scholarly journals Strategic Planning of Offshore Wind Farms in Greece

2020 ◽  
Vol 12 (3) ◽  
pp. 905 ◽  
Author(s):  
Sofia Spyridonidou ◽  
Dimitra G. Vagiona ◽  
Eva Loukogeorgaki

In the present article, a new methodological framework for the efficient and sustainable exploitation of offshore wind potential was developed. The proposed integrated strategic plan was implemented for the first time at national spatial planning scale in Greece. The methodological approach is performed through geographical information systems (GIS) and Microsoft Project Server Software and includes five distinct stages: (i) definition of vision/mission, (ii) identification of appropriate areas for offshore wind farms’ (OWFs) siting, (iii) determination of the OWFs’ layout, (iv) calculation of the OWFs’ (projects) total investment cost and, finally, (v) portfolio analysis. The final outcome of the proposed strategic planning is the prioritization of the proposed sixteen offshore wind projects based on their strategic value, as well as the estimation of the overall investment cost of the entire portfolio. High economic, socio-political and environmental benefits could be achieved through the implementation of only 60% of the total investment capital of the proposed strategic plan.

Author(s):  
Fatih Karipoğlu

In Turkey, current energy generations are not sufficient for the existing energy needs and besides, energy demand is expected to increase by 4-6% percent annually until 2023. Therefore, the government aims to increase the ratio of renewable energy sources in total installed capacity to 30 percent by 2023. Turkey has three quarter seas around itself. So, Turkey has a high level offshore wind potential for energy generations. But there are not any offshore wind farms in Turkey seas. In this study, we aimed at assessing the viability of establishing offshore wind farms of Marmara Sea and to identify favorable sites for such farms using Geographical Information System (GIS) procedures and algorithms. GIS layers were created and a weighted overlay GIS model based on the above mentioned criteria was built to identify suitable sites for hosting a new offshore wind farm. Furthermore, EMODnet (the European Marine Observation and Data Network) and GWA (Global Wind Atlas) were employed for data acquisition to unlock fragmented and hidden marine data resources and to facilitate investment in sustainable coastal and offshore activities. Received technical, social and environmental data from different sources were processed in the GIS and we created the GIS-based model. Results showed that most of Marmara Sea offshore areas were unsuitable. There are only two suitable areas. It is apparent that the growth of offshore wind farms in Turkey will increase provided that the supporting mechanism and the necessary legislation are ensured.  


2011 ◽  
Vol 383-390 ◽  
pp. 3610-3616 ◽  
Author(s):  
Xin Yin Zhang ◽  
Zai Jun Wu ◽  
Si Peng Hao ◽  
Ke Xu

Offshore wind farm is developed in the ascendant currently. The reliable operation, power loss, investment cost and performance of wind farms were effect by the integration solutions of electrical interconnection system directly. Several new integration configurations based on VSC-HVDC were comparative analyzed. For the new HVDC topology applied the wind farm internal DC bus, the Variable Speed DC (VSDC) system that is suitable for those topologies was proposed. The structure of VSDC was discussed and maximum wind power tracking was simulated on the minimal system. It is clear that new integration configurations based on VSC-HVDC has good prospects.


Web Ecology ◽  
2016 ◽  
Vol 16 (1) ◽  
pp. 73-80 ◽  
Author(s):  
Takvor Soukissian ◽  
Sofia Reizopoulou ◽  
Paraskevi Drakopoulou ◽  
Panagiotis Axaopoulos ◽  
Flora Karathanasi ◽  
...  

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.


2013 ◽  
Vol 14 (2) ◽  
pp. 235-243 ◽  

Wind energy offers significant potential for greenhouse gas emissions reductions. Most applications have been developed onshore but the planning and siting conflicts with other land uses have created considerable interest and motivated research to offshore wind energy establishments. In this paper, a systematic methodology in order to investigate the most efficient areas of offshore wind farms’ siting in Greece is performed, integrating multi-criteria decision making (MCDM) methods and Geographic Information Systems (GIS) tools. In the first level of analysis, all coastal areas that don’t fulfill a certain set of criteria (wind velocity, protected areas, water depth) are identified with the use of Geographical Information Systems (GIS) and excluded from further analysis. The Analytical Hierarchy Process is performed in the evaluation phase and pairwise comparisons provide the most appropriate sites to locate offshore wind farms. Information concerning evaluation criteria (average wind velocity, distance to protected areas, distance to ship routes, distance to the shore and distance of possible connection to the existing electricity network) is retrieved through GIS, eliminating the subjectivity in judgments. The whole methodology contributes to the portrait of the geographic analysis and stands as the last image of the space characteristics suitable for offshore wind farms.


Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 146
Author(s):  
Joongjin Shin ◽  
Seokheum Baek ◽  
Youngwoo Rhee

This paper examines the solution to the problem of turbine arrangement in offshore wind farms. The two main objectives of offshore wind farm planning are to minimize wake loss and maximize annual energy production (AEP). There is more wind with less turbulence offshore compared with an onshore case, which drives the development of the offshore wind farm worldwide. South Korea’s offshore wind farms, which are deep in water and cannot be installed far off the coast, are affected by land complex terrain. Thus, domestic offshore wind farms should consider the separation distance from the coastline as a major variable depending on the topography and marine environmental characteristics. As a case study, a 60 MW offshore wind farm was optimized for the coast of the Busan Metropolitan City. For the analysis of wind conditions in the candidate site, wind conditions data from the meteorological tower and Ganjeolgot AWS at Gori offshore were used from 2001 to 2018. The optimization procedure is performed by evolutionary algorithm (EA) and particle swarm optimization (PSO) algorithm with the purpose of maximizing the AEP while minimizing the total wake loss. The optimization procedure can be applied to the optimized placement of WTs within a wind farm and can be extended for a variety of wind conditions and wind farm capacity. The results of the optimization were predicted to be 172,437 MWh/year under the Gori offshore wind potential, turbine layout optimization, and an annual utilization rate of 26.5%. This could convert 4.6% of electricity consumption in the Busan Metropolitan City region in 2019 in offshore wind farms.


2021 ◽  
Vol 9 (7) ◽  
pp. 758
Author(s):  
Gerard Lorenz D. Maandal ◽  
Mili-Ann M. Tamayao-Kieke ◽  
Louis Angelo M. Danao

The technical and economic assessments for emerging renewable energy technologies, specifically offshore wind energy, is critical for their improvement and deployment. These assessments serve as one of the main bases for the construction of offshore wind farms, which would be beneficial to the countries gearing toward a sustainable future such as the Philippines. This study presents the technical and economic viability of offshore wind farms in the Philippines. The analysis was divided into four phases, namely, application of exclusion criteria, technical analysis, economic assessment, and sensitivity analysis. Arc GIS 10.5 was used to spatially visualize the results of the study. Exclusion criteria were applied to narrow down the potential siting for offshore wind farms, namely, active submerged cables, local ferry routes, marine protected areas, reefs, oil and gas extraction areas, bathymetry, distance to grid, typhoons, and earthquakes. In the technical analysis, the turbines SWT-3.6-120 and 6.2 M126 Senvion were considered. The offshore wind speed data were extrapolated from 80 m to 90 m and 95 m using power law. The wind power density, wind power, and annual energy production were calculated from the extrapolated wind speed. Areas in the Philippines with a capacity factor greater than 30% and performance greater than 10% were considered technically viable. The economic assessment considered the historical data of constructed offshore wind farms from 2008 to 2018. Multiple linear regression was done to model the cost associated with the construction of offshore wind farms, namely, turbine, foundation, electrical, and operation and maintenance costs (i.e., investment cost). Finally, the levelized cost of electricity and break-even selling price were calculated to check the economic viability of the offshore wind farms. Sensitivity analysis was done to investigate how LCOE and price of electricity are sensitive to the discount rate, capacity factor, investment cost, useful life, mean wind speed, and shape parameter. Upon application of exclusion criteria, several sites were determined to be viable with the North of Cagayan having the highest capacity factor. The calculated capacity factor ranges from ~42% to ~50% for SWT-3.6-120 and ~38.56% to ~48% for 6.2M126 turbines. The final regression model with investment cost as the dependent variable included the minimum sea depth and the plant capacity as the predictor variables. The regression model had an adjusted R2 of 90.43%. The regression model was validated with existing offshore wind farms with a mean absolute percentage error of 11.33%. The LCOE calculated for a 25.0372 km2 offshore area ranges from USD 157.66/MWh and USD 154.1/MWh. The breakeven electricity price for an offshore wind farm in the Philippines ranges from PHP 8.028/kWh to PHP 8.306/kWh.


Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 865
Author(s):  
Hugo Díaz ◽  
Carlos Guedes Soares

The study presents a methodology for floating wind farms site selection with a Canary Islands case study. The frame combines geographical information systems (GIS) and multiple criteria decision methods (MCDMs). First, the problematic areas for the installation of the turbines are identified through a GIS database application. This tool generates thematic layers representing exclusion criteria. Then, at the second stage of the study, available maritime locations are analyzed and ranked using the analytical hierarchy process (AHP), based on technical, economic, and environmental aspects. AHP’s technique guarantee the elimination of the judgment’s subjectivity. The study also compared the solutions of the AHP technique with other methods, such as Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), ELimination Et Choix Traduisant la Realité (ELECTRE III), Technique for Order Preferences by Similarity to Ideal Solution (TOPSIS) and Weighted Sum Algorithm (WSA(). The main result of this study is the creation of a realistic and objective overview of floating offshore wind farm site selection and the contribution to minimize the environmental impacts and to reduce the social conflicts between stakeholders.


2018 ◽  
Vol 596 ◽  
pp. 213-232 ◽  
Author(s):  
MJ Brandt ◽  
AC Dragon ◽  
A Diederichs ◽  
MA Bellmann ◽  
V Wahl ◽  
...  

2009 ◽  
Vol 1 (07) ◽  
pp. 809-813
Author(s):  
M. Martínez ◽  
A. Pulido ◽  
J. Romero ◽  
N. Angulo ◽  
F. Díaz ◽  
...  

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