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Rüzgar enerjisinin değerlendirilmesi, herhangi bir yerde bulunan potansiyel rüzgar enerjisi hakkında uzmanları bilgilendiren entegre analizlerin bir biçimidir. Bu tür değerlendirmenin başlangıç noktası, belirli bir yerde yaygın olarak meydana gelen rüzgar modellerini anlamaktır. Bunu, rüzgar verileri toplama ve toplanan verileri analiz etme izler. Bu makale, birinci ve ikinci bölgelerin kapsamlı bir çalışmasıdır. Bu nedenle, ortalama rüzgar hızı, yön verisi, kısa vadeli varyasyonlar (veya rüzgarlar), yıllık, mevsimsel ve hatta günlük değişiklikler / varyasyonlar ve yüksekliğe bağlı varyasyonlar gibi birkaç parametre dikkate alınmalıdır. Bahsedilen tüm parametreler sahaya özgü olduğundan, uzun bir süre boyunca yerinde ölçümlerle doğru bir şekilde belirlenebilir. Bu çalışma, rüzgar değerlendirmesi ve potansiyel rüzgar enerjisi üzerine odaklandığından Gharyan şehri bir konum olarak seçildi ve alt konumları Gharyan 1, 2, 3 ve 4 olarak adlandırıldı. İlk olarak, rüzgar enerjisi kaynağı ile ilgili konumun yakınında bulunan meteoroloji istasyonlarından alınan veriler arka planda toplandı. Genellikle, her bir konum için 3 saatlik uzun vadeli rüzgar verileri kullanılır ve daha sonra, göbek yüksekliğindeki gerçek rüzgar hızını bulmak için rüzgar verilerinin yeniden hesaplanması yapılır. Önemli hesaplama parametreleri arasında, önerilen her bir saha için hesaplanması gereken Weibull dağılımı, ortalama rüzgar hızı, yıllık kapasite faktörü ve yıllık enerji faktörü yer alır. Yıllık kapasite ve enerji faktörlerinin hesaplanması, genellikle Vestas (V60, 850kW) olarak adlandırılan rüzgar türbinini seçmek için gereklidir. Bu makale, Libya'daki bazı tesislerin, özellikle yıllık enerji, kapasite faktörü ve kabul edilebilir enerji üretim kapasitesinin kaydedildiği Gharyan'da bulunan dört bölgede yeterli rüzgar enerjisine sahip olduğunu açıkça göstermektedir., Assessing the potential of wind energy involves an integrated analysis approach, the conclusions of which inform the experts of the field about the possibilities of harnessing wind energy on a certain location. This type of analysis is made of multiple steps, starting from observing and understanding commonly occurring wind patterns at the designated site, followed by collection of data and finally analysis. The current paper is an extended study on the first two steps where several parameters such as wind’s average speed and its direction, as well as various changes such as short-term ones (or gusts), yearly, seasonal, and even daily changes, and height-related variations were collected. Since the above-mentioned parameters are site-specific, they can be accurately determined through on-site measurements during extended time periods. The site for this study is the city of Gharyan in Libya which was divided into four sub-locations. Data were gathered from meteorological stations located in the vicinity of the designated area in three-hours periods, and they were then used to recalculate wind’s real speed and height at a specific hub. Among the important calculation parameters were Weibull's distribution, average wind speed, annual capacity factor, and the annual energy factor, all of them required for each proposed site. The calculations of the annual capacity and energy factors are necessary for choosing the appropriate wind turbine, generally named Vestas (V60, 850kW). The current study clearly shows that some sites, in particular four locations in Ghayran where feasible annual energy, capacity factor, and acceptable power generation capacity were recorded have wind energy for civilian purposes.

Global installed wind power capacity has risen nearly 4.3 times in the last decade, from 120.7 GW in 2008 to more than 591 GW in 2018. On the other hand, installed wind power capacity in Turkey was reported as 7.37 GW in 2018, and it is scheduled to reach 12 GW in 2023. The aim of this paper is to assess the recent growth of wind power generation in Turkey in terms of power generation technologies, wind power potential, techno-economic feasibility, and visibility of onshore wind turbines. In this respect, several metrics such as cumulative installed wind power capacity (MW), total number of turbines, total swept area of turbines (km2), total hub height of turbines (km), number of the turbine per turbine power capacity (1/GW), swept area per turbine power capacity (m2/MW) and hub height per turbine power capacity (m/MW) are developed to assess wind power generation regionally between the years of 2010 and 2018. Results show that wind power generation capacity is on the rise in Turkey. But this growth also implies an increase in the number and size of turbines. Eventually, turbines with higher hubs and rotor diameters have become more abundant and visible in landscapes.

