Energy Management of Integrated Energy System in Large Ports.
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| Superior document: | Springer Series on Naval Architecture, Marine Engineering, Shipbuilding and Shipping Series ; v.18. |
|---|---|
| : | |
| TeilnehmendeR: | |
| Place / Publishing House: | Singapore : : Springer Singapore Pte. Limited,, 2024. ©2023. |
| Year of Publication: | 2024 |
| Edition: | First edition. |
| Language: | English |
| Series: | Springer series on naval architecture, marine engineering, shipbuilding and shipping.
|
| Physical Description: | 1 online resource (300 pages) |
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Table of Contents:
- Intro
- Preface
- Contents
- 1 Overview and Research Opportunities in Energy Management for Port Integrated Energy System
- 1.1 Introduction
- 1.2 Low-Carbon Technology in Ports
- 1.2.1 Electric Energy Substitution
- 1.2.2 Renewable Energy
- 1.2.3 Clean Fuel
- 1.2.4 Low-Carbon Port Management
- 1.3 Coupling Mechanism and Modeling for Energy and Logistics
- 1.3.1 Characteristics of Port Logistics Transportation
- 1.3.2 Coupling Mechanism of Energy and Logistics
- 1.3.3 Energy-Based Modeling of Logistics
- 1.4 Energy Management of Green Port Integrated Energy System
- 1.4.1 Port Integrated Energy System
- 1.4.2 Flexible Resources of Green Port
- 1.4.3 Energy Management Model of Port Integrated Energy System
- 1.5 Research Directions of Green Port Integrated Energy System
- 1.5.1 The Current Situation of Typical Ports
- 1.5.2 Future Research Directions
- 1.6 Conclusion
- References
- 2 Optimization Configuration of Renewable Energies and Energy Storages in Port Microgrids
- 2.1 Introduction
- 2.2 Scenario-Based Depiction of the Fluctuating Characteristics of Port Microgrid
- 2.3 High-Fidelity Compression and Reconstruction Method
- 2.3.1 Port Data Extraction and Integration
- 2.3.2 High-Fidelity Compression Based on Operational Week
- 2.3.3 Variable-Time-Scale Data Reconstruction
- 2.3.4 Data Output
- 2.4 Optimal Configuration Model for Port's Renewable Energies and Energy Storages
- 2.4.1 Objective Function
- 2.4.2 Constraints
- 2.5 Case Studies
- 2.5.1 Case Description
- 2.5.2 Analysis of Typical Scenario Results
- 2.5.3 Analysis of Optimization Configuration Results of Renewable Energy and Energy Storage
- 2.5.4 Calculation Time Analysis
- 2.6 Conclusion
- Appendix 1
- Appendix 2
- References
- 3 Adaptive Bidirectional Droop Control Strategy for Hybrid AC-DC Port Microgrids
- 3.1 Introduction.
- 3.2 Hybrid Microgrid and Its Interlinking Converter
- 3.2.1 AC-DC Hybrid Microgrid
- 3.2.2 The Structure of Hybrid Microgrid Interlinking Converter
- 3.3 Bidirectional Adaptive Droop Control Strategy for Interlinking Converter
- 3.3.1 Bidirectional Droop Control Targets
- 3.3.2 Adaptive Bidirectional Droop Control Strategy
- 3.3.3 Start-Up Conditions
- 3.4 Small-Signal Modeling and Stability Analysis of Interlinking Converter
- 3.5 Simulations
- 3.5.1 Scenario 1: Load Variation
- 3.5.2 Scenario 2: DG Output Change or on/off Switch
- 3.6 RT-LAB Simulation Verification
- 3.6.1 Scenario 1: Weak AC Microgrid and Strong DC Microgrid
- 3.6.2 Scenario 2: Strong AC Microgrid and Weak DC Microgrid
- 3.7 Conclusion
- References
- 4 Flexible Connected Multiple Port Microgrids
- 4.1 Introduction
- 4.2 Typical Structure and Characteristics of MMGs
- 4.3 Flexible Interconnection of MMGs
- 4.3.1 HUCC Structure and Operation Mode
- 4.3.2 Flexible Interconnection Solution for HUCC-Based MMGs
- 4.3.3 Operation Modes and Mode Switching of FCMMGs
- 4.4 HUCC-Based Control Strategies for FCMMGs
- 4.4.1 FCMMGs Control Architecture
- 4.4.2 Control Technique for the Central Layer of FCMMGs
- 4.4.3 Control Strategies for the Interface Layer and Microgrid Layer of FCMMGs
- 4.5 Simulations
- 4.5.1 System Architecture and Settings for MMGs
- 4.5.2 Simulation Results
- 4.6 Conclusion
- References
- 5 Smooth Control Strategy for Port-Ship Islanding/Grid-Connected Mode Switching
- 5.1 Introduction
- 5.2 Flexible Interconnected Port-Ship Microgrid and Operation Mode Based on FMS
- 5.2.1 Flexible Interconnected Port-Ship Microgrid Based on FMS
- 5.2.2 Operation Modes of the Flexible Interconnected Port-Ship Microgrid
- 5.2.3 Emergency Switching of Flexible Interconnected Ship-Port Microgrid.
