Decentralized Model Predictive Control for Offshore Wind-Powered Seaport DC Microgrids With Electric Vehicle Stations

IF 4.2 2区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Industry Applications Pub Date : 2025-01-21 DOI:10.1109/TIA.2025.3532585

Muhammad Sadiq;Chun-Lien Su;Zulfiqar Ali;Seyed Hossein Rouhani;Milan Straka;Lubos Buzna;Alexander Micallef;Giuseppe Parise

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引用次数: 0

Abstract

The rapid adoption of electric vehicles (EVs) has catalyzed the urgency of a resilient and sustainable charging infrastructure. This study addresses this issue by harnessing offshore wind energy resources to meet the charging demands, particularly in remote coastal regions. The primary challenge tackled in this research involves the complex management of power flow dynamics due to the inherent variability of wind energy and the stochastic nature of EV charging demands, modeled using probabilistic distributions to represent varying arrival times, charging durations, and power requirements of EVs. This work introduces a pioneering framework centered on the development of a wind-powered electric vehicle charging system (EVCS) that utilizes a medium-voltage direct current (MVDC) bus. An enhanced decentralized model predictive control (MPC) strategy was employed that distinguishes itself from conventional control paradigms due to its heightened adaptability and proficient management of the dynamic interactions among wind energy generation, energy storage systems (ESS), EV charging demands, and grid interactions. Rigorous simulations and real-time hardware-in-loop studies underscore the efficacy of the MPC strategy in preserving the voltage stability within the MVDC bus while optimizing the power flow, thereby minimizing energy losses and ensuring grid resilience. These results validate the viability of the proposed wind energy-integrated EVCS as an integral component of seaport grid infrastructure.

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带有电动汽车站的海上风力海港直流微电网的分散模型预测控制

电动汽车（EV）的迅速普及催化了建立弹性和可持续充电基础设施的紧迫性。本研究通过利用近海风能资源来满足充电需求，尤其是偏远沿海地区的充电需求，从而解决这一问题。这项研究面临的主要挑战涉及复杂的电力流动态管理，这是由于风能固有的可变性和电动汽车充电需求的随机性造成的。这项研究提出了一个开创性的框架，其核心是开发一个利用中压直流（MVDC）总线的风力电动汽车充电系统（EVCS）。该系统采用了增强型分散模型预测控制（MPC）策略，由于其适应性更强，并能熟练管理风能发电、储能系统（ESS）、电动汽车充电需求和电网互动之间的动态交互，因此有别于传统的控制范例。严格的模拟和实时硬件在环研究强调了 MPC 策略在优化电力流的同时保持 MVDC 总线内电压稳定性的功效，从而最大限度地减少了能源损耗并确保了电网的恢复能力。这些结果验证了拟议的风能集成 EVCS 作为海港电网基础设施组成部分的可行性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Industry Applications 工程技术-工程：电子与电气

CiteScore

9.90

自引率

9.10%

发文量

747

审稿时长

3.3 months

期刊介绍： The scope of the IEEE Transactions on Industry Applications includes all scope items of the IEEE Industry Applications Society, that is, the advancement of the theory and practice of electrical and electronic engineering in the development, design, manufacture, and application of electrical systems, apparatus, devices, and controls to the processes and equipment of industry and commerce; the promotion of safe, reliable, and economic installations; industry leadership in energy conservation and environmental, health, and safety issues; the creation of voluntary engineering standards and recommended practices; and the professional development of its membership.