The Optimal Configuration of Wave Energy Conversions Respective to the Nearshore Wave Energy Potential

被引:11
作者
Shadmani, Alireza [1 ]
Nikoo, Mohammad Reza [2 ]
Al-Raoush, Riyadh, I [3 ]
Alamdari, Nasrin [4 ]
Gandomi, Amir H. [5 ]
机构
[1] Amirkabir Univ Technol, Dept Maritime Engn, POB 15875-4413, Tehran, Iran
[2] Sultan Qaboos Univ, Coll Engn, Dept Civil & Architectural Engn, Muscat 123, Oman
[3] Qatar Univ, Dept Civil & Architectural Engn, POB 2713, Doha, Qatar
[4] Florida State Univ, Dept Civil & Environm Engn, Tallahassee, FL 32306 USA
[5] Univ Technol Sydney, Fac Engn & Informat Technol, Ultimo, NSW 2007, Australia
关键词
wave energy; wave energy converters; optimal configuration; nearshore sites; evolutionary algorithms; POWER TAKE-OFF; POINT ABSORBER; SHAPE OPTIMIZATION; CONSTRAINED OPTIMIZATION; RESOURCE ASSESSMENT; GENETIC ALGORITHM; RENEWABLE ENERGY; COASTAL REGIONS; PART I; CONVERTER;
D O I
10.3390/en15207734
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
Ocean energy is one potential renewable energy alternative to fossil fuels that has a more significant power generation due to its better predictability and availability. In order to harness this source, wave energy converters (WECs) have been devised and used over the past several years to generate as much energy and power as is feasible. While it is possible to install these devices in both nearshore and offshore areas, nearshore sites are more appropriate places since more severe weather occurs offshore. Determining the optimal location might be challenging when dealing with sites along the coast since they often have varying capacities for energy production. Constructing wave farms requires determining the appropriate location for WECs, which may lead us to its correct and optimum design. The WEC size, shape, and layout are factors that must be considered for installing these devices. Therefore, this review aims to explain the methodologies, advancements, and effective hydrodynamic parameters that may be used to discover the optimal configuration of WECs in nearshore locations using evolutionary algorithms (EAs).
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页数:29
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