With the rapid increase of penetration of the wind-based resources for generating electricity, the assessment of wind potential is becoming a vital aspect more than ever. For tapping the potential for a particular wind site, in addition to precisely assessing the wind potential, the accurate forecasting of the wind speed and wind power for the different time horizons is also an important aspect. In this chapter, we discuss various aspects associated with wind power assessment. Additionally, we discuss the scale of the analysis, and the methods that have been utilized. A comprehensive view is conducted for that purpose.

Wind power plant sizes, hub heights, and turbine ratings have increased since 2008 to optimize the cost and performance of wind power; however, the limits of these economies of scale remain unclear. Here, we explore how the costs incurred to install turbines at a wind power plant—the balance-of-system (BOS) costs—scale with turbine rating, hub height, and plant size. We also investigate how these changes in BOS costs influence the levelized cost of energy (LCOE). We show that increasing the plant size from 150 to 400 MW could reduce the BOS costs by 21%. We also show that if the foundation costs decreased by 50%, building a wind power plant with 5-MW turbines (having rotor diameters of 166 m and hub heights of 120 m) could decrease the LCOE by 5%. These results could help inform future BOS cost-reduction opportunities and thereby reduce future capital costs for land-based wind power.

This paper aims to optimize the power system design of a vineyard house in Pazarcık, Kahramanmaras. In this process, the electrical energy demand is met by the hybrid Photovoltaic-Wind-Diesel-Battery system because the vineyard house is remote from the electric network. The vineyard house is located in Karagol, southern of Pazarcık. During the summer in Karagol, many people stay in and visit the vineyard houses. However, the vineyard houses are generally unoccupied in winter. Therefore, an economical energy source is required in this process without compromising life quality. Capital costs are high and the running costs are low for stand-alone renewable sources. On the other hand, it is the opposite for stand-alone diesel power generators. This study is designed to take these circumstances into consideration. The optimal design is investigated for a hybrid system of renewable energy sources and a diesel power generator. The Homer software is used during this process. The realized design is evaluated in terms of its technical and environmental aspects. As a result of the study, 6 kW photovoltaic panels, a 1 kW wind turbine, a 1 kW diesel generator, a 2 kW converter, and an optimally sized 8-unit battery system are used to meet the electricity needs of the vineyard house. The renewable energy factor is 99.8% for a vineyard house. This value is an acceptable rate for a net zero energy house. This study shows that the hybrid system meets the house's electric energy demands and has a positive impact on the environment by reducing greenhouse gas emissions.

On December 21, 2020, The State Council Information Office issued a white paper titled “China’s Energy Development in the New Era,” in which the installed capacity of hydropower, wind power, photovoltaic power and biomass power generation in China ranked first in the world [1]. Solar photovoltaic power generation is the most important development direction of clean energy in the world. It is an important energy strategy to combine it with the field of construction in China. This paper mainly introduces the characteristics and problems of the key technologies of solar photovoltaic building integration, and explores its future development direction and ways, in order to constantly promote the industrialization of new energy technology in China.

Diploma III Electrical Technology Study Program is a institutional vocational education institutional in Department of Electrical Engineering and Informatics that aims to produce graduate who are ready to work in operation and maintenance of power system. Since phenomena of scarcity of fossil fuels, study program meet the 2 major problems, namely the limitations of electrical energy for practical lab work and increased job skills on the electrical energy conversion of electrical energy from renewable energy. The purpose of this research is to optimalize capacity of solar and wind energy contained in the environment of the laboratory on the microgrid configuration, namely PV-Wind turbine-Battery. Software HOMER is used to simulate microgrid configuration with AC-DC load, AC load, and DC load. The results show indicate that microgrid PV-Wind turbine-Battery is more economically to meet the need AC-DC load than the others.

The design, construction, and development of micro-turbines using 3D printing has been an important advance in the wind energy field to explore the possibility of offering viable alternative for the electric power generation, reducing the pollution caused by fossil fuels. In this work, a five blade vertical axis wind turbine prototype was tested. The components were designed using CAD and the turbine was manufactured by additive technology in a 3D printer. The material employed for 3D printing was commercial polylactic acid. The mechanical properties of the material used were obtained by tensile tests under the ASTM D-638 standard. On the other hand, a static structural simulation was performed by finite element method. Maximum tensile stress safety factor, maximum principal stresses, and fatigue analyses of the main turbine components were computed. The turbine performance as function of rotational velocity and relative wind velocity was analyzed implementing an experimental set-up.

