scholarly journals Spatial Complex Model for Wind Farm Site Assessment

2009 ◽  
Vol 3 (1) ◽  
pp. 204-211 ◽  
Author(s):  
Kornel Rozsavolgyi

Our research is on the spatial allocation of possible wind energy usage. We would like to carry this out with a newly developed model (CMPAM = Complex Multifactoral Polygenetic Adaptive Model), which basically is a climateoriented system, but other kind of factors are also considered. With this model those areas and terrains can be located where construction of wind farms would be reasonable. The wind field modeling core of CMPAM is mainly based on sequential Gaussian simulation (sGs) otherwise known as geostatistics. But concepts from atmospheric physics and Geographical Information Systems (GIS) are used as well. For application for Hungary WAsP generated 10 m wind speed data was used as input data. The geocorrection (geometric correction) of this data was performed by us. Using optimized variography and sGs, our results were applied for Hungary in different heights. Simulation results for different heights are summarized furthermore, an exponential regressive function describing the vertical wind profile was also established. From the complex analyses of CMPAM, results derived to the 100 m height are also included and explained in a map in this paper. This produces a basis for certain several possible sites for the utilization of wind energy, under given conditions.

2020 ◽  
pp. 0309524X2092539
Author(s):  
Mohamed Elgabiri ◽  
Diane Palmer ◽  
Hanan Al Buflasa ◽  
Murray Thomson

Current global commitments to reduce the emissions of greenhouse gases encourage national targets for renewable generation. Due to its small land mass, offshore wind could help Bahrain to fulfil its obligations. However, no scoping study has been carried out yet. The methodology presented here addresses this research need. It employs analytical hierarchy process and pairwise comparison methods in a geographical information systems environment. Publicly available land use, infrastructure and transport data are used to exclude areas unsuitable for development due to physical and safety constraints. Meteorological and oceanic opportunities are ranked and then competing uses are analyzed to deliver optimal sites for wind farms. The potential annual wind energy yield is calculated by dividing the sum of optimal areas by a suitable turbine footprint to deliver maximum turbine number. In total, 10 favourable wind farm areas were identified in Bahrain’s territorial waters, representing about 4% of the total maritime area, and capable of supplying 2.68 TWh/year of wind energy or almost 10% of the Kingdom’s annual electricity consumption. Detailed maps of potential sites for offshore wind construction are provided in the article, giving an initial plan for installation in these locations.


Author(s):  
Diane Palmer ◽  
Mohamed Elgabiri ◽  
Hanan Al Buflasa ◽  
Murray Thomson

Current global commitments to reduce emissions of greenhouse gases encourage national targets for renewable generation. Due to its small land mass, offshore wind could help Bahrain to fulfill its obligations. However, no scoping study has yet been carried out. The methodology presented here addresses this research need. It employs Analytical Hierarchy Process and pairwise comparison methods in a Geographical Information Systems environment. Publicly available land use, infrastructure and transport data are used to exclude areas unsuitable for development due to physical and safety constraints. Meteorological and oceanic opportunities are ranked, then competing uses are analyzed to deliver optimal sites for wind farms. The potential annual wind energy yield is calculated by dividing the sum of optimal areas by a suitable turbine footprint, to deliver maximum turbine number. Ten favourable wind farm areas were identified in Bahrain’s territorial waters, representing about 4% of the total maritime area, and capable of supplying 2.68 TWh/yr of wind energy or almost 10% of the Kingdom’s annual electricity consumption. Detailed maps of potential sites for offshore wind construction are provided in the paper, giving an initial plan for installation in these locations.


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.


