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The objective of this paper is to outline a framework that guides the development of sound maintenance strategies and policies for deep‐sea offshore wind turbines.

An important challenge with offshore wind energy production is to reduce the high operation and maintenance costs. To decrease complexity, and structure the maintenance strategy developing process, systems engineering principles are used.

The framework facilitates integration of fragmented but valuable information from different disciplines in the development of sound maintenance strategies. In addition, the framework may be used to identify knowledge gaps, and areas for further research.

The paper refers to research on deep‐sea offshore wind turbines, which is in its infancy, with a limited amount of data yet available for verification and validation. Deep‐sea offshore installations are not commercialized, and few pilot installations have been installed.

The design of the offshore wind turbines determines operation and maintenance features. Reducing operation and maintenance costs is necessary to make deep‐sea offshore wind projects viable in the first place. The framework contributes to the complicated development of maintenance strategies for a system not yet realized.

Improving reliability is a key factor in reducing the cost of wind energy, which is strongly influenced by the cost of maintenance operations. In this context, this paper aims to propose a degradation model that describes the phenomenon of fault propagation to apply proactive maintenance that will act on the cause of failure to prevent its reoccurrence as well as to improve future system designs.

The methodology adopted consists in identifying the different components of a wind turbine, their causes and failure modes, and then, classifying these components according to their causes of failure.

The result is a classification of the different components of a wind turbine according to their failure causes. From the obtained classification, the authors observed that the failure modes for one component are a failure cause for another component, which describes the phenomenon of failure propagation.

The different classifications existing in the literature depend on the nature, position and function of the different components. The classification of this study consists in grouping the components of a wind turbine according to their failure causes to develop a degradation model considering the propagation of failure in the field of wind turbines.

The purpose of this paper is to discuss how wind farms attract wind turbine manufacturers to get involved in wind turbines’ maintenance service with revenue sharing contract of bundled service under which the background of operation and maintenance (O&M) aftermarket of wind turbine exists. The authors also try to extend the results to the application of product plus service business mode on large-scale equipment O&M service. At present, Chinese wind power industry is suffering from production capacity redundancy. The profit levels for both wind farm and wind turbine manufacturers are relatively low. It is significant for Chinese wind power industry development to coordinate the supply chain of wind power in order to reduce O&M costs and increase revenues.

The present paper discusses product plus aftermarket service contract design on the background of closed-loop product service chain and uncertain equipment demand using revenue sharing contract model.

If centralized decision making is assumed, the authors find that the wind turbine order increases as the aftermarket service effort level and aftermarket service profit increase; aftermarket service effort level is positively correlative to the service efficiency. On the other hand, if decentralized decision making is assumed, the wind turbine order increases as share of the aftermarket service chain by manufacturer to wind farm increases and share of product supply chain by wind farm to manufacturer decreases. The optimal effort level of wind farm increases as the share of aftermarket service chain increases while the optimal effort level of the manufacturer is a concave function of share of aftermarket service chain if service quality linear correlates with effort level. Meanwhile, the authors find that the revenues of the product supply chain and aftermarket service chain have a concave relationship. This relationship is not affected by the format of relationship between service quality and effort level (linear or exponential).

The results could potentially be used to provide the wind turbine manufacturer with a greater profit space and satisfy wind farm’s equipment maintenance demand at the same time. It can also guide the practice of revenue sharing in the aftermarket service and manufacturing servitization.

In this model, the authors assumed that both the forward revenue sharing of power generation by wind farm to manufacturer and the backward revenue sharing of maintenance service by the manufacturer to wind farm exist in closed-loop product service chain. Then the authors discussed channel coordination of such cross-revenue sharing contract.

Wind energy has matured to a level of development at which it is ready to become a generally accepted power generation technology. The aim of this paper is to provide a brief review of the state of the art in the area of electrical machines and power‐electronic systems for high‐power wind energy generation applications. As the first part of this paper, latest market penetration, current technology and advanced electrical machines are addressed.

After a short description of the latest market penetration of wind turbines with various topologies globally by the end of 2010 is provided, current wind power technology, including a variety of fixed‐ and variable‐speed (in particular with doubly‐fed induction generator (DFIG) and permanent magnet synchronous generator (PMSG) supplied with partial‐ and full‐power converters, respectively) wind power generation systems, and modern grid codes, is presented. Finally, four advanced electrical‐machine systems, viz., brushless DFIG, open winding PMSG, dual/multi 3‐phase stator‐winding PMSG and magnetic‐gear outer‐rotor PMSG, are identified with their respective merits and challenges for future high‐power wind energy applications.