The current research deals with the possibility of relying on wind energy, specifically Flettner rotors; as a source of ships propulsion to reduce ships’ emissions. The paper highlights the technic...

In the world, electric power is the highest need for high prosperity and comfortable living standards. The security of energy supply is an essential concept in national energy management. Therefore, ensuring the security of electricity supply requires accurate estimates of electricity demand. The share of electricity generation from renewables is significantly growing in the world. This kind of energy types are dependent on weather conditions as the wind and solar energies. There are two vital requirements to locate and measure specific systems to utilize wind power: modelling and forecasting of the wind velocity. To this end, using only 4 years of measured meteorological data, the present research attempts to estimate the related speed of wind within the Libyan Mediterranean coast with the help of ANN (artificial neural networking) with three different learning algorithms, which are Levenberg-Marquardt, Bayesian Regularization and Scaled Conjugate Gradient. Conclusions reached in this study show that wind speed can be estimated within acceptable limits using a limited set of meteorological data. In the results obtained, it was seen that the SCG algorithm gave better results in tests in this study with less data.

With the growing adoption of wind-energy technology to help address climate change, we must now also consider the disposition of retired wind-turbine blades, which are not easily recycled. This pressing environmental problem was used as the prompt in a creativity study, where participants were asked to identify potential reuses in a wind-turbine-blade repurposing task (WRT). In past iterations of this study, participants consistently struggled with correctly incorporating the large physical size of wind-turbine blades in their reuse concepts. The Alternate Uses Task (AUT) is an established measure of creativity that involves asking participants to identify uses for common objects like bricks and paper clips. The current work explored whether an AUT can be adapted as an intervention to help overcome the WRT scale challenge so that the appropriateness of reuse concepts can be improved. Students in a fourth-year undergraduate engineering-design course (N = 28) underwent both of two conditions, a scaled-AUT intervention and a typical-AUT control, before the WRT. The results support that a main difficulty with the WRT is object size. Both fluency and flexibility (number and categories of ideas) for the relatively common AUT objects were significantly lower in the scaled AUT than in the typical AUT. However, correctly scaled WRT concepts significantly increased after the scaled AUT, supporting the intervention's effectiveness. While motivated by the real-world problem that decommissioned wind-turbine blades present, the current work focuses on conceptual design and creativity, where incorporating real-world problems may provide value beyond more typical AUTs, which have fewer real-world applications. Thus, for future work, the WRT is proposed as a standard design-study task whose solutions help address a real-world problem.

Currently, the Republic of Adygea is designing and building the Adygea wind farm. Given the parameters of the facility and based on the current regulatory documents, the project provides for the organization of monitoring of load-bearing structures. This paper highlights the issues of organizing geotechnical monitoring of the foundation part of wind turbines and presents solutions for creating an automated diagnostic control system (ADCS).

It is well known that wind energy could represent a promising solution to the continuous increase of energy demand in the modern society. At the end of 2016 the European wind power amounted to 153.7 GW, distributed on 77,000 wind turbines and corresponding to the 10.4% of the electrical energy supplied. Considering the EU program to increase the renewable energy share to 27% by 2030, the key role of the wind energy in the next decade is clear. As the number of wind towers that will be dismantled in the next years will continuously increase, the development of sustainable practices to dispose of these plants at the end of their life is of utmost importance. Some parts of these turbines (tower, foundations, generator and gear box) are constituted by materials having elevated recycling rates, while the blades, that are nowadays made up of thermosetting fiber reinforced polymers, are very difficult to be recycled, because of the nature of the materials involved and their complex composition. Therefore, the aim of this review is to present the state of the art in composite wind blades recycling. In the first chapter, some general concepts about wind energy and composite wind blades are presented. The second section of the work is devoted to the analysis of the most important methods for recycling composite laminates. In the third chapter, a presentation of the recycling processes directly applied on waste composite blades is reported. Considering the actual difficulties in composite blades recycling, particular attention is devoted in the fourth chapter to innovative solutions to develop composite structures with improved recyclability, with some examples of modified thermosetting composites, innovative thermoplastic laminates and composites reinforced with natural fibers. The key aspects of composite wind blades recycling and the future perspectives are summarized in the last section.

