Keywords

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

1 Introduction

Global warming and climate change are driven by the production of greenhouse gas emissions. The availability of fossil fuels is limited. The concern about global warming, climate change and the scarcity of fossil fuels have leaded us to renewable energy. One of the widest recognized renewable energy is Wind energy. Wind energy is getting more attention in recent years. Wind energy is considered clean, zero-carbon emitting energy source, original, diversified and show promising development in the future [1]. Wind energy is growing at 20–30 % annually making it the fastest growing new source of electricity worldwide [2]. According to Robert Thresher, Director of the U.S. Department of Energy’s (DOE) national Wind Technology Center, “In the 1980s, wind cost about 40 cents per kilowatt hour. Now the cost is between 4 and 6 cents per kilowatt hour, so we’ve reduced the cost of wind by an order of magnitude in the past two decades [2].” This fact even strengthens the argument that wind energy will be one of the most promising renewable energy in the future. The cost will be significantly lower compared to fossil fuels that have price volatility and keep increasing from time to time. Wind energy also supported by government. Wind energy users will receive tax benefits through the federal production tax credit (PTC).

Below are the advantages of using wind energy [3]:

  • Wind is naturally available and can be capture efficiently

  • Zero fuel costs—abundant and inexhaustible

  • Clean energy—cause no carbon dioxide emissions

  • Reliable—avoid reliance on importing fuels

  • Land friendly—wind turbines are usually tall which occupied only a small fraction of land on the ground. The land surrounded the tower can still be used for other activities

  • Wind turbines could be an interesting feature of the landscape

  • Wind turbines can benefit rural areas which are not connected to power grid

  • There are variety of wind turbines available which can fit range of needs.

To be able to produce energy from wind, wind turbines are required. The current designs of wind turbines usually have 2 or more blades with diameter of rotor between 70 and 100 m. It consists of 1–3 MW. Most of the wind turbines have three blades which look like airplane’s wing. This airplane’s wings look alike have the ability to create lift from air over the blade. Usually, the blades are made of a composite material structure [4]. These blades are positioned on a steel towers. The heights of the towers are varying from 30 to 85 m [5]. The natural wind kinetic energy will be converted by generator of the wind turbines to electricity.

Currently, the most well recognized designs for wind turbines are Horizontal Axis Wind Turbines (HAWT) and Vertical Axis Wind Turbines (VAWT). Horizontal Axis wind Turbines place main rotor shaft in horizontal direction. It usually requires a high wind speed and operates at high RPM. The vibration levels are quite high and can be noisy. Vertical Axis Wind Turbines place main rotor shaft in vertical direction. It usually requires low wind speed and operates at lower RPM. The vibrations levels are lower than HWAT therefore the noise levels are also lower [6]. Both wind turbines have their advantages and disadvantages.

However, up until now, research and development are still being conducted to find the most efficient design of wind turbines so that it will be able to increase the efficiency and power output of wind energy.

This paper is intended to help Wind group in Energy Trust of Oregon to find the most promising technology in wind turbines. Energy Trust of Oregon focuses mainly on small scale wind. The technologies identified in Chap. 2 are not exclusively developed to be applied to small scale wind. However, technologies are scalable. This paper believes that the technologies could be applied to utility scale or small scale wind turbines. Manufacturers can apply one of those technologies to their line of products regardless the size of the wind turbines. Therefore, the technologies in Chap. 2 are appropriate to be evaluated using technology forecasting methodology.

Forecasting methodologies used in this paper are bibliometrics, patent analysis, and growth curve. Those forecasting methodologies will be performed to identify which emerging wind turbines are showing the most promising development and close to maturity. This paper then will try to explore the key manufacturers in wind turbines that develop the emerging wind turbines.

2 Literature Review

2.1 Wind Turbine

Wind Turbine works the opposite principle of a fan. Wind turbine is utilizing wind to make electricity. Wind turbines convert the kinetic energy of wind into mechanical power. This mechanical power can be used to move generator that will convert this mechanical power into electricity. Wind Turbines comprise of components that work as an entity, e.g. anemometer, blades, brake, controller, gearbox, generator, high speed shaft, low speed shaft, nacelle, pitch, rotor, tower, wind direction, wind vane, yaw drive and yow motor [7].

