastic hybrid technique.
e‐Prime Advances in Electrical Engineering, Electronics and Energy
2: 100028.
8
Kazemi, B., Kavousi‐Fard, A., Dabbaghjamanesh, M., and Karimi, M. (2022). IoT‐enabled operation of multi energy hubs considering electric vehicles and demand response.
IEEE Transactions on Intelligent Transportation Systems
24: 2668–2676.
9
Iyer, L.S. (2021). AI enabled applications towards intelligent transportation.
Transportation Engineering
5: 100083.
10
Zapata Cortes, J.A., Arango Serna, M.D., and Andres Gomez, R. (2013). Information systems applied to transport improvement.
Dyna
80 (180): 77–86.
11
Agarwal, P.K., Gurjar, J., Agarwal, A.K., and Birla, R. (2015). Application of artificial intelligence for development of intelligent transport system in smart cities.
Journal of Traffic and Transportation Engineering
1 (1): 20–30.
12
Elkosantini, S. and Darmoul, S. (2013). Intelligent public transportation systems: A review of architectures and enabling technologies.
2013 International Conference on Advanced Logistics and Transport
, Sousse, Tunisia, 233–238. IEEE.
13
(March 31, 2023). Intelligent traffic management systems: a lowdown of software & hardware components.
https://intellias.com/intelligent‐traffic‐management/
(accessed 31 March 2023).
14
Lyu, L. and Fan, N. (2022). Research and design of intelligent parking management system based on UML technology.
2022 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS)
, Dalian, China, 919–922. IEEE.
15
Al‐Sakran, H.O. (2015). Intelligent traffic information system based on integration of Internet of Things and Agent technology.
International Journal of Advanced Computer Science and Applications (IJACSA)
6 (2): 37–43.
16
Moradi, M. and Assaf, G.J. (2023). Designing and building an intelligent pavement management system for urban road networks.
Sustainability
15 (2): 1157.
17
Ben Hamida, E., Noura, H., and Znaidi, W. (2015). Security of cooperative intelligent transport systems: Standards, threats analysis and cryptographic countermeasures.
Electronics
4 (3): 380–423.
2Green Transportation Systems
Reza Gharibi1, Behrooz Vahidi2, and Rahman Dashti1
1 Clinical‐Laboratory Center of Power System & Protection, Faculty of Intelligent Systems Engineering and Data Science, Persian Gulf University, Bushehr, Iran
2 Department of Electrical Engineering, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
2.1 Introduction
2.1.1 Motivation and Problem Description
The most significant issue facing contemporary society is population growth. The demand to consume various resources grows even more as the population grows. For stability and forward movement, the world has to guarantee dependable and stable access to its basic requirements. At first glance, food, energy, and water are the three basic needs that are thought to be necessary for a society. The environment must be destroyed in order to fulfill these systemic needs.
The society and organizations that make policies give these three demands a lot of consideration. One of society's fundamental needs is social welfare, although it receives less attention. One of the main pillars of social welfare is transportation. Unreasonable population expansion, inadequate planning for the construction of roads, and an unchecked increase in the number of automobiles have all caused issues for human society [1].
The development of technology opened up a new area for the planning and redesign of conventional systems [2]. Redesign and special look at the changes in traditional systems to save energy consumption were applied and implemented in large networks such as electricity. In the power system, the coordination between different energy carriers led to significant economic benefits [3]. The transportation system made a move toward redesign to enhance its conditions as one of the most significant energy consumers and generators of greenhouse gases. Along with energy and greenhouse gas emissions issues, the traditional transportation system struggles with car congestion due to its inadequate infrastructure. Green transportation (GT) was proposed as a solution to these issues and as the cornerstone of the new transportation system, notwithstanding these issues and the fundamental requirement to rethink the traditional transportation system [4]. The following objectives and problems have been addressed in this chapter, which is centered on the GT system:
Discussing the development and expansion of the transportation system.
Population growth and the issues it brings are studied statistically.
Vehicle traffic as a consequence of the community's growing population and people's time wastage.
Pollution of the environment and greenhouse gas emissions from the transportation system.
Effects and advantages of GT versus traditional transportation systems.
Issues that prevent the growth of GT.
Effect of new technologies on GT's acceleration.
Intelligent transportation systems and methods for connection between various components.
2.1.2 Literature Review
One of the biggest problems brought on by the use of traditional transport systems is global warming. Without changing the current system's structure, every attempt to reduce transportation density will have a negative impact on both the general satisfaction of society and the transportation industry [5]. In Ref. [6], it is investigated how increasing the usage of fossil fuels puts both the global environment and global society at irreversible harm. It is recommended that the global economy shift toward carbon reduction so that the rise in global temperature does not exceed 2°. There are serious challenges in reducing carbon with the goal of lowering temperatures. The use of renewable energy sources is one of these difficulties. In order to overcome these obstacles, there must be broad international cooperation. As a result, the United Nations member states decided to work together in this direction [7].