Bu çalışmada, rüzgar türbinlerinin rotor torku, tasarlanan küçük ölçekli Savonius ve dört yaprak rotor için toplanan gerçek zamanlı verilere dayanan makine öğrenme yaklaşımı kullanılarak tahmin edilmiştir. Uç hız oranı (TSR), makine öğrenimi modelleme tekniğinde doğrusal regresyon (LR), destek vektör makinesi (SVM) regresyonu ve Gauss işlemi (GP) regresyon yöntemlerinde ana giriş parametresi olarak seçilmiştir. Bu modellerin hiperparametreleri ızgara arama yöntemi ile tanımlanmıştır. RMSE, R2, MSE ve MAE, modellerin deneysel verilere tahimin performansını değerlendirmek için kullanılmıştır. Rotor tork modelleme sonuçları, rüzgar türbinlerinin verimliliğinin modellerin yüksek tahmin doğruluğu ile en üst düzeye çıkarılabileceğini göstermiştir. Öte yandan, Savonius tipi rüzgar türbininin torkunun dört yapraklı türbinden daha yüksek olduğu gözlemlenmiştir.

This paper presents lessons learned from own research studies and field experiments with drivetrains on floating wind turbines over the last ten years. Drivetrains on floating support structures are exposed to wave-induced motions in addition to wind loading and motions. This study investigates the drivetrain-floater interactions from two different viewpoints: how drivetrain impacts the sub-structure design; and how drivetrain responses and life are affected by the floater and support structure motion. The first one is linked to the drivetrain technology and layout, while the second question addresses the influence of the wave-induced motion. The results for both perspectives are presented and discussed. Notably, it is highlighted that the effect of wave induced motions may not be as significant as the wind loading on the drivetrain responses particularly in larger turbines. Given the limited experience with floating wind turbines, however, more research is needed. The main aim with this article is to synthesize and share own research findings on the subject in the period since 2009, the year that the first full-scale floating wind turbine, Hywind Demo, entered operation in Norway. In diesem Beitrag werden Erkenntnisse aus eigenen Forschungsarbeiten und Feldexperimenten mit Antriebssträngen in schwimmenden Windkraftanlagen der letzten zehn Jahre vorgestellt. Antriebsstränge auf schwimmenden Plattformen sind zusätzlich zu Windlasten und -bewegungen auch welleninduzierten Bewegungen ausgesetzt. Diese Studie untersucht die Wechselwirkungen zwischen Antriebsstrang und Plattform aus zwei verschiedenen Blickwinkeln: wie der Antriebsstrang die Konstruktion der Plattform beeinflusst; und wie sich die Bewegungsabläufe der Plattform auf die Dynamik und die Lebensdauer des Antriebsstrang auswirken. Die erste Frage bezieht sich auf die Antriebsstrangstechnik und -gestaltung, während die zweite Frage den Einfluss der welleninduzierten Bewegung betrifft. Die Ergebnisse für beide Perspektiven werden vorgestellt und diskutiert. Insbesondere wird hervorgehoben, dass bei größeren Windkraftanlagen der Einfluss der welleninduzierten Bewegungen auf die Dynamik des Antriebsstrangs nicht so signifikant ist wie die Windlasten. In Anbetracht der begrenzten Erfahrung mit schwimmenden Windkraftanlagen ist jedoch weitere Forschungsarbeit erforderlich. Das Hauptziel dieses Artikels ist es, eigene Forschungsergebnisse zu diesem Thema seit 2009, dem Jahr, in dem die erste schwimmende Windkraftanlage, Hywind Demo, in Norwegen in Betrieb genommen wurde, zusammenzufassen und zu teilen. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

In the last years, renewable energies have been proposed as a solution to mitigate climate change. In this sense, biomass has become a more popular alternative than other sources of renewable energy, such as solar energy and wind power. As its main advantage, biomass is obtained from organic material, which makes it consistent throughout the year. Studies on biomass as a source of energy are usually conducted at a pilot scale to determine its energetic potential. However, there is less emphasis on studying the logistic operations and key variables that enable the feasibility of biomass as a source of energy at an industrial scale. To address this gap, we study the potential of coffee pulp as a source of biomass, and consequently, as a source of energy. To this end, we use the System Dynamics methodology. First, we developed a simulation model where the results indicate that one ton of coffee pulp can produce 180 m3 of biogas, which in turn can generate 0.41 MW of net electricity. Then, we performed a 20-year sensitivity analysis to identify the key variables ensuring electricity generation from coffee pulp which include: harvested area (hectares), cherry coffee yield (ton/ha), and efficient usage of coffee pulp.

Windmills were developed to a high degree between their initial European use in the twelfth century and the twentieth century when mathematical analysis was first applied to optimise the design of ...

Over the last decade, electrical power generation in the territory of the Russian Federation has increased owing to the development of wind power energy. One of the wind energy facilities implemented is the Adygea wind power plant. The design and field supervision for the construction of this facility were performed by specialists from the Mosoblgidroproekt JSC company.

