Real-time hybrid controls of energy storage and load shedding for integrated power and energy systems of ships

被引:4
作者
Vu, Linh [1 ]
Nguyen, Thai-Thanh [2 ]
Nguyen, Bang Le-Huy [3 ]
Anam, Md. Isfakul [1 ]
Vu, Tuyen [1 ]
机构
[1] Clarkson Univ, Potsdam, Germany
[2] New York Power Author NYPA, Adv Grid Innovat Lab Energy AGILe, New York, NY USA
[3] Los Alamos Natl Lab, Los Alamos, NM USA
关键词
Energy management; Ship power system; Resilience; Load shedding; Energy storage system; Receding horizon optimization; SHIPBOARD POWER; PREDICTIVE CONTROL; OPTIMIZATION METHOD; MANAGEMENT; PERFORMANCE; STRATEGY; FLUCTUATIONS; OPERATION;
D O I
10.1016/j.epsr.2024.110191
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents an original energy management methodology to enhance the resilience of ship power systems. The integration of various energy storage systems (ESS), including battery energy storage systems (BESS) and super-capacitor energy storage systems (SCESS), in modern ship power systems poses challenges in designing an efficient energy management system (EMS). The EMS proposed in this paper aims to achieve multiple objectives. The primary objective is to minimize shed loads, while the secondary objective is to effectively manage different types of ESS. Considering the diverse ramp -rate characteristics of generators, SCESS, and BESS, the proposed EMS exploits these differences to determine an optimal long-term schedule for minimizing shed loads. Furthermore, the proposed EMS balances the state -of -charge (SoC) of ESS and prioritizes the SCESS's SoC levels to ensure the efficient operation of BESS and SCESS. For better computational efficiency, we introduce the receding horizon optimization method, enabling real -time EMS implementation. A comparison with the fixed horizon optimization (FHO) validates its effectiveness. Simulation studies and results demonstrate that the proposed EMS efficiently manages generators, BESS, and SCESS, ensuring system resilience under generation shortages. Additionally, the proposed methodology significantly reduces the computational burden compared to the FHO technique while maintaining acceptable resilience performance.
引用
收藏
页数:12
相关论文
共 63 条
  • [1] MPC Framework for the Energy Management of Hybrid Ships with an Energy Storage System
    Antonopoulos, Spyros
    Visser, Klaas
    Kalikatzarakis, Miltiadis
    Reppa, Vasso
    [J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2021, 9 (09)
  • [2] Anvari-Moghaddam A, 2016, IEEE IND ELEC, P2095, DOI 10.1109/IECON.2016.7793272
  • [3] Power System Resilience: Current Practices, Challenges, and Future Directions
    Bhusal, Narayan
    Abdelmalak, Michael
    Kamruzzaman, Md
    Benidris, Mohammed
    [J]. IEEE ACCESS, 2020, 8 (08): : 18064 - 18086
  • [4] Model and Load Predictive Control for Design and Energy Management of Shipboard Power Systems
    Bijaieh, Mehrzad Mohammadi
    Vedula, Satish
    Anubi, Olugbenga Moses
    [J]. 5TH IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (IEEE CCTA 2021), 2021, : 607 - 612
  • [5] Distributed optimization and statistical learning via the alternating direction method of multipliers
    Boyd S.
    Parikh N.
    Chu E.
    Peleato B.
    Eckstein J.
    [J]. Foundations and Trends in Machine Learning, 2010, 3 (01): : 1 - 122
  • [6] Energy management strategy for hybrid power ships based on nonlinear model predictive control
    Chen, Long
    Gao, Diju
    Xue, Qimeng
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2023, 153
  • [7] Robust Real-Time Shipboard Energy Management System With Improved Adaptive Model Predictive Control
    Chen, Wenjie
    Tai, Kang
    Lau, Michael Wai Shing
    Abdelhakim, Ahmed
    Chan, Ricky R.
    Adnanes, Alf Kare
    Tjahjowidodo, Tegoeh
    [J]. IEEE ACCESS, 2023, 11 : 110342 - 110360
  • [8] Optimal Power and Energy Management Control for Hybrid Fuel Cell-Fed Shipboard DC Microgrid
    Chen, Wenjie
    Tai, Kang
    Lau, Michael Wai Shing
    Abdelhakim, Ahmed
    Chan, Ricky R.
    Adnanes, Alf Kare
    Tjahjowidodo, Tegoeh
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (12) : 14133 - 14150
  • [9] Performance Metrics for Electric Warship Integrated Engineering Plant Battle Damage Response
    Cramer, Aaron M.
    Sudhoff, Scott D.
    Zivi, Edwin L.
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2011, 47 (01) : 634 - 646
  • [10] Dynamic Simulation-Based Analysis of a New Load Shedding Scheme for a Notional Destroyer-Class Shipboard Power System
    Ding, Zhiping
    Srivastava, Sanjeev K.
    Cartes, David A.
    Suryanarayanan, Siddharth
    [J]. IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2009, 45 (03) : 1166 - 1174