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Optimization-Based Energy Management for Multi-energy Maritime Grids 2021 ed. [Mīkstie vāki]

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  • Formāts: Paperback / softback, 201 pages, height x width: 235x155 mm, weight: 454 g, 138 Illustrations, color; 7 Illustrations, black and white; XVIII, 201 p. 145 illus., 138 illus. in color., 1 Paperback / softback
  • Sērija : Springer Series on Naval Architecture, Marine Engineering, Shipbuilding and Shipping 11
  • Izdošanas datums: 22-Apr-2021
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9813367369
  • ISBN-13: 9789813367364
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Optimization-Based Energy Management for Multi-energy Maritime Grids 2021 ed.Palielināt
  • Formāts: Paperback / softback, 201 pages, height x width: 235x155 mm, weight: 454 g, 138 Illustrations, color; 7 Illustrations, black and white; XVIII, 201 p. 145 illus., 138 illus. in color., 1 Paperback / softback
  • Sērija : Springer Series on Naval Architecture, Marine Engineering, Shipbuilding and Shipping 11
  • Izdošanas datums: 22-Apr-2021
  • Izdevniecība: Springer Verlag, Singapore
  • ISBN-10: 9813367369
  • ISBN-13: 9789813367364
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9789813367364.html

This open access book discusses the energy management for the multi-energy maritime grid, which is the local energy network installed in harbors, ports, ships, ferries, or vessels. The grid consists of generation, storage, and critical loads. It operates either in grid-connected or in islanding modes, under the constraints of both power system and transportation system. With full electrification, the future maritime grids, such as all-electric ships and seaport microgrids, will become “maritime multi-energy system” with the involvement of multiple energy, i.e., electrical power, fossil fuel, and heating/cooling power. With various practical cases, this book provides a cross-disciplinary view of the green and sustainable shipping via the energy management of maritime grids. In this book, the concepts and definitions of the multi-energy maritime grids are given after a comprehensive literature survey, and then the global and regional energy efficiency policies for the maritime transportation are illustrated. After that, it presents energy management methods under different scenarios for all-electric ships and electrified ports. At last, the future research roadmap are overviewed. The book is intended for graduate students, researchers, and professionals who are interested in the energy management of maritime transportation.

1 Introduction to the Multi-energy Maritime Grids 1(30)
1.1 Background and Motivation
1(6)
1.1.1 Economy Growth and the Demand for Maritime Transport
1(1)
1.1.2 Ship Supply Capacity and Market Structure
2(1)
1.1.3 Shipping Services and Ports
3(2)
1.1.4 The Path to the Green Shipping
5(2)
1.2 Promising Technologies
7(14)
1.2.1 Overview
7(1)
1.2.2 Selected Technical Designs for Energy Efficiency Improvement
8(7)
1.2.3 Selected Alternative Fuels or Energy Sources
15(6)
1.3 Next-Generation Maritime Grids
21(4)
1.3.1 Shipboard Microgrid
22(1)
1.3.2 Seaport Microgrid
23(1)
1.3.3 Coordination Between Shipboard and Seaport Microgrids
24(1)
1.4 Summary
25(1)
References
26(5)
2 Basics for Optimization Problem 31(16)
2.1 Overview of Optimization Problems
31(3)
2.1.1 General Forms
31(2)
2.1.2 Classifications of Optimization Problems
33(1)
2.2 Optimization Problems with Uncertainties
34(5)
2.2.1 Stochastic Optimization
35(1)
2.2.2 Robust Optimization
36(1)
2.2.3 Interval Optimization
37(2)