The Green Climate Fund was formed in 2010 to help finance this objective. The big businesses then started to reduce their carbon emissions. Businesses are encouraged to invest in this area, and transportation companies strive to act in a less carbon‐intensive manner, thanks to the assistance of the international community and the adoption of legislation [8]. The ultimate purpose of the transportation system is to make it easier for people to go about their normal, everyday lives without wasting time. Another major objective of better transportation is to move commodities more efficiently while having less of a negative impact on the environment [9]. In light of these circumstances, the world community has set sustainability in transportation as a goal. This means finding ways to meet societal requirements while also protecting the environment and future generations' access to resources [10]. Several governments have modified their policies to solve this problem and are working to achieve sustainable transportation [11]. Despite government attempts to promote sustainable transportation, the use of conventional and fossil fuels and the resulting greenhouse gas emissions have created an unstable environment [12]. One of the key causes of declining societal health and environmental destruction is the emission of greenhouse gases [13]. The use of clean fuels and the electrification of cars rather than the use of fossil fuels in the transportation sector can work to address these concerns and problems [14, 15]. The use of sustainable transport was recognized, and suggestions were made specifically for public transportation [16]. There are still some unknowns despite all the recommendations and alternative solutions to the transportation issues. Researchers recognized the urgent need to develop a GT system after assessing the severity of the system's issues. A system of GT is one in which all modes of transportation cause the least amount of damage to the environment and to people's health [4]. These concepts and topics are also covered in this chapter:
Investigated the development of transportation from the invention of the wheel to modern green and smart transportation.
Problems brought on by population growth, such as the escalation of traffic and the contamination of the environment.
Agreements and treaties established in relation to reducing greenhouse gas emissions.
Challenges that need to be overcome to implement GT.
Technology advancements that are practical as well as new are speeding up the development of greener transportation.
2.1.3 Chapter Organization
The remainder of this chapter first reviews and presents the history of the transportation system from the age of the invention of the wheel to the present, and then lists the issues and difficulties that the current transportation faces as a result of population increase. After reviewing the international accords that have been put forth to address the issues of GT and global warming, the GT system is described and its difficulties are looked at. Multiple energy networks and GT's effects are investigated. The methods for implementing GT are offered after the definition of the GT system. The newest technology utilized by the GT system is discussed and presented at the end.
2.2 History of Transportation
Studying the history and current state of transportation systems is crucial for researching and evaluating various vehicle types. The welfare of society is considerably increased by transportation systems. The movement of people and products both vertically and horizontally may be referred to as transportation. When it comes to vertical transportation, equipment is utilized for lifting tasks like removing objects from atop structures, metal from mines, and other things. The Shadow apparatus, which was used in Mesopotamia to lift water, is one of the historical examples of a vertical transportation system [17–20].
The invention of the first wheel in 3500 BC can be regarded as the start of horizontal transportation [21]. Around 2000 BC, small chariots developed in Syria or northern Mesopotamia and were the first horizontal wheeled means of transportation, which swiftly swept throughout the Middle East [22]. Although it was primarily utilized for military purposes, this kind of chariot was also used for travel and hunting. Around 1550 BC, chariot use spread throughout Greece as a result of trade and migration. Chariot use led to the development of roadways, which were primarily tied to the building of bridges across rivers and streams [22]. Horses were utilized to pull chariots throughout this time period, and they were regarded as the most crucial component of the transportation system [3].
Up until the year 1400 AD, when Europeans invented the horse‐drawn wagon, chariots were still in use [23]. James Watt's invention of the steam engine in 1769 sparked a massive revolution in both industry and daily life [24]. Boats and steamships were among the first modes of transportation to make significant strides using Watt steam engines in 1783 [25]. Locomotives were the first land vehicles to benefit from steam engines. The locomotive was unveiled in 1801, and its “Salamanca” commercial counterpart was conceived and constructed in 1812 [25]. A more advanced version of this locomotive with eight wagons was shown two years later. Thirty tons of coal could be moved by this locomotive at a speed of 4 miles per hour [25]. The first air transport method was the hot air balloon, which was invented and developed in 1783 [26].
The invention of the bicycle in the 1790s marked the beginning of the personal vehicle age [25]. In 1886, the first motorized vehicle was created, and people started using them [27]. A century or so later, in 1980, a more advanced model of the automobile without a driver was invented [28]. Parallel to this progress, motorized airplanes first flew in 1903; electric subways began operating in 1890; cruise ships appeared in 2002; and lastly, from 2010 onward, electric automobiles have significantly increased horizontal transportation and impacted people's lives [29]. Figure 2.1 depicts the development and growth of transportation based on the history as described.
Figure 2.1 Development of the transportation system across time.
2.3 Transportation Expansion Issues
There are several issues with the traditional transportation system. These issues are caused by an increase in the number of vehicles, a lack of infrastructure, and facilities within the system, as well as factors relating to the local environment and society. The spread of urbanization and the rise in population are just two problems that have a negative impact on the traditional transportation system. The transportation system has also imposed problems on the environment, such as the rise in traffic and the release of greenhouse gases. Below, these concerns and issues are discussed in more detail.
