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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.

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.

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.

A new method for forecasting wind turbine capacity of China is proposed through grey modelling technique.

First of all, the concepts of discrete grey model are introduced into the NGBM(1,1) model to reduce the discretization error from the differential equation to its discrete forms. Then incorporating the conformable fractional accumulation into the discrete NGBM(1,1) model is carried out to further improve the predictive performance. Finally, in order to effectively seek the emerging coefficients, namely, fractional order and nonlinear coefficient, the whale optimization algorithm (WOA) is employed to determine the emerging coefficients.

The empirical results show that the newly proposed model has a better prediction performance compared to benchmark models; the wind turbine capacity from 2019 to 2021 is expected to reach 275954.42 Megawatts in 2021. According to the forecasts, policy suggestions are provided for policy-makers.

By combing the fractional accumulation and the concepts of discrete grey model, a new method to improve the prediction performance of the NGBM(1,1) model is proposed. The newly proposed model is firstly applied to predict wind turbine capacity of China.

Pakistan is an energy starving country that needs continuous supply of energy to keep up its economic speed. The aim of this paper is to assess the wind resource and energy potential of Quaidabad site for minimizing the dependence on fuels and improving the environment.

The Quaidabad site wind shear coefficient and turbulence intensity factor are investigated. The two-parameter k and c Weibull distribution function is used to analyze the wind speed of site. The standard deviation of the site is also assessed for a period of a year. The wind power density and energy density are assessed for a period of a year. The economic assessment of energy/kWh is investigated for selection of appropriate wind turbine.

The mean wind shear coefficient was observed to be 0.2719, 0.2191 and 0.1698 at 20, 40 and 60 m, respectively, for a period of a year. The mean wind speed is found to be 2.961, 3.563, 3.907 and 4.099 m/s at 20, 40, 60 and 80 m, respectively. The mean values of k parameters were observed to be 1.563, 2.092, 2.434 and 2.576 at 20, 40, 60 and 80 m, respectively, for a period of a year. The mean values of c m/s parameter were found to be 3.341, 4.020, 4.408 and 4.625 m/s at 20, 40, 60 and 80 m, respectively, for a period of a year. The major portion of values of standard deviation was found to be in between 0.1 and 2.00 at 20, 40, 60 and 80 m. The wind power density (W/m²) sum total values were observed to be 351, 597, 792 and 923 W/m² at 20, 40, 60 and 80 m, respectively, for a period of a year. The mean coefficient of variation was found to be 0.161, 0.130, 0.115 and 0.105 at 20, 40, 60 and 80 m, respectively. The sum total energy density was observed to be 1,157, 2,156, 2,970 and 3,778 kWh/m² at 20, 40, 60 and 80 m, respectively. The economic assessment is showing that wind turbine E has the minimum cost US$0.049/kWh.

The Quaidabad site is suitable for installing the utility wind turbines for energy generation at the lowest cost.

The objective of this paper to assess the wind energy potential of the Sujawal site for minimizing the dependence on fossil fuels.

The site-specific wind shear coefficient and the turbulence model were investigated. The two-parameter, k and c, Weibull distribution function was used to analyze the wind speed of the Sujawal site. The standard deviation of the site was also assessed for a period of a year. Also, the coefficient of variation was carried out to determine the difference at each height. The wind power and energy densities were assessed for a period of a year. The economic assessment of energy/kWh was investigated for selection of appropriate wind turbine.

The mean wind shear of the Sujawal site was found to be 0.274. The mean wind speed was found to be 7.458, 6.911, 6.438 and 5.347 at 80, 60, 40 and 20 m, respectively, above the ground level (AGL). The mean values of k parameter were observed to be 2.302, 2.767, 3.026 and 3.105 at 20, 40, 60 and 80 m, respectively, for a period of a year. The Weibull c m/s parameter values were found to be 8.415, 7.797, 7.265 and 6.084 m/s at 80, 60, 40 and 20 m, respectively. The mean values of standard deviation were found to be 0.765, 0.737, 0.681 and 0.650 at 20, 40, 60, and 80 m, respectively. The mean wind power density (W/m²) was found to be 287.33, 357.16, 405.16 and 659.58 for 20, 40, 60 and 80 m, respectively. The economic assessment showed that wind turbine 7 had the minimum cost/kWh US$ 0.0298.