2.3 Convex Optimization
39(2)
2.3.1 Semi-definite Programming
39(1)
2.3.2 Second-Order Cone Programming
39(2)
2.4 Optimization Frameworks
41(2)
2.4.1 Two-Stage Optimization
41(1)
2.4.2 Bi-level Optimization
42(1)
2.5 Summary
43(1)
References
44(3)
3 Mathematical Formulation of Management Targets 47(30)
3.1 Overview of the Management Tasks
47(1)
3.2 Navigation Tasks
47(8)
3.2.1 Typical Cases
47(5)
3.2.2 Mathematical Model
52(3)
3.3 Energy Consumption
55(6)
3.3.1 Diesel Engines/Generators
55(2)
3.3.2 Fuel Cell
57(1)
3.3.3 Energy Storage
58(1)
3.3.4 Renewable Energy Generation
59(2)
3.3.5 Main Grid
61(1)
3.4 Gas Emission
61(5)
3.4.1 Gas Emission from Ships
61(3)
3.4.2 Gas Emission from Ports
64(2)
3.5 Reliability Under Multiple Failures
66(3)
3.5.1 Multiple Failures in Ships
66(1)
3.5.2 Multiple Failures in Ports
67(1)
3.5.3 Reliability Indexes
68(1)
3.6 Lifecycle Cost
69(2)
3.6.1 Fuel Cell Lifetime Degradation Model
69(1)
3.6.2 Energy Storage Lifetime Degradation Model
70(1)
3.7 Quality of Service
71(1)
3.7.1 Comfort Level of Passengers
71(1)
3.7.2 Satisfaction Degree of Berthed-in Ships
72(1)
References
72(5)
4 Formulation and Solution of Maritime Grids Optimization 77(20)
4.1 Synthesis-Design-Operation (SDO) Optimization
77(1)
4.2 Coordination Between Maritime Grids
78(1)
4.3 Topologies of Maritime Grids
79(6)
4.3.1 Topologies of Ship Power Systems
80(3)
4.3.2 Topologies of Seaport Microgrids
83(1)
4.3.3 Topologies of Other Maritime Grids
84(1)
4.4 Synthesis-Design-Operation Optimization of Maritime Grids
85(6)
4.4.1 Synthesis Optimization for Maritime Grids
85(3)
4.4.2 Design and Operation Optimization for Maritime Grids
88(3)
4.5 Formulation and Solution of SDO Optimization
91(3)
4.5.1 The Compact Form of SDO Optimization
91(1)
4.5.2 Classification of the Solution Method
92(1)
4.5.3 Decomposition-Based Solution Method
93(1)
References
94(3)
5 Energy Management of Maritime Grids Under Uncertainties 97(28)
5.1 Introductions of Uncertainties in Maritime Grids
97(3)
5.1.1 Different Types of Uncertainties
97(2)
5.1.2 Effects of Electrification for Uncertainties
99(1)
5.2 Navigation Uncertainties
100(4)
5.2.1 Uncertain Wave and Wind
100(1)
5.2.2 Adverse Weather Conditions
101(2)
5.2.3 Calls-for-Service Uncertainties
103(1)
5.3 Energy Source Uncertainties
104(4)
5.3.1 Renewable Energy Uncertainties
104(1)
5.3.2 Main Grid Uncertainties
105(1)
5.3.3 Equipment Uncertainties
106(2)
5.4 Data-Driven Optimization with Uncertainties
108(3)
5.4.1 General Model
108(1)
5.4.2 Data-Driven Stochastic Modeling
109(1)
5.4.3 Data-Driven Robust Modeling
109(2)
5.5 Typical Problems
111(9)
5.5.1 Energy Management for Photovoltaic (PV) Uncertainties in AES
111(6)
5.5.2 Energy Management for Navigation Uncertainties in AES
117(3)
References
120(5)
6 Energy Storage Management of Maritime Grids 125(24)
6.1 Introduction to Energy Storage Technologies
125(2)
6.2 Characteristics of Different Energy Storage Technologies
127(4)
6.2.1 Classifications of Current Energy Storage Technologies
127(1)
6.2.2 Battery
128(1)
6.2.3 Flywheel
129(1)
6.2.4 Ultracapacitor
130(1)
6.3 Applications of Energy Storage in Maritime Grids
131(5)
6.3.1 Roles of Energy Storage in Maritime Grids
131(1)
6.3.2 Navigation Uncertainties and Demand Response
132(2)
6.3.3 Renewable Energy Integration
134(1)
6.3.4 Energy Recovery for Equipment
135(1)
6.4 Typical Problems
136(10)
6.4.1 Energy Storage Management in AES for Navigation Uncertainties
136(3)
6.4.2 Energy Storage Management in AES for Extending Lifetime
139(7)
References
146(3)
7 Multi-energy Management of Maritime Grids 149(24)
7.1 Concept of Multi-energy Management
149(3)
