Analytical wake model of tidal current turbine. (1st January 2015)
- Record Type:
- Journal Article
- Title:
- Analytical wake model of tidal current turbine. (1st January 2015)
- Main Title:
- Analytical wake model of tidal current turbine
- Authors:
- Lam, Wei-Haur
Chen, Long
Hashim, Roslan - Abstract:
- Abstract: Prediction of the wake structure is important to understand the lee flow of a tidal current turbine. The proposed analytical wake model consists of several equations derived from the theoretical works of a ship propeller jet. Axial momentum theory was used to predict the minimum velocity at the immediate plane of the lee wake and followed by the proposed recovery equation to determine the minimum velocity at various lateral sections along the rotation axis. Gaussian probability distribution was used to predict the velocity distribution of lateral sections in a wake. Entire wake is able to be illustrated through the calculation of the efflux equation, recovery equation and lateral distribution equations. Authors' previous works proposed a simplified one-dipped velocity profile and this works were being extended to predict the two-dipped velocity profile with the consideration of hub effects. The wake model is validated by using the well-accepted experimental measurements and the goodness-of-fit test. The results demonstrated that the wake model is able to predict the wake profile under various ambient turbulence conditions of TI (turbulence intensity) = 3%, 5%, 8% and 15%. Highlights: Wake model is proposed to predict the velocity distribution of tidal turbine. Model is derived from concept of ship propeller and axial momentum theory. Two-dipped profile with schematic diagram of wake is proposed. R -square and MSE (mean square error) are used to ensure correlationAbstract: Prediction of the wake structure is important to understand the lee flow of a tidal current turbine. The proposed analytical wake model consists of several equations derived from the theoretical works of a ship propeller jet. Axial momentum theory was used to predict the minimum velocity at the immediate plane of the lee wake and followed by the proposed recovery equation to determine the minimum velocity at various lateral sections along the rotation axis. Gaussian probability distribution was used to predict the velocity distribution of lateral sections in a wake. Entire wake is able to be illustrated through the calculation of the efflux equation, recovery equation and lateral distribution equations. Authors' previous works proposed a simplified one-dipped velocity profile and this works were being extended to predict the two-dipped velocity profile with the consideration of hub effects. The wake model is validated by using the well-accepted experimental measurements and the goodness-of-fit test. The results demonstrated that the wake model is able to predict the wake profile under various ambient turbulence conditions of TI (turbulence intensity) = 3%, 5%, 8% and 15%. Highlights: Wake model is proposed to predict the velocity distribution of tidal turbine. Model is derived from concept of ship propeller and axial momentum theory. Two-dipped profile with schematic diagram of wake is proposed. R -square and MSE (mean square error) are used to ensure correlation of equations. … (more)
- Is Part Of:
- Energy. Volume 79:(2015)
- Journal:
- Energy
- Issue:
- Volume 79:(2015)
- Issue Display:
- Volume 79, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 79
- Issue:
- 2015
- Issue Sort Value:
- 2015-0079-2015-0000
- Page Start:
- 512
- Page End:
- 521
- Publication Date:
- 2015-01-01
- Subjects:
- Tidal-current turbine -- Efflux velocity -- Wake
Power resources -- Periodicals
Power (Mechanics) -- Periodicals
Energy consumption -- Periodicals
333.7905 - Journal URLs:
- http://www.elsevier.com/journals ↗
- DOI:
- 10.1016/j.energy.2014.11.047 ↗
- Languages:
- English
- ISSNs:
- 0360-5442
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3747.445000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7250.xml