As mentioned in previous section, the most well known wind turbines designs are HAWT and VAWT. However, it is believed that the designs of wind turbines could be better in order to produce electricity more efficiently.

There are several wind turbines designs are in development. All of those designs offer different advantages. This paper has identified 5 wind turbine designs that might evolve in the future. Those wind turbines are based on Horizontal-Axis principle. This paper is not intended to focus on horizontal-axis principle. However, the development of the technology in wind turbines seems to evolve more in horizontal-axis principle rather than vertical-axis principle.

2.1.1 Jet Engine Wind Turbine

Jet Engine Wind Turbine is a turbine design that surrounds its blades with shroud. This shroud is based on the principles of high bypass jet engine design that is used by commercial jet engines to increase the efficiency [8]. From the front, the wind turbines will look like jet engine. When air approaches, blades will direct the air to rotor, pass it and emerges on the other side. The shroud will guides this relatively fast-moving air from outside into the area behind rotors. This mechanism will help the wind turbines to suck more air [8].

There are several advantages of jet engine wind turbine [9] which includes but not limited to: reduce the cost of generating electricity from wind power by 50 %, jet engine wind turbines can utilize wind energy more efficiently by extracting more input and producing more output, footprints would be smaller, reliability is higher than normal wind turbines because it can handle lower and higher wind better, essentially safer because it is using engineering of jet engines and can be placed nearer to populations. Last but not least, this jet engine wind turbine will reduce the size of wind turbine significantly. Reduction in size means that more wind turbines can be put together more closely than conventional wind turbines (HAWT or VAWT). Because it can be put closer together, the amount of power produced by the area of land by jet engine wind turbine also increases.

2.1.2 Gearless Wind Turbine

Gearless wind turbine will not depend on gearbox. In fact, the design gets rid of the gearbox completely. The rotor shaft is attached directly through generator rather than mechanical center gear. It will spin at the same speed as the blades to generate energy [10]. Some gearless wind turbines produce electricity using permanent magnet machines that allows the motion of the blade to stimulate a voltage field that lead to the creation of electrical current [11].

The advantages of using gearless wind turbines are [12]: higher reliability because it does not break easily, cost saving because maintenance frequency will be lower, high efficiency because direct gearless drive eliminates gear loss, low noise and less influence to grid [11].

2.1.3 Magnus Wind Turbine

Magnus wind turbine can be described as a wind turbine that consist of rotating part and non rotating root parts that looks like cylinders with additional spiral-shaped structures. It also has a part called turbulators. The rotating cylinders will create the Magnus force and the spiral-shaped structures will create the driving force. The whole process will ensures an aerodynamic principle [12].

There are several advantages of Magnus wind turbine over the conventional wind turbines [12] e.g. the rotation is low speed that decrease the noise and increase the long lasting durability, help improve environmental by reducing green house emissions, the unique design will create curiosity that lead to great environmental education, it can work with a low wind velocity, rotating cylinder will create more stability because it is automatically optimized to incarcerate various wind velocity.

2.1.4 Airborne Wind Turbine

Airborne wind turbine is a wind turbine that is floating and supported in the air without tower and it is controlled by computer. It floats around 2000 feet height and generated power that will be transferred to the ground through tether which later will be ready for consumption via a power grid [13].

The idea of this wind turbine lies on the height of the wind turbine itself. With higher altitude, wind speed and consistency can be maintained which will result in more power, more often. Therefore, electricity production can be more significant compare to conventional wind turbines.

There are several advantages of airborne wind turbine [14, 15], e.g. the energy production will be more consistent, the capital cost is fairly lower than conventional wind turbines, it delivers the most cost-effective renewable energy, lower noise, birds and bats friendly, less footprint, mobile and easy to install closer to power grid and ideal for off grid applications.

2.1.5 LIDAR Wind Turbine

LIDAR is shortened from Light Detection and Ranging. LIDAR wind turbine is the new generation of wind turbine that uses laser to analyze and predict wind speeds, directions, gusts and turbulence. The laser will help the wind turbines to anticipate the upcoming wind by position the wind turbine and adjust it toward the wind so it will be used more efficiently. By doing that, it can help to preserve the wind turbine to live longer [16].

