Online Energy Management Strategy Based on Adaptive Model Predictive Control for Microgrid with Hydrogen Storage

被引:0
|
作者
Ma, Jun [1 ]
Baysal, Mustafa [1 ]
机构
[1] Yildiz Tech Univ, Fac Elect & Elect, Dept Elect Engn, Istanbul, Turkey
关键词
Adaptive Model Predictive Control; Hydrogen Fuel Cell; Microgrid; Online Energy Management Strategy;
D O I
10.20508/IJRER.V8I2.7493.G7409
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Energy management optimization is still a big challenge for Microgrid, which includes Renewable Energy and Hydrogen Fuel Cell. In this paper, an online Adaptive Model Predictive Control (AMPC) based Energy Management Strategy (EMS) is proposed to increase the energy sources lifetime of the microgrid while minimizing hydrogen consumption. The EMS problem is simplified according to the control structure of microgrid system and the cost function of system is built and transferred to standard format of the Quadratic Programming problem to solve. Moreover, adaptive algorithm is used to automatically adjust the weights of different targets according to the states of system. It is shown by simulation results for different cases from MATLAB-Simulink (TM) that proposed EMS has significant effects on controlling State-of-Charge (SoC) of battery and a noticeable improvement on extension of Hydrogen Fuel Cell lifetime and battery charge-sustainability.
引用
收藏
页码:861 / 870
页数:10
相关论文
共 50 条
  • [41] A Power Distribution Strategy for Hybrid Energy Storage System Using Adaptive Model Predictive Control
    Wang, Li
    Wang, Yujie
    Liu, Chang
    Yang, Duo
    Chen, Zonghai
    IEEE TRANSACTIONS ON POWER ELECTRONICS, 2020, 35 (06) : 5897 - 5906
  • [42] Hybrid Energy Storage Control Strategy Based on Energy Prediction for Photovoltaic Microgrid
    Gao, Wengen
    Yu, Yue
    Wang, Ning
    Lu, Huacai
    Zhang, Mei
    2021 PROCEEDINGS OF THE 40TH CHINESE CONTROL CONFERENCE (CCC), 2021, : 1990 - 1996
  • [43] Energy Management and Control Strategy of DC Microgrid Including Multiple Energy Storage Systems
    Sayed, Khairy
    Kassem, Ahmed M.
    Aboelhassan, Ismail
    Aly, Abdelmaged M.
    Abo-Khalil, Ahmed G.
    2019 21ST INTERNATIONAL MIDDLE EAST POWER SYSTEMS CONFERENCE (MEPCON 2019), 2019, : 736 - 741
  • [44] A Coordinated Multitimescale Model Predictive Control for Output Power Smoothing in Hybrid Microgrid Incorporating Hydrogen Energy Storage
    Abdelghany, Muhammad Bakr
    Al-Durra, Ahmed
    Zeineldin, Hatem H.
    Gao, Fei
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2024, 20 (09) : 10987 - 11001
  • [45] Empowering Microgrid Energy Management with Artificial Intelligence and Model Predictive Control
    Dankir, S.
    Puig, V.
    Lasri, R.
    Maatoui, Y.
    Chekenbah, H.
    IFAC PAPERSONLINE, 2024, 58 (13): : 436 - 441
  • [46] RESEARCH ON CONTROL STRATEGY OF PV STORAGE DC MICROGRID BASED ON ADAPTIVE DROOP CONTROL
    Dai, Li
    Wang, Junrui
    Tan, Lu
    Zhu, Xuqiang
    Wang, Ming
    Dou, Shuai
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2024, 45 (08): : 154 - 163
  • [47] Particle Swarm Optimization - Model Predictive Control for Microgrid Energy Management
    Van Quyen Ngo
    Al-Haddad, Kamal
    Kim Khoa Nguyen
    2020 ZOOMING INNOVATION IN CONSUMER TECHNOLOGIES CONFERENCE (ZINC), 2020, : 264 - 269
  • [48] Energy Management Strategy for Hybrid Electric Vehicles Based on Adaptive Equivalent Ratio-Model Predictive Control
    Ali, Farah Mahdi
    Abbas, Nizar Hadi
    ELECTRICITY, 2024, 5 (04): : 972 - 990
  • [49] Hybrid Energy Storage Control of Microgrid Based on Adaptive Consistency Algorithm
    Yan Yao
    Kang Jiale
    Zhou Xuntian
    Zhang Zhigang
    Cen Yinwei
    2022 6TH INTERNATIONAL CONFERENCE ON POWER AND ENERGY ENGINEERING, ICPEE, 2022, : 91 - 95
  • [50] Constrained hybrid optimal model predictive control for intelligent electric vehicle adaptive cruise using energy storage management strategy
    Zhang, Ronghui
    Wu, Na
    Wang, Zihan
    Li, Kening
    Song, Zhumei
    Chang, Zhenting
    Chen, Xia
    Yu, Fan
    JOURNAL OF ENERGY STORAGE, 2023, 65