原文信息：
Consensus-based decentralized scheduling method for collaborative operation in seaport virtual power plant
原文链接：
https://www.sciencedirect.com/science/article/pii/S0306261924012182
Highlights
• Vessels serve as mobile energy storage units, supporting V2S and V2V transfers.
• An energy sharing scheduling method is proposed to enhance SVPP flexibility.
• A decentralized optimization framework is designed to protect entity privacy.
• V2S and V2V economics are analyzed across three operational scenarios.
Abstract
The accelerating trend towards electrification in seaport operations presents the opportunities for ports to achieve near zero and decarbonization strategies. However, integrating a large number of flexible resources into seaport energy systems introduces complex management challenges, including the need for coordinated charging of electrified vessels and the optimized energy utilization of seaport equipment. To address these challenges, we establish a seaport virtual power plant (SVPP) system model and an energy service model that leverages the concepts of vessel-to-shore (V2S) and vessel-to-vessel (V2V) for facilitating diverse energy transfer modes among the grid, shore, and vessels. To unlock the flexible value of electrified vessels, we propose an energy sharing scheduling method that integrates a hybrid V2S and V2V mode. This method considers the diversity in vessel berthing durations and charging demands, utilizing V2V interaction mechanisms among electrified vessels to determine the optimal shore-vessel scheduling schemes. To ensure the privacy and reliability of multi-entity operations, we design a decentralized energy management algorithm for the SVPP based on the consensus alternating direction method of multipliers (ADMM). A decentralized optimization framework is designed based on the consensus mechanism. By introducing coupling information as consensus variables, we fully decouple the operations of multiple owners and solve the primal optimization problem in parallel. Additionally, by formulating two baseline optimization problems, we evaluate the effects of V2S and V2V on the overall SVPP and on the individual vessels. Simulation results demonstrate that introducing V2S can reduce the total cost by 13.68%, while the further integration of V2V can achieve a cost reduction of 26.56%. Notably, V2V interactions enhance the scheduling potential, particularly for vessels with longer berthing durations.
Keywords
Seaport virtual power plant
Electrified vessel
Vessel-to-vessel
Energy trading
Decentralized optimization
Graphics
Fig. 1. Overview of the proposed method.
图1 所提出方法的概述
Fig. 2. The structure of the seaport virtual power plant.
图2 海港虚拟电厂的结构
Fig. 3. Scenarios of seaport virtual power plant include the US scenario, the BI scenario, and the ES scenario.
图3 海港虚拟电厂场景，包括US场景、BI场景、ES场景
Fig. 4. The operational process of the consensus-based decentralized energy management algorithm.
图4 基于共识的去中心化能源管理算法的运行流程。
Fig. 5. Power generation profiles of the main grid. (a) US scenario, (b) BI scenario, (c) ES scenario.
图5 主电网发电概况 (a) US场景，(b) BI 场景，(c) ES 场景
Fig. 6. Vessel energy trading for 60 vessels under ES scenario: (a) V2S energy trading, (b) V2V energy trading.
图 6 ES场景下60艘船舶的船舶能源交易：(a) V2S能源交易，(b) V2V能源交易。
本研究由武汉理工大学自动化学院、莫纳什大学信息技术学院和湖北经济学院信息工程学院的研究人员共同完成。
通信作者简介：
苏义鑫，教授，博士生导师，中国电源学会理事，湖北省自动化学会副理事长，中国指挥与控制学会智能控制与系统专业委员会常委，2010.06-2022.06 担任武汉理工大学自动化学院副院长。现主要研究方向包括：新能源系统建模与优化、新型配电网、智能控制、机器学习、智能船舶等。在Neural Computing and Applications, IEEE Systems Journal, Ocean Engineering, IEEE Transactions on Instrumentation & Measurement, IEEE Transactions on Circuits and Systems II, 控制与决策等国内外重要期刊和重要国际会议发表学术论文120余篇，其中50余篇被 SCI检索。获得授权发明专利10余项。
第一作者简介：
熊畅，于武汉理工大学自动化学院攻读博士学位，主要研究方向为虚拟电厂优化调度、分布式能源管理与优化、智能电网通信网络控制等，以第一作者发表SCI检索论文3篇，授权国家发明专利1项。
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