Joint Modelling of Wave Energy Flux and Wave Direction

In the context of wave resource assessment, the description of wave climate is usually confined to significant wave height and energy period. However, the accurate joint description of both linear and directional wave energy characteristics is essential for the proper and detailed optimization of wa...

Full description

Bibliographic Details
Published in:Processes
Main Authors: Soukissian, Takvor H., Karathanasi, Flora E.
Format: Article in Journal/Newspaper
Language:English
Published: 2021
Subjects:
Online Access:https://zenodo.org/record/7642344
https://doi.org/10.3390/pr9030460
id ftzenodo:oai:zenodo.org:7642344
record_format openpolar
spelling ftzenodo:oai:zenodo.org:7642344 2023-05-15T17:34:09+02:00 Joint Modelling of Wave Energy Flux and Wave Direction Soukissian, Takvor H. Karathanasi, Flora E. 2021-03-04 https://zenodo.org/record/7642344 https://doi.org/10.3390/pr9030460 eng eng info:eu-repo/grantAgreement/EC/Horizon 2020 Framework Programme - Coordination and support action/857586/ https://zenodo.org/communities/cmmi https://zenodo.org/record/7642344 https://doi.org/10.3390/pr9030460 oai:zenodo.org:7642344 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Processes 9(3)(460) wave energy flux wave direction mixture distribution bivariate distribution wave energy converters European seas info:eu-repo/semantics/article publication-article 2021 ftzenodo https://doi.org/10.3390/pr9030460 2023-03-11T00:36:44Z In the context of wave resource assessment, the description of wave climate is usually confined to significant wave height and energy period. However, the accurate joint description of both linear and directional wave energy characteristics is essential for the proper and detailed optimization of wave energy converters. In this work, the joint probabilistic description of wave energy flux and wave direction is performed and evaluated. Parametric univariate models are implemented for the description of wave energy flux and wave direction. For wave energy flux, conventional, and mixture distributions are examined while for wave direction proven and efficient finite mixtures of von Mises distributions are used. The bivariate modelling is based on the implementation of the Johnson–Wehrly model. The examined models are applied on long-term measured wave data at three offshore locations in Greece and hindcast numerical wave model data at three locations in the western Mediterranean, the North Sea, and the North Atlantic Ocean. A global criterion that combines five individual goodness-of-fit criteria into a single expression is used to evaluate the performance of bivariate models. From the optimum bivariate model, the expected wave energy flux as function of wave direction and the distribution of wave energy flux for the mean and most probable wave directions are also obtained. Article in Journal/Newspaper North Atlantic Zenodo Processes 9 3 460
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language English
topic wave energy flux
wave direction
mixture distribution
bivariate distribution
wave energy converters
European seas
spellingShingle wave energy flux
wave direction
mixture distribution
bivariate distribution
wave energy converters
European seas
Soukissian, Takvor H.
Karathanasi, Flora E.
Joint Modelling of Wave Energy Flux and Wave Direction
topic_facet wave energy flux
wave direction
mixture distribution
bivariate distribution
wave energy converters
European seas
description In the context of wave resource assessment, the description of wave climate is usually confined to significant wave height and energy period. However, the accurate joint description of both linear and directional wave energy characteristics is essential for the proper and detailed optimization of wave energy converters. In this work, the joint probabilistic description of wave energy flux and wave direction is performed and evaluated. Parametric univariate models are implemented for the description of wave energy flux and wave direction. For wave energy flux, conventional, and mixture distributions are examined while for wave direction proven and efficient finite mixtures of von Mises distributions are used. The bivariate modelling is based on the implementation of the Johnson–Wehrly model. The examined models are applied on long-term measured wave data at three offshore locations in Greece and hindcast numerical wave model data at three locations in the western Mediterranean, the North Sea, and the North Atlantic Ocean. A global criterion that combines five individual goodness-of-fit criteria into a single expression is used to evaluate the performance of bivariate models. From the optimum bivariate model, the expected wave energy flux as function of wave direction and the distribution of wave energy flux for the mean and most probable wave directions are also obtained.
format Article in Journal/Newspaper
author Soukissian, Takvor H.
Karathanasi, Flora E.
author_facet Soukissian, Takvor H.
Karathanasi, Flora E.
author_sort Soukissian, Takvor H.
title Joint Modelling of Wave Energy Flux and Wave Direction
title_short Joint Modelling of Wave Energy Flux and Wave Direction
title_full Joint Modelling of Wave Energy Flux and Wave Direction
title_fullStr Joint Modelling of Wave Energy Flux and Wave Direction
title_full_unstemmed Joint Modelling of Wave Energy Flux and Wave Direction
title_sort joint modelling of wave energy flux and wave direction
publishDate 2021
url https://zenodo.org/record/7642344
https://doi.org/10.3390/pr9030460
genre North Atlantic
genre_facet North Atlantic
op_source Processes 9(3)(460)
op_relation info:eu-repo/grantAgreement/EC/Horizon 2020 Framework Programme - Coordination and support action/857586/
https://zenodo.org/communities/cmmi
https://zenodo.org/record/7642344
https://doi.org/10.3390/pr9030460
oai:zenodo.org:7642344
op_rights info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.3390/pr9030460
container_title Processes
container_volume 9
container_issue 3
container_start_page 460
_version_ 1766132899667509248