Site Selection of Offshore Solar Farm Deployment in the Aegean Sea, Greece
Offshore solar energy presents a new opportunity for low-carbon energy transition. In this research, we identify and rank suitable Offshore Solar Farm (OSF) sites in the Aegean Sea, Greece, considering various constraints and assessment criteria. The methodology includes two distinct phases. In the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/10/2/224 |
| _version_ | 1797478994163007488 |
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| author | Dimitra G. Vagiona George Tzekakis Eva Loukogeorgaki Nikolaos Karanikolas |
| author_facet | Dimitra G. Vagiona George Tzekakis Eva Loukogeorgaki Nikolaos Karanikolas |
| author_sort | Dimitra G. Vagiona |
| collection | DOAJ |
| description | Offshore solar energy presents a new opportunity for low-carbon energy transition. In this research, we identify and rank suitable Offshore Solar Farm (OSF) sites in the Aegean Sea, Greece, considering various constraints and assessment criteria. The methodology includes two distinct phases. In the first phase, Geographic Information Systems (GIS) are used to spatially depict both incompatible and compatible marine areas for OSF deployment, while in the second phase, two models based on different combinations of multi-criteria decision-making methods are deployed to hierarchically rank the eligible areas for OSF deployment. The first model (Objective Model—OM) attributes weights to assessment criteria using an entropy-based weight method, while the second model (Subjective Model—SM) utilizes the pairwise comparison of the Analytical Hierarchy Process (AHP) method. Both models use TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to prioritize the suitable OSF sites. The results indicate the existence of nine suitable OSF marine areas in the Greek marine environment (total surface area of 17.25 km<sup>2</sup>) and a different ranking of these sites depending upon the deployed model (OM or SM). The present approach provides useful guidelines for OSF site selection in Greece as well as in other countries. |
| first_indexed | 2024-03-09T21:39:32Z |
| format | Article |
| id | doaj.art-c141fd02c8cc4d28bd13cdd2d8f974c4 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-09T21:39:32Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-c141fd02c8cc4d28bd13cdd2d8f974c42023-11-23T20:35:31ZengMDPI AGJournal of Marine Science and Engineering2077-13122022-02-0110222410.3390/jmse10020224Site Selection of Offshore Solar Farm Deployment in the Aegean Sea, GreeceDimitra G. Vagiona0George Tzekakis1Eva Loukogeorgaki2Nikolaos Karanikolas3Department of Spatial Planning and Development, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceDepartment of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceDepartment of Civil Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceDepartment of Spatial Planning and Development, Aristotle University of Thessaloniki, 54124 Thessaloniki, GreeceOffshore solar energy presents a new opportunity for low-carbon energy transition. In this research, we identify and rank suitable Offshore Solar Farm (OSF) sites in the Aegean Sea, Greece, considering various constraints and assessment criteria. The methodology includes two distinct phases. In the first phase, Geographic Information Systems (GIS) are used to spatially depict both incompatible and compatible marine areas for OSF deployment, while in the second phase, two models based on different combinations of multi-criteria decision-making methods are deployed to hierarchically rank the eligible areas for OSF deployment. The first model (Objective Model—OM) attributes weights to assessment criteria using an entropy-based weight method, while the second model (Subjective Model—SM) utilizes the pairwise comparison of the Analytical Hierarchy Process (AHP) method. Both models use TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to prioritize the suitable OSF sites. The results indicate the existence of nine suitable OSF marine areas in the Greek marine environment (total surface area of 17.25 km<sup>2</sup>) and a different ranking of these sites depending upon the deployed model (OM or SM). The present approach provides useful guidelines for OSF site selection in Greece as well as in other countries.https://www.mdpi.com/2077-1312/10/2/224solar farm sitingassessment criteriaentropy weight methodAHPTOPSIS |
| spellingShingle | Dimitra G. Vagiona George Tzekakis Eva Loukogeorgaki Nikolaos Karanikolas Site Selection of Offshore Solar Farm Deployment in the Aegean Sea, Greece Journal of Marine Science and Engineering solar farm siting assessment criteria entropy weight method AHP TOPSIS |
| title | Site Selection of Offshore Solar Farm Deployment in the Aegean Sea, Greece |
| title_full | Site Selection of Offshore Solar Farm Deployment in the Aegean Sea, Greece |
| title_fullStr | Site Selection of Offshore Solar Farm Deployment in the Aegean Sea, Greece |
| title_full_unstemmed | Site Selection of Offshore Solar Farm Deployment in the Aegean Sea, Greece |
| title_short | Site Selection of Offshore Solar Farm Deployment in the Aegean Sea, Greece |
| title_sort | site selection of offshore solar farm deployment in the aegean sea greece |
| topic | solar farm siting assessment criteria entropy weight method AHP TOPSIS |
| url | https://www.mdpi.com/2077-1312/10/2/224 |
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