The LIDAR is usually positioned on a wind turbine rotor. It constantly adjusts the blades so that the components are protected. The energy production will increase and the extreme loads will be decreased. The laser will scan the wind and transfer the information to fiber optic detector that will fed to on-board processor [17].

The advantages of using LIDAR wind turbines [16, 17] e.g. increase energy production by up to 10 % because the possibility of using longer blades, it can significantly reduce the CO2 emissions because of the smart Laser, greater energy capture and machine lifetime is longer.

All those wind turbine show promising application in wind energy. If they all are well developed, a lot of parties will benefit from the application. It is very difficult to choose or predict which wind turbines are in steady developing stages since all the wind turbines above are still in emerging stage. Chapter 3 will use bibliometrics and patent analysis method to analyze all of the emerging wind turbines. Growth curve will show the development curve of each of the wind turbines. The information from the analysis will help decision maker to be able to make a better assessment and decision on which wind turbines they should pursue or focus on.

2.2 Technology Forecasting

Technology is not static. Technology will keep developing and the existing technology might become obsolete in the future. It is very difficult for companies to decide whether they should optimize the usage of the current technology or develop and move to the new technology. Technology forecasting will help technology managers to sustain competitive advantage by forecasting and assessing the technological development [18]. Not only that, technology forecasting will also help companies in anticipating the direction and pace of changes as well as identify and evaluate market opportunities or threats, develops administrative strategies, and adjusting R&D activities with new product development [19]. Technology forecasting requires company to continuously monitor technology development which will give the company the opportunity for early identification of future application and its potential development. Technology forecasting usually focuses on particular technology fields and aims to find the most promising technology in the future [19]. Technology forecasting is different from technology speculation. Technology forecasting attempts to forecast based on available data through the use of logical and explicit methods [20]. It can be used for short term or long term exercise. Short term will range from 1 to 2 years, medium will be up to 10 years and long term will be up to 20 years. The longer the time frame, the accuracy of the forecasting will be more challenging [21].

There are two types of technology forecasting. The first one is exploratory technology forecasting which based on today’s knowledge and leaning towards the future. The second one is normative technological forecasting that start from future scenarios and work backwards to the present [21].

There are several technology forecasting methods available to facilitate managers on forecasting technology. Technology forecasting methods are divided into several categories. They are expert opinion, trend analysis, statistical methods, monitoring and intelligence methods, modeling and simulation, scenario planning, economic methods, descriptive and matrices methods and creativity [18, 20]. Expert opinion will ask the opinion of experts related to the subject matter. It usually will involve interrogation followed by feedback of responses. The examples of expert opinions are Delphi method, focus group, etc. Trend Analysis will look at the trend to forecast the technology. It is related to technology life cycle and predicts when technology will reach a particular life cycle stage. The examples of trend analysis are growth curve, trend impact analysis, etc. Monitoring and intelligence method will monitor variations, environmental scan, and technology watch for the forecasting attributes, for example: bibliometrics. Statistical method will utilize available historical data for forecasting purpose. The examples of statistical method are correlation analysis, risk analysis, etc. Modeling and simulation are also used in forecasting method by using a simulation that is a simplified version of real world problems. Examples of Modeling and simulation methods are agent modeling, cross impact analysis, etc. Scenario planning will depict several scenarios based on assumptions that have been validated for forecasting method, for example: scenario simulation. Economics method will employ mathematical approach for forecasting method. Examples of economic method are decision analysis, cost-benefit analysis, etc. Descriptive and Matrices method are also popular in forecasting technology. Examples of this method are roadmapping, social impact assessment, mitigation analysis, etc. Last but not least, creativity method is also used in forecasting method. The famous example of creativity is TRIZ.

3 Methodology

Technology forecasting methods to forecast the wind turbines in this paper are bibliometics, patent analysis and growth curve. Bibliometrics will analyze the trend by finding the text and literature from scientific publications. Patent analysis will plot and count the number of related patents to see the industries’ trends. The growth curve will plot the trend of accumulative patents for jet engine wind turbine, gearless wind turbine, airborne wind turbine, magnus wind turbine, and LIDAR wind turbine.