Author(s):  
Seyyed Pooya Hekmati Athar ◽  
Dorsa Ziaei ◽  
Navid Goudarzi

Abstract Renewable Energy (RE)-based power production often comes with certain challenges in variability and uncertainty of generated electricity. One promising solution to tackle these challenges is developing a network of RE power plants with sites located far enough from each other that experience different weather patterns. Most of the site selection-related literature use Geographical Information Systems to determine the studied site RE suitability. This work converts the site selection into a numerical problem through a novel Networked Renewable Power Plant Site Selection model and solves it by employing optimization techniques. To enhance the accuracy of the results, it compares a set of criteria for individual and network of sites at different regions to determine the exact locations for RE plant developments. The Analytical Hierarchy Process is used for criteria weighing. The state-of-the-art meta-heuristic Bare Bones of Fireworks algorithm offer a simple, fast, yet accurate approach to solve the optimization. The proposed method is applied on North Carolina wind farms for both individual and a network of sites. The results identified the areas with the highest wind capacity potential for individual or a network of wind farms in North Carolina. The identified suitable areas were verified with Amazon Wind Farm US East.


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 3 (2) ◽  
pp. 573-588 ◽  
Author(s):  
Tobias Ahsbahs ◽  
Merete Badger ◽  
Patrick Volker ◽  
Kurt S. Hansen ◽  
Charlotte B. Hasager

Abstract. Rapid growth in the offshore wind energy sector means more offshore wind farms are placed closer to each other and in the lee of large land masses. Synthetic aperture radar (SAR) offers maps of the wind speed offshore with high resolution over large areas. These can be used to detect horizontal wind speed gradients close to shore and wind farm wake effects. SAR observations have become much more available with the free and open-access data from European satellite missions through Copernicus. Examples of applications and tools for using large archives of SAR wind maps to aid offshore site assessment are few. The Anholt wind farm operated by the utility company Ørsted is located in coastal waters and experiences strong spatial variations in the mean wind speed. Wind speeds derived from the Supervisory Control And Data Acquisition (SCADA) system are available at the turbine locations for comparison with winds retrieved from SAR. The correlation is good, both for free-stream and waked conditions. Spatial wind speed variations along the rows of wind turbines derived from SAR wind maps prior to the wind farm construction agree well with information gathered by the SCADA system and a numerical weather prediction model. Wind farm wakes are detected by comparisons between images before and after the wind farm construction. SAR wind maps clearly show wakes for long and constant fetches but the wake effect is less pronounced for short and varying fetches. Our results suggest that SAR wind maps can support offshore wind energy site assessment by introducing observations in the early phases of wind farm projects.


2019 ◽  
Vol 21 (2) ◽  
pp. 745-754
Author(s):  
Otávio Augusto de Oliveira Lima Barra ◽  
Fábio Perdigão Vasconcelos ◽  
Danilo Vieira dos Santos ◽  
Adely Pereira Silveira

