11
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Economic Feasibility of Floating Offshore Wind Farms Considering Near Future Wind Resources: Case Study of Iberian Coast and Bay of Biscay

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Wind energy resources are subject to changes in climate, so the use of wind energy density projections in the near future is essential to determine the viability and profitability of wind farms at particular locations. Thus, a step forward in determining the economic assessment of floating offshore wind farms was taken by considering current and near-future wind energy resources in assessing the main parameters that determine the economic viability (net present value, internal rate of return, and levelized cost of energy) of wind farms. This study was carried out along the Atlantic coast from Brest to Cape St. Vincent. Results show that the future reduction in wind energy density (2%–6%) mainly affects the net present value ( NPV) of the farm and has little influence on the levelized cost of energy ( LCOE). This study provides a good estimate of the economic viability of OWFs (Offshore Wind Farms) by taking into account how wind resources can vary due to climate change over the lifetime of the farm.

          Related collections

          Most cited references52

          • Record: found
          • Abstract: not found
          • Article: not found

          EURO-CORDEX: new high-resolution climate change projections for European impact research

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Selecting global climate models for regional climate change studies.

            Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D&A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D&A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D&A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average (MM) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D&A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              An Introduction to Dynamic Meteorology

                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                04 March 2021
                March 2021
                : 18
                : 5
                : 2553
                Affiliations
                [1 ]Departamento de Enxeñaría Naval e Industrial, Escola Politécnica Superior, Universidade da Coruña, Esteiro, 15471 Ferrol, Spain
                [2 ]Environmental Physics Laboratory (EphysLab), Centro de Investigacións Mariñas (CIM)-UVIGO, Universidade de Vigo, Edificio Campus da Auga, 32004 Ourense, Spain; mdecastro@ 123456uvigo.es (M.d.); jorge.costoya.noguerol@ 123456usc.es (X.C.); mggesteira@ 123456uvigo.es (M.G.-G.)
                [3 ]Group of Nonlinear Physics, Department of Particle Physics, CRETUS Institute, University of Santiago de Compostela, 15705 Santiago de Compostela, Spain
                [4 ]Departamento de Química, Escola Politécnica Superior, Universidade da Coruña, Esteiro, 15471 Ferrol, Spain; almudena.filgueira.vizoso@ 123456udc.es
                [5 ]Departamento de Ciencias da Navegación e Enxeñaría Mariña, Escola Politécnica Superior, Universidade da Coruña, Esteiro, 15471 Ferrol, Spain; isabel.lamas.galdo@ 123456udc.es
                [6 ]Centro de Estudos do Ambiente e do Mar (CESAM), Physics Department, University of Aveiro, 3810-193 Aveiro, Portugal; americosribeiro@ 123456ua.pt (A.R.); joao.dias@ 123456ua.pt (J.M.D.)
                Author notes
                Author information
                https://orcid.org/0000-0001-9284-1170
                https://orcid.org/0000-0001-6443-3620
                https://orcid.org/0000-0002-7905-0320
                https://orcid.org/0000-0001-5824-1542
                https://orcid.org/0000-0002-7613-6241
                Article
                ijerph-18-02553
                10.3390/ijerph18052553
                7967524
                b92022a7-989f-49b0-a07f-9d12e0b0c498
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 29 January 2021
                : 25 February 2021
                Categories
                Article

                Public health
                floating offshore wind farms,wind power density,cordex future projections,lcoe,npv,irr
                Public health
                floating offshore wind farms, wind power density, cordex future projections, lcoe, npv, irr

                Comments

                Comment on this article