4.7 Article

Selecting optimum locations for co-located wave and wind energy farms. Part I: The Co-Location Feasibility index

期刊

ENERGY CONVERSION AND MANAGEMENT
卷 122, 期 -, 页码 589-598

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2016.05.079

关键词

Wave energy; Wind energy; Co-located wind-wave farm; North Sea; Power variability; Cross-correlation factor

资金

  1. Atlantic Area Operational Transnational Programme, European Regional and Development Fund (ERDF) [2011-1/151]
  2. FPU of the Spanish Ministry of Education, Culture and Sport [13/03821]

向作者/读者索取更多资源

Marine energy is poised to play a fundamental role in meeting renewable energy and carbon emission targets thanks to the abundant, and still largely untapped, wave and tidal resources. However, it is often considered difficult and uneconomical - as is usually the case of nascent technologies. Combining various renewables, such as wave and offshore wind energy, has emerged as a solution to improve their competitiveness and in the process overcome other challenges that hinder their development. The objective of this paper is to develop a new approach to identifying suitable sites for co-located wave and wind farms based on the assessment of the available resources and technical constraints, and to illustrate its application by means of a case study off the Danish coast - an area of interest for combining wave and wind energy. The method is based on an ad hoc tool, the Co-Location Feasibility (CLF) index, and is based on a joint characterisation of the wave and wind resources, which takes into account not only the available power but also the correlation between both resources and the power variability. The analysis is carried out based on hindcast data and observations from 2005 to 2015, and using third-generation models of winds and waves - WAsP and SWAN, respectively. Upon selection and ranking, it is found that a number of sites in the study region are indeed suited to realising the synergies between wave and offshore wind energy. The approach developed in this work can be applied elsewhere. (C) 2016 Elsevier Ltd. All rights reserved.

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