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)

This book explores energy management strategies for large ports, emphasizing the need for low-carbon and green port operations. It examines the integration of logistics and energy subsystems, focusing on renewable energy sources like wind and solar, and clean fuels such as natural gas and hydrogen. The book discusses advanced technologies like energy storage systems and electric yard cranes, and their role in optimizing energy use and reducing emissions. It also analyzes the interaction mechanisms of energy and logistics subsystems, proposing models for energy optimization and management. The intended audience includes researchers, engineers, and policy makers involved in marine energy systems. Generated by AI.

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.