- 5.3 Emergency Mode Switching Control Strategy for Interconnected Port-Ship Microgrid
- 5.3.1 Mode Emergency Switching
- 5.3.2 Flow of Smooth Control for Emergency Switching of Operation Modes
- 5.4 Simulations
- 5.5 Conclusion
- References
- 6 Voltage Optimization Method for Port Power Supply Networks
- 6.1 Introduction
- 6.2 Power Supply Networks with SOPs
- 6.2.1 IPPSNs Structure
- 6.2.2 Structure and Operating Principle of the SOPs
- 6.3 The MPC-Based Voltage Optimization Method
- 6.3.1 Voltage and Power Losses Model
- 6.3.2 IPPSNs Voltage Optimization Model
- 6.4 Implementation of MPC-Based Voltage Optimization Method with SOPs
- 6.5 Case Studies
- 6.5.1 Analysis of All-Day Operation Scenario
- 6.5.2 Analysis of Comparison Study Under Abnormal Scenarios
- 6.5.3 Analysis of Multiple SOPs Installed
- 6.6 Conclusion
- References
- 7 Hierarchical Optimization Scheduling Method for Large-Scale Reefer Loads in Ports
- 7.1 Introduction
- 7.2 Operation Characteristics and Modeling of Reefers
- 7.3 Hierarchical Scheduling Modeling of Reefer Groups
- 7.3.1 Hierarchical Scheduling Architecture
- 7.3.2 Dynamic Model of PDC
- 7.3.3 RFA Decision Model
- 7.4 Consensus Based Multi-agent Power Dynamic Distribution Model
- 7.4.1 Refrigeration Efficiency Factor of Reefers
- 7.4.2 Leader-Follower Consensus Algorithm for Refrigeration Efficiency of Multi-agent System
- 7.4.3 Analysis of Power Deviation Adjustment Factor
- 7.5 Solution Methodology
- 7.6 Case Studies
- 7.6.1 Case Description
- 7.6.2 Analysis of Scheduling Results
- 7.6.3 Efficiency Analysis of Consensus Based Multi-agent Hierarchical Optimization
- 7.6.4 LREC Algorithm Analysis
- 7.6.5 Method Accuracy Verification
- 7.7 Conclusion
- References
- 8 Demand Side Response in Ports Considering the Discontinuity of the ToU Tariff
- 8.1 Introduction.
- 8.2 Problem Formulation
- 8.3 The FB-DSR Strategy
- 8.3.1 Day-Ahead Complete-Period DSR Optimization
- 8.3.2 Short-Term Power Volatility Suppression
- 8.4 Case Studies
- 8.4.1 Case Description
- 8.4.2 The Results of the Proposed Strategy
- 8.4.3 Comparative Studies
- 8.4.4 Short-Term Volatility Suppression Effect
- 8.5 Conclusion
- References
- 9 Energy Cascade Utilization of Electric-Thermal Port Microgrids
- 9.1 Introduction
- 9.2 Electric-Thermal Port Microgrids
- 9.2.1 Structure of Electric-Thermal Port Microgrids
- 9.2.2 Cascaded Utilization of the Electric-Thermal Microgrids
- 9.3 Energy Flow Analysis of Cascaded Utilization in Electric-Thermal Port Microgrids
- 9.3.1 The Coupling Relationship of Energy Flow
- 9.3.2 Energy Grade Conversion Model
- 9.3.3 Energy Supply and Demand Analysis
- 9.4 Optimization Strategy for Cascaded Utilization of Electric-Thermal Microgrids
- 9.4.1 Objective Function
- 9.4.2 Constraints
- 9.4.3 Solution Methodology
- 9.5 Case Studies
- 9.5.1 Case Description
- 9.5.2 Results Analysis
- 9.5.3 Economic Analysis of Diverse Energy Supply Structures
- 9.6 Conclusion
- References
- 10 Optimal Coordination Operation of Port Integrated Energy Systems
- 10.1 Introduction
- 10.2 Structure of Port Integrated Energy Systems (PIES)
- 10.3 PIES Formulation
- 10.3.1 Logistics System
- 10.3.2 Energy System
- 10.3.3 The Nexus Between Logistics System and Energy System
- 10.3.4 Coordinated Optimization of PIES
- 10.4 Solution Methodology
- 10.4.1 Linearizing Logistic Constraints
- 10.4.2 Convexifying the Energy Systems Equations
- 10.4.3 The Final Optimization Formulation of PIES
- 10.5 Case Studies
- 10.5.1 Case of Sufficient Berths
- 10.5.2 Case of Berth Congestion
- References
- 11 Joint Scheduling of Power Flow and Berth Allocation in Port Microgrids
- 11.1 Introduction.
- 11.2 Deterministic Joint Scheduling Model
- 11.2.1 Problem Description
- 11.2.2 Objective Function
- 11.2.3 Constraints
- 11.3 DRO-Based Joint Scheduling Model Under Multiple Uncertainties
- 11.3.1 Joint Scheduling Framework
- 11.3.2 Two-Stage Joint Scheduling Model Based on DRO Method
- 11.3.3 Solution Methodology
- 11.4 Case Studies
- 11.4.1 Case Description
- 11.4.2 Comparison of Different Scheduling Model
- 11.4.3 Sensitivity Analysis of System Parameters
- References
- 12 Port Electrification and Integrated Energy Cases
- 12.1 Port Carbon Allowance Projections
- 12.2 Port Energy Consumption and Carbon Emission Projections
- 12.3 Port Low-Carbon Planning
- 12.3.1 Action Plan for Electrification Equipment
- 12.3.2 Action Plan for New Energy
- 12.3.3 Optimization Plan for Collection and Distribution System
- 12.3.4 Operation Process Transformation Plan
- 12.3.5 Action Plan for the Construction of Management Mechanisms.