O Brasil é um país com uma extensa linha de costa, são cerca de 7.367 km de extensão do seu litoral, com um potencial natural para a geração de energia eólica. O estado do Ceará é um dos maiores produtores de energia eólica para o país, obtendo notoriedade e a necessidade de manutenção dos seus parques eólicos, especialmente se instalados em zonas de costa, onde há uma grande dinâmica natural. O presente trabalho, busca o acompanhamento das dinâmicas morfológicas na praia de Volta do Rio, localizada em Acaraú/CE, que fica a cerca de 238 km de Fortaleza/CE. Os dados coletados em idas à campo, constataram que há um forte processo erosivo atuante na praia de Volta do Rio, o que alerta para a contenção do avanço marinho sob o parque eólico presente no local. A erosão é um fenômeno natural que trabalha na modelação de demasiadas formas terrestres. No litoral, isso não é diferente, por ser um ambiente altamente dinâmico onde há a interação entre continente, atmosfera e oceano, sendo possível encontrar diversos atuantes que podem intensificar os processos erosivos, sejam eles o vento, maré, ou por intervenções humanas, como construções e ocupações indevidas ao longo da linha de costa.Palavras Chave: Volta do Rio; Energia Eólica; Erosão. ABSTRACTBrazil is a country with an extensive coastline, about 7,367 km of coastline, with a natural potential for wind power generation. The state of Ceará is one of the largest producers of wind energy for the country, obtaining notoriety and required maintenance of its wind farms, especially if located in coastal areas, where there is a great natural dynamic. The present work seeks the movement of morphological dynamics in the beach of Volta do Rio, located in Acaraú/CE, which is about 238 km from Fortaleza/CE. The data collected in the field found that there is a strong erosive process on the Beach of Volta do Rio, which warns about the expansion of advanced marine on the wind farm present on site. Erosion is a natural phenomenon that works in the modeling of many hearth forms. On the coast, this is not different, considering a highly dynamic environment in which there is an interaction between continent, atmosphere and ocean, being possible to find many factors that can intensify the erosive processes, such as wind, tide, or human intervention, as constructions and improper occupations along the coast line.Key words: Volta do Rio; Wind Energy; Erosion. RESUMENBrasil es un país con una extensa costa, cerca de 7.367 km de costa, con un potencial natural para la generación de energía eólica. El estado del Ceará es uno de los mayores productores de energía eólica del país, ganando notoriedad y la necesidad de mantener sus parques eólicos, especialmente si está instalado en zonas costeras, donde existe una gran dinámica natural. La presente investigación tiene como objetivo monitorear la dinámica morfológica en la playa de Vuelta del Rio, ubicada en Acaraú / CE, que está a unos 238 km de Fortaleza / CE. Los datos recopilados en los viajes de campo, encontraron que hay un fuerte proceso erosivo en la playa de Vuelta del Rio, que advierte sobre la contención del avance marino bajo el parque eólico presente en el sitio. La erosión es un fenómeno natural que funciona en el modelado de muchas formas terrestres. En la costa, esto no es diferente, ya que es un entorno altamente dinámico donde existe la interacción entre el continente, la atmósfera y el océano, permitiendo encontrar varios actores que pueden intensificar los procesos erosivos, ya sea viento, marea o intervenciones humanas, como edificios y ocupaciones inadecuadas a lo largo de la costa.Palabras clave: Vuelta del Río; Energía Eólica; Erosión.


Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 693
Author(s):  
Anna Dóra Sæþórsdóttir ◽  
Margrét Wendt ◽  
Edita Tverijonaite

The interest in harnessing wind energy keeps increasing globally. Iceland is considering building its first wind farms, but its landscape and nature are not only a resource for renewable energy production; they are also the main attraction for tourists. As wind turbines affect how the landscape is perceived and experienced, it is foreseeable that the construction of wind farms in Iceland will create land use conflicts between the energy sector and the tourism industry. This study sheds light on the impacts of wind farms on nature-based tourism as perceived by the tourism industry. Based on 47 semi-structured interviews with tourism service providers, it revealed that the impacts were perceived as mostly negative, since wind farms decrease the quality of the natural landscape. Furthermore, the study identified that the tourism industry considered the following as key factors for selecting suitable wind farm sites: the visibility of wind turbines, the number of tourists and tourist attractions in the area, the area’s degree of naturalness and the local need for energy. The research highlights the importance of analysing the various stakeholders’ opinions with the aim of mitigating land use conflicts and socioeconomic issues related to wind energy development.


2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.


2021 ◽  
pp. 0309524X2110438
Author(s):  
Carlos Méndez ◽  
Yusuf Bicer

The present study analyzes the wind energy potential of Qatar, by generating a wind atlas and a Wind Power Density map for the entire country based on ERA-5 data with over 41 years of measurements. Moreover, the wind speeds’ frequency and direction are analyzed using wind recurrence, Weibull, and wind rose plots. Furthermore, the best location to install a wind farm is selected. The results indicate that, at 100 m height, the mean wind speed fluctuates between 5.6054 and 6.5257 m/s. Similarly, the Wind Power Density results reflect values between 149.46 and 335.06 W/m2. Furthermore, a wind farm located in the selected location can generate about 59.7437, 90.4414, and 113.5075 GWh/y electricity by employing Gamesa G97/2000, GE Energy 2.75-120, and Senvion 3.4M140 wind turbines, respectively. Also, these wind farms can save approximately 22,110.80, 17,617.63, and 11,637.84 tons of CO2 emissions annually.


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