Geo-spatial multi-criteria evaluation of wave energy exploitation in a semi-enclosed sea

Abstract The present study aims to determine priority areas for installation of wave energy converters (WECs) in a semi-enclosed sea using a multi-criteria, spatial, decision-making analysis based on geographical information systems (GIS). The study also suggests a new methodology for determination of suitable areas for WECs taking into consideration different extreme wave conditions, intra-annual variation of wave conditions, and operational range of wave conditions by the WECs. A case study over a distance of 1140 km along the coast in the southwest Black Sea is presented. In the multi-criteria analysis, areas with environmental, economic, technical and social constraints are excluded. Ocean depth, distance to ports, shore, power line, and sub-station, wave climate, and sea-floor geology are all evaluated for their impact on the system implementation and weighted according to their relevance. Thus, the final suitability index (SI) map is produced and spatial statistical significance of the suitable areas is checked using hotspot analysis. Based on this, Kirklareli coastal area and the area between Igneada Cape and Kiyikoy village are determined as primary priority areas. The sustainability parameters with different weights proposed in this study do not differentiate priority areas but affect the SI scores.

[1]  L. Anselin.  Local Indicators of Spatial Association—LISA , 2010 .

[2]  Laura Castro-Santos,et al.  Planning of the installation of offshore renewable energies: A GIS approach of the Portuguese roadmap , 2019, Renewable Energy.

[3]  A. Akpınar,et al.  Assessment of wave energy resource of the Black Sea based on 15-year numerical hindcast data , 2013 .

[4]  Jon Andreu,et al.  Review of wave energy technologies and the necessary power-equipment , 2013 .

[5]  Burak Aydogan,et al.  Black Sea wave energy atlas from 13 years hindcasted wave data , 2013 .

[6]  A. Akpınar,et al.  Wave energy potential and variability for the south west coasts of the Black Sea: The WEB-based wave energy atlas , 2020 .

[7]  Adem Akpınar,et al.  Wave model predictions in the Black Sea: Sensitivity to wind fields , 2015 .

[8]  Maria Dicorato,et al.  Guidelines for assessment of investment cost for offshore wind generation , 2011 .

[9]  Serwan Mj Baban,et al.  Developing and applying a GIS-assisted approach to locating wind farms in the UK , 2001 .

[10]  Ian R Coghlan,et al.  Multi-criteria evaluation of wave energy projects on the south-east Australian coast , 2016 .

[11]  Daniel Ganea,et al.  A joint evaluation of wave and wind energy resources in the Black Sea based on 20-year hindcast information , 2018 .

[12]  J. Rezaei.  Best-worst multi-criteria decision-making method: Some properties and a linear model , 2016 .

[13]  M. S. García-Cascales,et al.  GIS-based onshore wind farm site selection using Fuzzy Multi-Criteria Decision Making methods. Evaluating the case of Southeastern Spain , 2016 .

[14]  Gregorio Iglesias,et al.  Wave energy potential in Galicia (NW Spain) , 2009 .

[15]  Liliana Rusu,et al.  Assessment of the Wave Energy in the Black Sea Based on a 15-Year Hindcast with Data Assimilation , 2015 .

[16]  George Galanis,et al.  Multi-criteria site selection for offshore renewable energy platforms , 2016 .

[17]  A. Getis.  The Analysis of Spatial Association by Use of Distance Statistics , 2010 .

[18]  Gregorio Iglesias,et al.  The collocation feasibility index – A method for selecting sites for co-located wave and wind farms , 2017 .

[19]  Manish Pal,et al.  Development of the location suitability index for wave energy production by ANN and MCDM techniques , 2016 .

[20]  C. C. Aydin,et al.  Nuclear power plant site selection by Weighted Linear Combination in GIS environment, Edirne, Turkey , 2017 .

[21]  Luís M.C. Gato,et al.  Geo-spatial multi-criteria analysis for wave energy conversion system deployment , 2009 .

[22]  Murat İhsan Kömürcü,et al.  Wave energy potential along the south-east coasts of the Black Sea , 2012 .

[23]  Trevor M. Daniell,et al.  Using GIS to evaluate the impact of exclusion zones on the connection cost of wave energy to the electricity grid , 2007 .

[24]  Eugen Rusu,et al.  Wave energy assessments in the Black Sea , 2009 .

[25]  A. Akpınar,et al.  Wind and wave characteristics in the Black Sea based on the SWAN wave model forced with the CFSR winds , 2016 .

[26]  Eva Loukogeorgaki,et al.  GIS-based multi-criteria decision analysis for site selection of hybrid offshore wind and wave energy systems in Greece , 2017 .

[27]  Anjali Awasthi,et al.  Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia , 2017 .

[28]  Temitope Raphael Ayodele,et al.  A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytic hierarchy process: The case study of Nigeria , 2018, Applied Energy.

[29]  Barbara Zanuttigh,et al.  A methodology for multi-criteria design of multi-use offshore platforms for marine renewable energy harvesting , 2016 .

[30]  Jens Leth Hougaard,et al.  A fuzzy approach to a multiple criteria and Geographical Information System for decision support on suitable locations for biogas plants , 2015 .

[31]  André Martinez,et al.  An Aid Decision Tool for Implementing Wave Energy Devices on the Coast , 2016 .

[32]  A. Akpınar,et al.  Long-term analysis of wave power potential in the Black Sea, based on 31-year SWAN simulations , 2017 .

[33]  A. Etemad-Shahidi,et al.  Inter- and intra-annual variability of potential power production from wave energy converters , 2019, Energy.

[34]  Murat İhsan Kömürcü,et al.  Evaluation of the numerical wave model (SWAN) for wave simulation in the Black Sea , 2012 .

[35]  J. Rezaei.  Best-worst multi-criteria decision-making method , 2015 .

[36]  Luca Cavallaro,et al.  Potential wave energy production by different wave energy converters around Sicily , 2015 .

[37]  B. Divinsky,et al.  Spatiotemporal variability of the Black Sea wave climate in the last 37 years , 2017 .

[38]  J. Kaldellis,et al.  Wave energy exploitation in the Ionian Sea Hellenic coasts: spatial planning of potential wave power stations , 2018, International Journal of Sustainable Energy.

[39]  Suitability mapping for renewable energy potential in the North Sea – results from the BLAST project , 2012 .

[40]  Á. Borja,et al.  A Marine Spatial Planning Approach to Select Suitable Areas for Installing Wave Energy Converters (WECs), on the Basque Continental Shelf (Bay of Biscay) , 2012 .

[41]  Irene Penesis,et al.  Aggregating GIS and MCDM to Optimize Wave Energy Converters Location in Tasmania, Australia , 2015 .

[42]  G. Besio,et al.  Wave power technologies for the Mediterranean offshore: Scaling and performance analysis , 2018, Coastal Engineering.

[43]  António F.O. Falcão,et al.  Wave energy utilization: A review of the technologies , 2010 .