The Sujawal site is suitable for installing the utility wind turbines for energy generation at the lowest cost; hence, a sustainable solution.

Power‐electronic systems have been playing a significant role in the integration of large‐scale wind turbines into power systems due to the fact that during the past three decades power‐electronic technology has experienced a dramatic evolution. This second part of the paper aims to focus on a comprehensive survey of power converters and their associated control systems for high‐power wind energy generation applications.

Advanced control strategies, i.e. field‐oriented vector control and direct power control, are initially reviewed for wind‐turbine driven doubly fed induction generator (DFIG) systems. Various topologies of power converters, comprising back‐to‐back (BTB) connected two‐ and multi‐level voltage source converters (VSCs), BTB current source converters (CSCs) and matrix converters, are identified for high‐power wind‐turbine driven PMSG systems, with their respective features and challenges outlined. Finally, several control issues, viz., basic control targets, active damping control and sensorless control schemes, are elaborated for the machine‐ and grid‐side converters of PMSG wind generation systems.

For high‐power PMSG‐based wind turbines ranging from 3 MW to 5 MW, parallel‐connected 2‐level LV BTB VSCs are the most cost‐effective converter topology with mature commercial products, particularly for dual 3‐phase stator‐winding PMSG generation systems. For higher‐capacity wind‐turbine driven PMSGs rated from 5 MW to 10 MW, medium voltage multi‐level converters, such as 5‐level regenerative CHB, 3‐ and 4‐level FC BTB VSC, and 3‐level BTB VSC, are preferred. Among them, 3‐level BTB NPC topology is the favorite with well‐proven technology and industrial applications, which can also be extensively applicable with open‐end winding and dual stator‐winding PMSGs so as to create even higher voltage/power wind generation systems. Sensorless control algorithms based on fundamental voltages/currents are suggested to be employed in the basic VC/DPC schemes for enhancing the robustness in the entire PMSG‐based wind power generation system, due to that the problems related with electromagnetic interferences in the position signals and the failures in the mechanical encoders can be avoided.

This second part of the paper for the first time systematically reviews the latest state of arts with regard to power converters and their associated advanced control strategies for high‐power wind energy generation applications. It summarizes a variety of converter topologies with pros and cons highlighted for different power ratings of wind turbines.

Acute shortage of potable water and energy supplies is expected to raise in developing countries in the near future. One solid way to address these issues is to exploit renewable energy resources efficiently. Hence, this study aims to investigate wind and solar energy use in the coastal areas of southern Iran for renewable-powered seawater desalination and hydrogen production systems.

To accomplish the aforementioned purpose, five areas most prone to the problems in Iran, namely, Mahshahr, Jask and Chabahar ports and Kish and Hormoz islands were scrutinized. To ascertain the amount of wind and solar energy available in the areas, Weibull distribution function, Angstrom–Prescott equation and HOMER software were used.

The findings indicated that wind energy density in Kish was 2,014.86 (kWh/m².yr) and solar energy density in Jask equaled to 2,255.7 (kWh/m².yr) which possessed the best conditions among the areas under study. Moreover, three commercial wind turbines and three photovoltaic systems were examined for supplying energy needed by the water desalination and hydrogen production systems. The results showed that application of wind turbines with rated power of 660, 750 and 900 kWh in Kish could result in desalting 934,145, 1,263,339 and 2,000,450 (m³/yr) of seawater or producing 14,719, 20,896 and 31,521 (kg/yr) of hydrogen, respectively. Additionally, use of photovoltaic systems with efficiency of %14.4, %17.01 and %21.16 in Jask could desalinate 287, 444 and 464 (m³/yr) of seawater or generate 4.5, 7 and 7.3 (kg/yr) of hydrogen, respectively.

