An Overview of Optimization Methods for Tidal Instream and Wind Turbines Farms

被引:0
|
作者
Fituri, Ali [1 ]
Aly, Hamed H. [1 ,2 ]
El-Hawary, M. E. [1 ]
机构
[1] Dalhousie Univ, Dept Elect & Comp Engn, Halifax, NS, Canada
[2] Zagazig Univ, Zagazig, Egypt
来源
2017 IEEE ELECTRICAL POWER AND ENERGY CONFERENCE (EPEC) | 2017年
关键词
Array; Design; Optimization; Sizing; Tidal Instream Farm; Tidal Instream Turbine; Wind Turbine; GENETIC ALGORITHM; DESIGN; SYSTEM; LAYOUT;
D O I
暂无
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
Renewable energy resources have a positive environmental impact and are considered as a vital source of pollution free energy. Tidal instream and wind energy use similar techniques for generating electrical energy. Wind energy cost is still lower than tidal instream energy cost. However Tidal instream speed is more predictable than wind speed. Researchers are still working on tidal instream to reduce the energy extraction cost. Optimization is one of the best tools used to minimize the cost depending on some constraints. This paper is exploring different optimization tools for wind and tidal instream energies. Three different concepts are discussed using various tools for both types of energy. The fist concept is using arrays layout arrangements for the optimum performance. The second concept consider the turbine parameters for the minimum energy cost. The third concept depends on the coordination between several types of energy sources and the location of the units for the minimum cost.
引用
收藏
页码:458 / 462
页数:5
相关论文
共 50 条
  • [31] Active power dispatch optimization for offshore wind farms considering fatigue distribution
    Liao, Hao
    Hu, Weihao
    Wu, Xiawei
    Wang, Ni
    Liu, Zhou
    Huang, Qi
    Chen, Cong
    Chen, Zhe
    RENEWABLE ENERGY, 2020, 151 : 1173 - 1185
  • [32] Integrated aero-structural optimization of wind turbines
    Bottasso, C. L.
    Bortolotti, P.
    Croce, A.
    Gualdoni, F.
    MULTIBODY SYSTEM DYNAMICS, 2016, 38 (04) : 317 - 344
  • [33] Seeding evolutionary algorithms with heuristics for optimal wind turbines positioning in wind farms
    Saavedra-Moreno, B.
    Salcedo-Sanz, S.
    Paniagua-Tineo, A.
    Prieto, L.
    Portilla-Figueras, A.
    RENEWABLE ENERGY, 2011, 36 (11) : 2838 - 2844
  • [34] Prediction and multi-objective optimization of tidal current turbines considering cavitation based on GA-ANN methods
    Sun, Zhaocheng
    Li, Zengliang
    Fan, Menghao
    Wang, Meng
    Zhang, Le
    ENERGY SCIENCE & ENGINEERING, 2019, 7 (05): : 1896 - 1912
  • [35] An airfoil optimization technique for wind turbines
    Ribeiro, A. F. P.
    Awruch, A. M.
    Gomes, H. M.
    APPLIED MATHEMATICAL MODELLING, 2012, 36 (10) : 4898 - 4907
  • [36] Optimization of wind farm turbines layout using an evolutive algorithm
    Serrano Gonzalez, Javier
    Gonzalez Rodriguez, Angel G.
    Castro Mora, Jose
    Riquelme Santos, Jesus
    Burgos Payan, Manuel
    RENEWABLE ENERGY, 2010, 35 (08) : 1671 - 1681
  • [37] Drivers for optimum sizing of wind turbines for offshore wind farms
    Mehta, Mihir
    Zaaijer, Michiel
    von Terzi, Dominic
    WIND ENERGY SCIENCE, 2024, 9 (01) : 141 - 163
  • [38] Overview of subsynchronous resonance analysis and control in wind turbines
    Ghasemi, Hosein
    Gharehpetian, G. B.
    Nabavi-Niaki, Seyed Ali
    Aghaei, Jamshid
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2013, 27 : 234 - 243
  • [39] New approach on optimization in placement of wind turbines within wind farm by genetic algorithms
    Emami, Alireza
    Noghreh, Pirooz
    RENEWABLE ENERGY, 2010, 35 (07) : 1559 - 1564
  • [40] SUPPORT STRUCTURE OPTIMIZATION FOR OFFSHORE WIND TURBINES WITH A GENETIC ALGORITHM
    Pasamontes, Lucia Barcena
    Torres, Fernando Gomez
    Zwick, Daniel
    Schafhirt, Sebastian
    Muskulus, Michael
    33RD INTERNATIONAL CONFERENCE ON OCEAN, OFFSHORE AND ARCTIC ENGINEERING, 2014, VOL 9B: OCEAN RENEWABLE ENERGY, 2014,