Fast economic model predictive control for marine current turbine generator system

被引:4
作者
Teng, Yiming [1 ]
Hu, Dewen [1 ]
Wu, Feng [1 ]
Zhang, Ridong [1 ]
Gao, Furong [2 ]
机构
[1] Hangzhou Dianzi Univ, Informat & Control Inst, Hangzhou 310018, Peoples R China
[2] Hong Kong Univ Sci & Technol, Dept Chem & Biol Engn, Kowloon, Clear Water Bay, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Marine current turbine; Power generation optimization; System modeling; Fast economic MPC; RENEWABLE ENERGY; POWER; IMPLEMENTATION;
D O I
10.1016/j.renene.2020.11.136
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper considers the optimal operation of the ocean current turbine power generation system. Based on the model construction of the ocean current turbine system, the model predictive control strategy with economic indicators as the main consideration and the system focusing on real-time control issues are used. It is known that the quadratic form complicates the process to be solved, thereby increasing the solution time. For some complex formulation settings, although the system optimization problem can be solved more effectively, the complexity of the system is increased and the calculation time is increased. Therefore, this paper considers an optimal control that can be obtained fast enough for real-time optimization of the feedback scheme. The economic model predictive control framework is proposed in the paper, with the sensitivity components to solve the formulation, and the paper also consider an iterative optimization algorithm to enhance and improve the response speed of the system without affecting the economics of the system. Finally, all of these concepts are demonstrated on a detailed case study of a marine current turbine generator system. (C) 2020 Elsevier Ltd. All rights reserved.
引用
收藏
页码:108 / 116
页数:9
相关论文
共 38 条
[1]   Power and thrust measurements of marine current turbines under various hydrodynamic flow conditions in a cavitation tunnel and a towing tank [J].
Bahaj, A. S. ;
Molland, A. F. ;
Chaplin, J. R. ;
Batten, W. M. J. .
RENEWABLE ENERGY, 2007, 32 (03) :407-426
[2]   Fundamentals applicable to the utilisation of marine current turbines for energy production [J].
Bahaj, AS ;
Myers, LE .
RENEWABLE ENERGY, 2003, 28 (14) :2205-2211
[3]  
Ben Elghali SE, 2007, IEEE IEMDC 2007: PROCEEDINGS OF THE INTERNATIONAL ELECTRIC MACHINES AND DRIVES CONFERENCE, VOLS 1 AND 2, P1407
[4]  
Bir G.S., 2015, ASME 30 INT C OC ROT, V5, P797
[5]   Dynamic Safety Constraints by Scenario-Based Economic Model Predictive Control of Marine Electric Power Plants [J].
Bo, Torstein I. ;
Johansen, Tor Arne .
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2017, 3 (01) :13-21
[6]   The economics of tidal energy [J].
Denny, Eleanor .
ENERGY POLICY, 2009, 37 (05) :1914-1924
[7]   A hybrid prognostic methodology for tidal turbine gearboxes [J].
Elasha, Faris ;
Mba, David ;
Togneri, Michael ;
Masters, Ian ;
Teixeira, Joao Amaral .
RENEWABLE ENERGY, 2017, 114 :1051-1061
[8]   Wave energy utilization: A review of the technologies [J].
Falcao, Antonio F. de O. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2010, 14 (03) :899-918
[9]   Biomass energy: the scale of the potential resource [J].
Field, Christopher B. ;
Campbell, J. Elliott ;
Lobell, David B. .
TRENDS IN ECOLOGY & EVOLUTION, 2008, 23 (02) :65-72
[10]   Integrated design and implementation of 120-kW horizontal-axis tidal current energy conversion system [J].
Gu, Ya-jing ;
Liu, Hong-wei ;
Li, Wei ;
Lin, Yong-gang ;
Li, Yang-jian .
OCEAN ENGINEERING, 2018, 158 :338-349