An Offshore Wind Energy Geographic Information System (OWE-GIS) for assessment of the UK's offshore wind energy potential

Cavazzi, S.; Dutton, A.G.

doi:10.1016/j.renene.2015.09.021

Cited by 142 publications

(72 citation statements)

References 11 publications

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“…Data obtained from Ref. [21] was used to compare factors and to identify the different elements of costs of OWF. It should be noted that the cost values were estimated as an average from the cost of offshore wind projects in the UK spanning the period 2010 to 2015 [21].…”

Section: Resultsmentioning

confidence: 99%

“…[21] was used to compare factors and to identify the different elements of costs of OWF. It should be noted that the cost values were estimated as an average from the cost of offshore wind projects in the UK spanning the period 2010 to 2015 [21]. Table 4 gives the cost of the various components for a wind farm including turbine foundation, cabling cost and their percentage of the total cost [21].…”

Section: Resultsmentioning

confidence: 99%

“…However, using only factors without considering constraints is likely to affect the accuracy of results. Further research to produce a suitability map for offshore wind areas around the UK was also undertaken but was biased towards cost modelling [21]. The analysis was mainly based on data obtained from the UK Crown Estate using specific Crown Estate restrictions, weights and scores.…”

Section: Relevant Literaturementioning

confidence: 99%

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Multi criteria decision analysis for offshore wind energy potential in Egypt

2018

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a b s t r a c tOffshore wind energy is highlighted as one of the most important resource to exploit due to greater wind intensity and minimal visual impacts compared with onshore wind. Currently there is a lack of accurate assessment of offshore wind energy potential at global sites. A new methodology is proposed addressing this gap which has global applicability for offshore wind energy exploitation. It is based on Analytical Hierarchy Process and pairwise comparison methods linked to site spatial assessment in a geographical information system. The method is applied to Egypt, which currently plan to scale renewable energy capacity from 1 GW to 7.5 GW by 2020, likely to be through offshore wind. We introduce the applicability of the spatial analysis, based on multi-criteria decision analysis providing accurate estimates of the offshore wind from suitable locations in Egypt. Three high wind suitable areas around the Red Sea were identified with minimum restrictions that can produce around 33 GW of wind power. Suitability maps are also included in the paper providing a blueprint for the development of wind farms in these sites. The developed methodology is generalised and is applicable globally to produce offshore wind suitability map for appropriate offshore wind locations.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Relevant Literaturementioning

confidence: 99%

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Multi criteria decision analysis for offshore wind energy potential in Egypt

2018

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“…In addition, due to smaller farm area of OWFs in comparison with its on-shore counterpart (identical power rating), the power loss of its electrical interconnection system is relatively lower (mostly, it is just about 1%). Note that, according to the offshore wind characteristic, the annual capacity factors of installed OWFs are generally in the range of 0.33-0.54 [25,26]. Hence, in order to minimize the CAPEX for investors, the power loss is defined as a penalty function with its admissible value (lower than 2%) [13].…”

Section: Objective Functionsmentioning

confidence: 99%

Simultaneous optimization of electrical interconnection configuration and cable sizing in offshore wind farms

Sedighi

Moradzadeh

Kükrer

et al. 2018

J. Mod. Power Syst. Clean Energy

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Offshore wind farm (OWF) is the largest renewable energy resource. The electrical interconnection cost of OWFs is a considerable fraction of the overall design cost of the farm. In order to minimize the investment and operational costs, this paper proposes an optimization formulation to find the optimal electrical interconnection configuration of wind turbines (WTs), and the optimal cable sizing simultaneously. This simultaneous minimization of total trenching length and cable dimensions creates a complex optimization problem that is solved by the harmony search (HS) algorithm. In this paper, two distinct methods of full and partial optimal cable sizing are considered to comprehensively assess the optimal interconnection layout of OWFs. Furthermore, various shipping and burying costs as well as various WTs power ratings are considered in order to investigate their impact on the optimal electrical interconnection system. The optimal electrical interconnection design obtained by the HS algorithm corresponds to a lower cost that together with the technological developments can help policy makers increase the use of offshore wind energy as a feasible unlimited renewable resource in their energy production portfolios.

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“…During recent years, due to its flexibility and available features, this spatial analysis tool has been extensively used by renewable energy developers in the context of multi-criteria decision analysis for OWF site selection procedure (see, for example, Atici et al, 2015). Moreover, there are recent studies evaluating OWE development through GIS tools, but only at a national level; for instance, there are assessment studies for Denmark (Möller et al, 2012), Greece (Vagiona and Karanikolas, 2012), Portugal (Costa et al, 2006), and the UK (Cavazzi and Dutton, 2016). Although there are numerous studies proposing multicriteria approaches for wind farm siting (mainly onshore), an integrated approach combining the aforementioned viewpoints with evaluation procedures is still missing for offshore wind applications with reference to an extended spatial scale, such as a large basin.…”

Section: Introductionmentioning

confidence: 99%

Greening offshore wind with the Smart Wind Chart evaluation tool

et al. 2016

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Abstract. The development of offshore wind farms (OWFs) and the establishment of marine protected areas (MPAs) comprise two main elements for the production of clean energy, and the simultaneous maintenance and protection of biodiversity in the Mediterranean and Black seas. Successful, efficient, and sustainable coupling of these two aspects presumes that the criteria for selecting suitable locations for the deployment of OWFs should not only include technical-engineering terms (e.g. high wind energy efficiency, bottom suitability, inland infrastructures) but also ecological-environmental considerations (e.g. the least possible impact on biodiversity, ecosystem functioning) and socio-economic aspects (e.g. effects on coastal and marine activities, development of marine spatial planning). In the context of the FP7 CoCoNet project, the integration between OWFs and MPAs is based on four main steps: (i) the identification of existing (networks of) MPAs focusing on the biodiversity distribution patterns and current legislation, (ii) the coupling of offshore wind potential within networks of MPAs, (iii) the evaluation of the knowledge gained up to date and the theoretical approaches at the two pilot sites of the Mediterranean and Black sea basins, and (iv) the development of the "Smart Wind Chart", a convenient and rational tool addressed to scientists and policy makers for the evaluation of maritime policy management schemes. The latter step comprises the core of this work.

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An Offshore Wind Energy Geographic Information System (OWE-GIS) for assessment of the UK's offshore wind energy potential

Cited by 142 publications

References 11 publications

Multi criteria decision analysis for offshore wind energy potential in Egypt

Multi criteria decision analysis for offshore wind energy potential in Egypt

Simultaneous optimization of electrical interconnection configuration and cable sizing in offshore wind farms

Greening offshore wind with the Smart Wind Chart evaluation tool

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