Cost-Effective Optimization of an Array of Wave Energy Converters in Front of a Vertical Seawall

Senthil Kumar Natarajan and Il Hyoung Cho ()
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Senthil Kumar Natarajan: Department of Ocean System Engineering, Jeju National University, Jeju 690-756, Republic of Korea
Il Hyoung Cho: Department of Ocean System Engineering, Jeju National University, Jeju 690-756, Republic of Korea

Energies, 2023, vol. 17, issue 1, 1-21

Abstract: The present paper focuses on investigating the cost-effective configuration of an array of wave energy converters (WECs) composed of vertical cylinders situated in front of a vertical seawall in irregular waves. First, the hydrodynamic calculations are performed using a WAMIT commercial code based on linear potential theory, where the influence of the vertical wall is incorporated using the method of image. The viscous damping experienced by the oscillating cylinder is considered through CFD simulations of a free decay test. A variety of parameters, including WEC diameter, number of WECs, and the spacing between them, are considered to determine an economically efficient WEC configuration. The design of the WEC configuration is aided by a cost indicator, defined as the ratio of the total submerged volume of the WEC to overall power capture. The cost-effective configuration of WECs is achieved when WECs are positioned in front of a vertical wall and the distance between them is kept short. It can be explained that the trapped waves formed between adjacent WECs as well as the standing waves in front of a seawall significantly intensify wave fields around WECs and consequently amplify the heave motion of each WEC. A cost-effective design strategy of WEC deployment enhances the wave energy greatly and, consequently, contributes to constructing the wave energy farm.

Keywords: wave energy converter; cost-effective analysis; method of image; linear potential theory; vertical seawall (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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