Assessment of wave energy resources in Hawaii

2011 ◽  
Vol 36 (2) ◽  
pp. 554-567 ◽  
Author(s):  
Justin E. Stopa ◽  
Kwok Fai Cheung ◽  
Yi-Leng Chen
Keyword(s):  
2021 ◽  
Vol 302 ◽  
pp. 117492
Author(s):  
Andrea Lira-Loarca ◽  
Francesco Ferrari ◽  
Andrea Mazzino ◽  
Giovanni Besio

Author(s):  
Jose V. Taboada ◽  
Hirpa G. Lemu

This paper describes a wave energy analysis of North Atlantic waters and provides an overview of the available resources. The analysis was conducted using a scatter diagram data combined with wave statistics and empirical parameters given by wave height and periods. Such an overview is instrumental for modelling of wave energy sources, design of wave energy converter (WEC) devices and determination of locations of the devices. Previous survey of wave energy resources widely focused on determination of the reliability on installations of WECs. Though the renewable energy source that can be utilized from the waves is huge, the innovative work in design and development of WECs is insignificant and the available technologies still require further optimization. Furthermore, the wave potential of North Atlantic waters is not sufficiently studied and documented. Closer review of the literature also shows that wave energy conversion technology, compared with other conversion machines of renewable energy sources such as wind energy and solar energy, seems still immature and most of the research and development efforts in this direction are limited in scope. The design of energy converters is also highly dictated by the wave energy resource intensity distribution, which varies from North to South hemisphere. The immaturity of the technology can be attributed to several factors. Since there are a number of uncertainties on the accuracy of wave data, the design, location and installation of WECs face a number of challenges in terms of their service life, structural performance and topological configuration. As a result, collection and assessment of wave characteristics and the wave state conditions data serve as key inputs for development of robust, reliable, operable and affordable wave energy converters. The fact that a number of variables are involved in wave distribution characteristics and the extraction of wave power, treating these variables in the design process imposes immense challenges for the design optimization and hence the optimum energy conversion. The conversion machines are expected to extract as high wave energy as possible while their structural performance is ensured. The study reported in this paper is to analyse wave data over several years of return periods with a detailed validation for wave statistics and wave power. The analysis is intended to contribute in better understanding of the wave characteristics with influencing parameters that can serve as design optimization parameters. A method is proposed to conduct a survey and analysis of the available wave energy resources and the potential at cited locations. The paper concludes that wave energy data accuracy is the baseline for project scoping, coastal and offshore design, and environmental impact assessments.


2013 ◽  
Vol 57 ◽  
pp. 330-338 ◽  
Author(s):  
Bingchen Liang ◽  
Fei Fan ◽  
Zegao Yin ◽  
Hongda Shi ◽  
Dongyong Lee

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 902
Author(s):  
Ophelie Choupin ◽  
Michael Henriksen ◽  
Amir Etemad-Shahidi ◽  
Rodger Tomlinson

Wave energy converters (WECs) can play a significant role in the transition towards a more renewable-based energy mix as stable and unlimited energy resources. Financial analysis of these projects requires WECs cost and WEC capital expenditure (CapEx) information. However, (i) cost information is often limited due to confidentiality and (ii) the wave energy field lacks flexible methods for cost breakdown and parameterisation, whereas they are needed for rapid and optimised WEC configuration and worldwide site pairing. This study takes advantage of the information provided by Wavepiston to compare different costing methods. The work assesses the Froude-Law-similarities-based “Similitude method” for cost-scaling and introduces the more flexible and generic “CapEx method” divided into three steps: (1) distinguishing WEC’s elements from the wave energy farm (WEF)’s; (2) defining the parameters characterising the WECs, WEFs, and site locations; and (3) estimating elements that affect WEC and WEF elements’ cost and translate them into factors using the parameters defined in step (2). After validation from Wavepiston manual estimations, the CapEx method showed that the factors could represent up to 30% of the cost. The Similitude method provided slight cost-overestimations compared to the CapEx method for low WEC up-scaling, increasing exponentially with the scaling.


2014 ◽  
Vol 33 (1) ◽  
pp. 92-101 ◽  
Author(s):  
Chongwei Zheng ◽  
Longtan Shao ◽  
Wenli Shi ◽  
Qin Su ◽  
Gang Lin ◽  
...  

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