For the time being, the gear‐drive DFIG‐based wind turbine is significantly dominating the markets despite its defect caused by mechanical gears, slip rings and brush sets. Meanwhile, direct‐drive synchronous generator, especially utilizing permanent magnets on its rotor, supplied with a full‐capacity power converter has become a more effective solution, particularly in high‐power offshore wind farm applications.

This first part of the paper reviews the latest market penetration of wind turbines with a variety of mature topologies, by summarizing their advantages and disadvantages. Four advanced electrical‐machine systems are selected and identified by distinguishing their respective merits and challenges for future high‐power wind energy applications.

Wind power is an important source of renewable energy and accounts for significant portions in supplying electricity in many countries and locations. The purpose of this paper is to develop a method for wind power system reliability assessment and condition-based maintenance (CBM) optimization considering both turbine and wind uncertainty. Existing studies on wind power system reliability mostly considered wind uncertainty only and did not account for turbine condition prediction.

Wind power system reliability can be defined as the probability that the generated power meets the demand, which is affected by both wind uncertainty and wind turbine failures. In this paper, a method is developed for wind power system reliability modeling considering wind uncertainty, as well as wind turbine condition through health condition prediction. All wind turbine components are considered. Optimization is performed for maximizing availability or minimizing cost. Optimization is also conducted for minor repair activities to find the optimal number of joint repairs.

The wind turbine condition uncertainty and its prediction are important for wind power system reliability assessment, as well as wind speed uncertainty. Optimal CBM policies can be achieved for optimizing turbine availability or maintenance cost. Optimal preventive maintenance policies can also be achieved for scheduling minor repair activities.

This paper considers uncertainty in both wind speed and turbine conditions and incorporates turbine condition prediction in reliability analysis and CBM optimization. Optimization for minor repair activities is studied to find the optimal number of joint repairs, which was not investigated before. All wind turbine components are considered, and data from the field as well as reported studies are used.

Sustainable energy has been on the political agenda in Denmark for decades. This chapter will highlight how wind turbine production quite unforeseen became a great success in Denmark before the turn of the Millennium. An integrative public leadership approach using a mix of supportive institutional designs and instruments, combined with an unexpected bottom-up pressure for alternatives to nuclear power, promoted ways for wind turbine innovation and production in the 1970s. After the turn of the Millennium, being a huge financial success creating many new jobs and export has it developed into a cluster based on huge investments and professionalised developers. The comprehensive transition of wind turbine production in Denmark, from small scale to large scale, has however provided a counterproductive decrease in community commitment for local renewable energy production.

Denmark is known internationally as a climate frontrunner and not only due to wind turbine production and planning. The status is obtained by polycentric governance applied in cooperative-owned energy systems. The Danish response to climate change is a concerted effort of a plethora of public and private actors, providing a crucial momentum and robustness in climate politics not at least generated from a genuine civic society involvement. ‘The Danish Energy Model’; a withhold strategic effort to combine ambitious renewable energy goals, energy efficiency targets and political support of technical and industrial development has for four decades, succeeded in providing high levels of cheap energy supply, while partly reducing fossil fuel dependency at the same time.

The purpose of this paper is to find out a new potential site for energy generation to maximize the energy generation via installing utility wind turbines.

In this paper, Weibull two-parameter methodologies are used to determine the effectiveness of the wind speed at three different heights including 80, 60 and 30 m. Standard deviation and wind power density (WPD) are also calculated for the site. After analyzing the wind resource, the wind turbine selection is materialized to maximize the energy production, considering the best configuration of the wind turbines that is suitable for the site. In the end, economic aspect is also calculated.

The mean Weibull dimensionless parameter k is found to be 2.91, 2.845 and 2.617, respectively. The mean Weibull scale parameter c is found to be 6.736, 6.524 and 6.087 at the heights of 80, 60 and 30 m, respectively. The mean standard deviation is found to be 2.297, 2.249 and 2.157 at the heights of 80, 60 and 30 m at the heights of 80, 60 and 30 m, respectively. Wind power densities are calculated to be 265, 204 and 157.9 W/m² at the heights of 80, 60 and 30 m, respectively (highest in the month of July when the mean wind speed is 7.707 m/s and WPD is 519 W/m²). Finally, site-specific economic analysis of wind turbines is carried out, which shows $0.0230 per kWh at the height of 80 m.

The results show that the site is beneficial for the installation of small and large wind turbines.

This paper aims to design an optimum vertical axis wind turbine (VAWT) and assess its techno-economic performance for wind energy harvesting at high-speed railway in Malaysia.

