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A Markovian approach to power generation capacity assessment of floating wave energy converters


Arzaghi, E and Abaei, MM and Abbassi, R and O'Reilly, M and Garaniya, V and Penesis, I, A Markovian approach to power generation capacity assessment of floating wave energy converters, Renewable Energy, 146 pp. 2736-2743. ISSN 0960-1481 (2020) [Refereed Article]

Copyright Statement

2019 Elsevier Ltd. All rights reserved

DOI: doi:10.1016/j.renene.2019.08.099


The significant cost required for implementation of WEC sites and the uncertainty associated with their performance, due to the randomness of the marine environment, can bring critical challenges to the industry. This paper presents a probabilistic methodology for predicting the long-term power generation of WECs. The developed method can be used by the operators and designers to optimize the performance of WECs by improving the design or in selecting optimum site locations. A Markov Chain model is constructed to estimate the stationary distribution of output power based on the results of hydrodynamic analyses on a point absorber WEC. To illustrate the application of the method, the performance of a point absorber is assessed in three locations in the south of Tasmania by considering their actual longterm sea state data. It is observed that location 3 provides the highest potential for energy extraction with a mean value for absorbed power of approximately 0:54 MW, while the value for locations 1 and 2 is 0:33 MW and 0:43 MW respectively. The model estimated that location 3 has the capacity to satisfy industry requirement with probability 0.72, assuming that the production goal is to generate at least 0:5 MW power.

Item Details

Item Type:Refereed Article
Keywords:renewable energy, power generation, wave energy converter, markov chain, probabilistic modelling
Research Division:Engineering
Research Group:Maritime engineering
Research Field:Ocean engineering
Objective Division:Energy
Objective Group:Renewable energy
Objective Field:Wave energy
UTAS Author:O'Reilly, M (Associate Professor Malgorzata O'Reilly)
UTAS Author:Garaniya, V (Associate Professor Vikram Garaniya)
UTAS Author:Penesis, I (Professor Irene Penesis)
ID Code:134920
Year Published:2020 (online first 2019)
Web of Science® Times Cited:4
Deposited By:NC Maritime Engineering and Hydrodynamics
Deposited On:2019-09-13
Last Modified:2020-03-11
Downloads:1 View Download Statistics

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