A brief overview of the materials used in wind turbine blades is presented in the following. Wind power is one of the biggest sources of natural energy which is tapped by installing windmills in open areas of land, usually far from metropolitan areas. The biggest task involved in this, is achieving maximum efficiency with minimal cost. One way this can be achieved is by replacing the medieval wind turbine blades with hybrid composite material blades. The main advantage of this is balanced strength and stiffness. Wind turbine blades are manufactured according to certain pre-made mathematical calculations and are placed accordingly so that the blades rotate in a determined direction. The turbine blades are manufactured in different ways, some of which have been discussed further in this paper. The use of new materials such as nano-powders and hybrid fibers revolutionize the current manufacturing processes and throw open the doors to new opportunities, those which involve higher efficiencies, lower environmental impact, lesser wear, etc. Details of such materials and their properties have been discussed in this paper.

The gearbox will directly affect the safety and reliability of the wind turbine, whose failure leads to low processing accuracy and certain economic losses. To address this issue, a deep enhanced fusion network (DEFN) is proposed for the fault diagnosis of the wind turbine gearbox with the experimental vibration data. In the proposed DEFN, three sparse autoencoders are first applied to extract deep features of three-axial vibration signals, respectively. Second, a feature enhancement mapping is developed to minimize the intraclass distance of the deep features in the three-axial vibration. Finally, the fused three-axis features are put into an echo state network for fault classification. The results of the experiment carried out in a wind turbine show that the proposed DEFN has a good fault diagnosis accuracy compared with other peer models. National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [51775112, 71801044, 51975121]; Guangdong Research Foundation [2019B1515120095]; Chongqing Natural Science Fund [cstc2019jcyjzdxmX0013]; CTBU Project [KFJJ2019060] info:eu-repo/semantics/publishedVersion

Sürdürülebilir gelişim için yenilenebilir enerji kaynaklarına olan ihtiyaç her geçen gün artmaktadır. Bu kaynaklardan birisi de rüzgar enerjisidir. Rüzgarın stokastik yapısı nedeniyle rüzgar hızı ve rüzgar gücünün tahmini son yıllarda araştırmacılar tarafından oldukça ilgi çeken bir konu haline gelmiştir. Yapılan çalışmada Türkiye’de yer alan bir rüzgar türbini için 2018 yılı boyunca SCADA sistemi ile elde edilen veri seti ile aynı konum için NASA tarafından paylaşılan meteorolojik veri seti kullanılarak rüzgar gücü tahmini gerçekleştirilmiştir. Girdi değişkenleri olarak SCADA sisteminden çekilen rüzgar hızı, rüzgar yönü ve teorik güç eğrisi; NASA sisteminden çekilen meteorolojik parametreler ve rüzgar gücüne ait geçmiş veriler kullanılmıştır. Modelde yer alan ve hesaplama karmaşıklığına neden olan gereksiz öznitelikler model performansını artırmak amacıyla sarmal seçim yöntemi ile modelden çıkarılmıştır. Sarmal seçim yöntemi olarak Genetik Algoritma (GA) kullanılmıştır. Yapılan çalışmada hem farklı makine öğrenme algoritmalarının tahmin gücü, farklı performans ölçütlerine göre karşılaştırılmış hem de öznitelik seçiminin modele etkisi değerlendirilmiştir. GA ile önerilen nihai modelde değişken sayısı 47’den 9’a indirgenerek gereksiz değişkenler modelden uzaklaştırılmış ve en az sayıda değişken ile R2 değeri 0,98 olan güçlü bir tahmin modeli elde edilmiştir., The need for renewable energy sources for sustainable development has been increasing every day. One of these sources is wind energy. Due to the stochastic nature of the wind, the estimation of wind speed and wind power has been a subject of great interest to researchers in recent years. In this study, wind power estimation was carried out for a wind turbine in Turkey, using the data set obtained by the SCADA system during 2018 and the meteorological data set shared by NASA for the same location. Wind speed, wind direction, and theoretical power curve were taken from the SCADA system as input variables; Meteorological parameters were taken from the NASA system and historical data of wind power were used. Unnecessary features in the model that cause computational complexity are removed from the model with the wrapper selection method to increase model performance. Genetic Algorithm (GA) was used as the wrapper selection method. In the study, the predictive power of different machine learning algorithms was compared according to different performance criteria and the effect of feature selection on the model was evaluated. In the final model proposed by GA, the number of variables was reduced from 47 to 9, unnecessary variables were removed from the model, and a strong prediction model with R2 value of 0.98 was obtained with the least number of variables.