This project adopted AutoCAD and ANSYS modeling tools to design and optimize the blade of the turbine. The site selected has a railway of 30 km with six stops. The vertical turbines are placed 1 m apart from each other considering the optimum tip speed ratio. The power produced and net present value had been analyzed to evaluate its techno-economic viability.

Computational fluid dynamics (CFD) analysis of National Advisory Committee for Aeronautics (NACA) 0020 blade has been carried out. For a turbine with wind speed of 50 m/s and swept area of 8 m², the power generated is 245 kW. For eight trains that operate for 19 h/day with an interval of 30 min in nonpeak hours and 15 min in peak hours, total energy generated is 66 MWh/day. The average cost saved by the train stations is RM 16.7 mil/year with battery charging capacity of 12 h/day.

Wind energy harvesting is not commonly used in Malaysia due to its low wind speed ranging from 1.5 to 4.5 m/s. Conventional wind turbine requires a minimum cut-in wind speed of 11 m/s to overcome the inertia and starts generating power. Hence, this paper proposes an optimum design of VAWT to harvest an unconventional untapped wind sources from railway. The research finding complements the alternate energy harvesting technologies which can serve as reference for countries which experienced similar geographic constraints.

The purpose of this paper is to analyze wind characteristics and their effects on wind turbine components and energy generation at the candidate site.

The methodology covered the detailed investigation of wind characteristics using Weibull k and c parameters and standard deviation at 30 m above the ground level (AGL). The wind shear coefficient and air density were also studied. The weight model was developed to determine the effects on wind turbine components and energy generation. At last, an economic assessment was carried out to determine the pre- and post-effects of the weight model on the cost of energy per kilowatt-hour.

The mean standard deviation, Weibull k parameter and Weibull c parameter were found to be 2.157, 2.617 and 6.087 m/s, respectively, at 30 m for a period of a year. The mean wind shear coefficient was found to be 0.176 for a year. The calculated results showed that site-specific midrange and amplitude force were 40.95 per cent and 37.75 per cent on wind turbine mechanical components, respectively. The average rise in force and drop in energy was found to be 35.50 per cent and 47.55 per cent, respectively. The lift coefficient, drag coefficient and pitching moment considering values (a, 0.1 and 0.2) showed an increase in force on wind turbine components that resulted in a drop in energy. The cost assessment results showed that the cost of energy was increased from US$0.032/kWh to 0.0466/kWh for wind turbine A.

An accurate determination of the weight factor is necessary for near-reality assessment of wind energy yield and rise of force on the wind turbine. The results paved the way for site-specific design optimization of wind turbines.

The study contributes to the site-specific wind characteristic-based weight model to determine the effects of wind loads on wind turbine components and energy generation and compared with the specified design standard. The lift coefficient, drag coefficient and pitching moment coefficient show a rise in the force while considering the weight factor values. The results show that the site has the potential to generate energy at the lowest cost per kilowatt-hour, but it needs wind turbine design adjustments according to site-specific wind characteristics. If site-specific wind characteristics are considered, it would lead to maximum energy generation and high reliability of wind turbine components.

The non-stationary operational wind loads vary in time and site and has remarkable effect on wind turbine drive train. The purpose of this paper is to determine the effects of wind class 3 and 7 on the life of wind turbine drive train. The two-wind class 3 and 7 are described by average wind speed and weight factor and effects of two variables on wind energy generation and wind turbine drive train studied.

The load distribution method is used to calculate stress range cycles for wind class 3 and 7. To determine the rise of force on wind turbine drive train, the load cycle method is proposed. The fatigue damage model is studied with respect to influence of different wind speeds and wind shear factor and then results analysed accordingly. Also sensitivity analysis has been carried out to assess the percentage of drop of energy generation and rise of tangential force for wind class 3 and 7. Linear fit method is used to determine the inclination of wind variation and wind shear of wind class 3 and 7. In this regard, two practical wind sites fall under the wind class 3 and 7 and 1.5 MW wind turbine have been taken in to account.

The results showed that the average rise of force on wind turbine drive train is 37.5% which can influence the drop in energy 34.7% for wind class 3. Similarly, the results of wind class 7 are showing that the average rise in force and drop in energy found to be 49.05% and 51.16%, respectively. The wind class 7 have higher tendency of wind fluctuations and weight factor that can cause a damage to wind turbine drive train components. The results showed that when wind speed increases to rated power 11.5 m/s the damages occurred and remain steady. Similarly, when weight factor increased from 0.18 to onwards the damage occurred. The increased wind loads increased the tangential loads on the wind turbine decreased life of the gearbox.

The results of study suggest that wind turbine should be design according to site specific wind environment for maximum energy generation and lowers the wind loads on the drive train component.