Compared to the huge extent of water shortage and environmental pollution, there has not been conducted enough studies to obtain broader view regarding use of renewable energies to solve these issues in Iran. Therefore, this study tries to close this gap and to give other developing nations the idea of water desalination and hydrogen production via renewable energies.

The purpose of this paper is to investigate wind power potential of site using wind speed, wind direction and other meteorological data including temperature and air density collected over a period of one year.

The site-specific air density, wind shear, wind power density, annual energy yield and capacity factors have been calculated at 30 and 10 m above the ground level (AGL). The Weibull parameters have been calculated using empirical, maximum likelihood, modified maximum likelihood, energy pattern and graphical methods to determine the other dependent parameters. The accuracies of these methods are determined using correlation coefficient (R²) and root mean square error (RMSE) values.

The site-specific wind shear coefficient was found to be 0.18. The annual mean wind speeds were found to be 5.174 and 4.670 m/s at 30 and 10 m heights, respectively, with corresponding standard deviations of 2.085 and 2.059. The mean wind power densities were found to be 59.50 and 46.75 W/m² at 30 and 10 m heights, respectively. According to the economic assessment, the wind turbine A is capable of producing wind energy at the lowest value of US$ 0.034/kWh.

This assessment provides the sustainable solution of energy which minimizes the dependence on continuous supply of oil and gas to run the conventional power plants that is a major cause of increasing load shedding in the significant industrial and thickly populated city of Pakistan. Also, this will minimize the quarrel between the local power producer and oil and gas supplier during the peak season.

This wind resource assessment has some important social implications including decreasing the environmental issues, enhancing the uninterrupted supply of electricity and decreasing cost of energy per kWh for the masses of Karachi.

The results are showing that the location can be used for installing the wind energy power plant at the lower cost per kWh compared to other energy sources. The wind energy is termed as sustainable solution at the lowest cost.

Wind as a major source of renewable energy has received tremendous attentions due to its unique features to reduce carbon emission and also to keep the environment safe. Nevertheless, to use wind energy properly, the environmental circumstances and geographical location related to wind intensity should be considered as a priority. Different factors may affect the selection of a suitable location for developments of wind power plants; thus, these factors should be considered concurrently to identify the optimum location of wind plants.

In this study, first, basic data envelopment analysis (DEA) was used, then dual DEA was used and, finally, Anderson Petersen (AP) model of dual DEA was selected to prioritize cities or decision-making units (DMUs). Numerical Taxonomy (NT) method was also used to assess the validity of AP dual model in DEA. The prescribed approach was applied for five cities in East Azerbaijan province of Iran.

The results indicate that wind power as a renewable energy can be harnessed in few cities, and the ranking by DEA illustrated that the city of Tabriz is the first priority.

Low environmental degradation effects in comparison to other methods and the ability to utilization at a widespread level include the benefits of using wind energy in the generation of electricity. In this regard, the study of relevant potentials and finding suitable locations for the deployment of wind energy utilization equipment are essential. Using DEA method helps us to choose optimal locations according to different criteria.

Wind energy is justifiable in reducing social costs in comparison with fossil fuel plants, which includes negative effects, and its electricity can be used as a sustainable energy in the country's economic, social and cultural development.

For identifying the most proper location for development of wind power plants in Iran, DEA is applied for the first time to prioritize the suitable locations for installations of wind turbines among five different cities in the East Azerbaijan region. A number of crucial factors including land price, distance to power, rate of natural hazards, wind speed and topography are considered for location optimization of wind turbines for the first time. Also, to validate the results of DEA method, NT method is used to assess the validity of AP dual model in DEA.