Modelling assessment of the tidal stream resource in the Ria of Ferrol (NW Spain) using a year-long simulation

Marc Mestres, Pablo Cerralbo, Manel Grifoll, Joan Pau Sierra and Manuel Espino

Renewable Energy, 2019, vol. 131, issue C, 811-817

Abstract: The availability of tidal stream energy in the Ría of Ferrol (NW Spain) has been assessed using a long term hydrodynamic simulation (351 days). A priori, a strait in the central part of the estuary seems a promising site for tidal energy tapping, but the results show that barotropic currents rarely exceed 0.9 m/s during spring tides, with a maximum peak power density of 0.45 kW/m2 estimated at a spring tide mid-ebb. The maximum annual energy density is estimated at 415 kWh/m2, significantly lower than at other nearby estuaries. A comparison of the annual resource estimates shows that differences of up to 35% can be introduced depending on whether a simulation of one tidal cycle, one lunar month, or a full year is used for the calculations. This proves that usual tidal resource estimations, based on a single tidal cycle, can significantly misestimate the tidal energy potential of a site.

Keywords: Ría of Ferrol; Tidal current energy; Tidal resources; Numerical modelling; ROMS (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148118309029
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:131:y:2019:i:c:p:811-817

DOI: 10.1016/j.renene.2018.07.105

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().