7.1.1 Motivation and Background
149(1)
7.1.2 Classification of Multi-energy Systems
150(2)
7.2 Future Multi-energy Maritime Grids
152(4)
7.2.1 Multi-energy Nature of Maritime Grids
152(2)
7.2.2 Multi-energy Cruise Ships
154(1)
7.2.3 Multi-energy Seaport
155(1)
7.3 General Model and Solving Method
156(4)
7.3.1 Compact Form Model
156(1)
7.3.2 A Decomposed Solving Method
157(3)
7.4 Typical Problems
160(10)
7.4.1 Multi-energy Management for Cruise Ships
160(3)
7.4.2 Multi-energy Management for Seaport Microgrids
163(7)
References
170(3)
8 Multi-source Energy Management of Maritime Grids 173(12)
8.1 Multiples Sources in Maritime Grids
173(4)
8.1.1 Main Grid
173(1)
8.1.2 Main Engines
173(1)
8.1.3 Battery and Fuel Cell
174(2)
8.1.4 Renewable Energy and Demand Response
176(1)
8.2 Coordination Between Multiple Sources in Maritime Grids
177(1)
8.3 Some Representative Coordination Cases
178(4)
8.3.1 Main Engine-Battery Coordination in AES
178(1)
8.3.2 Main Engine-Fuel Cell Coordination in AES
179(2)
8.3.3 Demand Response Coordination Within Seaports
181(1)
References
182(3)
9 The Ways Ahead 185
9.1 Future Maritime Grids
185(2)
9.2 Data-Driven Technologies
187(6)
9.2.1 Navigation Uncertainty Forecasting
187(1)
9.2.2 States of Battery Energy Storage
187(3)
9.2.3 Fuel Cell Degradation
190(2)
9.2.4 Renewable Energy Forecasting
192(1)
9.3 Siting and Sizing Problems
193(5)
9.3.1 Energy Storage Integration
193(4)
9.3.2 Fuel Cell Integration
197(1)
9.4 Energy Management
198(1)
9.5 Summary
199(1)
References
199
Dr. Sidun Fang, born in 1991, received the B.E degree in the School of Electrical Engineering, Chongqing University, Chongqing, China, in 2012, and his Ph.D. degree of Power System and its automation in the School of Electronics Information and Electrical Engineering, Shanghai Jiaotong University, Shanghai, China, in 2017. Then he serves as a Research Fellow in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore till 2020. Now he is a postdoctoral fellow in the Chinese University of Hong Kong. His research interests include optimal operation of mobile microgrids. Dr. Fang was awarded the Outstanding Graduate prize of Shanghai Jiaotong University and his doctoral dissertation was nominated as the Excellent Dissertation Papers in Shanghai Jiaotong University in 2017. He has organized many special issues in journals and was invited as tutorial presenters in various top-tier international conferences. He also serves as the associate editor of International Transactions on Electrical Energy Systems. 





Dr. Hongdong Wang, born in 1989, received the degrees of undergraduate, master and Ph. D in Naval Architecture and Marine Engineering in Shanghai Jiaotong University. Dr. Wang is now the associate professor and doctoral supervisor in school of Naval Architecture, Ocean & Civil Engineering. Meanwhile, Dr. Wang is now the member of Youth Working Committee in the Chinese society of Naval architects and Marine Engineers and the director of China Association of the National Shipbuilding industry in Shanghai. His research area focuses on the development and effectiveness evaluation of marine intelligent equipment, and the intelligent control based on the dynamic properties of marine equipment. More than 40 research papers in above area have been published, while 15 patents have been authorized. In addition, amounts of projects are directed by Dr. Wang from National Natural Science Foundation of China,sub-program of National Key Research and Development Program of China and so on. Whats more, Dr. Wang is sponsored by China Association of Science and Technology Youth Talent Support Project and Shanghai Sailing Program.