Energy Management of Integrated Energy System in Large Ports.

• Superior document: Springer Series on Naval Architecture, Marine Engineering, Shipbuilding and Shipping Series ; v.18.
• Author: Huang, Wentao.
• TeilnehmendeR: Yu, Moduo.; Li, Hao.; Tai, Nengling.
• 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)

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.