Bibliometrics is a methodology that measures and analyzes the enormous amount of texts and literatures of specific technology [22, 23]. Bibliometrics method will capture the information in the body of the content and identify the hidden-pattern of the literatures. According to [24], bibliometrics will help researchers in the decision making process by exploring, organizing, and analyzing the historical data. It provides an interesting data source of R&D activities. Not only that, bibliometrics also provides nicely accessible and cost-effective information [25]. There are three types of bibliometrics analysis, e.g. citation analysis, patent analysis and publication analysis [26]. Citation analysis will examine the patterns among papers to identify the interaction of papers. Patent analysis will study related patents to explore industries’ interests and trends. Publication analysis will look into papers or articles that examine the subject matter and as such tell indicators of R&D Activities [26]. Bibliometrics method being used in this paper is publication analysis and patent analysis. The source of bibliometrics used in this paper is Compendex (Engineering Village Database). This paper will search the publications related to gearless wind turbine, Magnus wind turbine, jet engine wind turbine, airborne wind turbine and LIDAR wind turbine from 1969 to 2010.

One or more keywords are used to search the publications. Some wind turbines are pretty straight forward for example: jet engine wind turbine. However, some will have different names of the wind turbine for example: Gearless wind turbine will also be called direct drive generator turbine.

Below is the table that represents the keywords being used to search the publications related to the emerging wind turbines

Patent analysis will analyze the number of patents to explore the technological competitiveness and technology trend in the industries. Patent analysis is straightforward and adequate to perform the analysis because of the availability of free patent databases. By counting the number of patents registered by firms, this paper will be able to present the trends in research and business environment [27]. Also, measuring the growth of number of patents in a specific technology by using keywords can recognize the overall technology forecasting model [24]. For the patent counts, this paper gathers the information of patents from United States Patent and Trademark Office (USTPO), European Patent Organization (EPO), and World Intellectual Property Organization (WIPO). The keywords being used for each wind turbines are the same with bibliometrics keywords presented in Table 1.

Table 1 Bibliometrics key word search
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This paper will assume diffusion of the wind turbine technologies as measured by number of patents and publications.

This paper utilize growth curve to map the patent activities. It will forecast the technology by fitting a growth curve to a set of data, and then extrapolating the growth curve beyond the range of the data to obtain an estimate future performance. There most frequent used growth curves for forecasting are pearl growth curves and Gompertz curve. Pearl curve also known as logistic curve, and it is well-known for its usage for population forecasting. Pearl curve is usually symmetric at the infliction point and plots a straight line. Gompertz curve depict a curve where the development is the slowest in the beginning and the end of the time period. At the infliction point, Gompertz curve is not symmetric and does not plot a straight line. Generally, pearl curve will be used for forecasting technology substitution. Meanwhile, Gompertz curve is mostly used to forecast absolute technical performance [21].

Since, we are looking on emerging of wind turbine to substitute the current wind turbine, this paper will use Pearl growth curve with the following formula [28]:

$$ Y = \frac{L}{{1 + \alpha e^{ - bt} }} $$

Where:

L:

the upper limit to growth of Y

T:

time (Y is a function of time)

e:

the base of natural logarithms

Change in \( \alpha \) affect location only, while changes in b affect the shape only.

The upper limit of the growth curve is based on assumption of similar technology. In this chapter, all the emerging wind turbines will be plotted in refer to Horizontal Axis Wind Turbine that has matured. The pearl curve above will represent annual accumulative growth. The S curve indicated that the beginning of the time period will be slow and increase in the adoption phase and slowing down when the technology approach maturity [29]. The results of the pearl curve plotted from the number of patents will help researchers to understand the technology trends in the future [30].

4 Results and Analysis

4.1 Bibliometrics Analysis

The searching of the keyword in bibliometrics analysis utilized Compendex (Engineering Village) database. The searching includes the publications from 1969 to 2010 using the keywords presented in Table 1. Figures 1, 2, 3, 4, 5 will give illustrations of the publications development for each wind turbine with X-axis represents the year and Y-axis represents number of publications. Figure 1 show the growth of publications related to jet engine wind turbine. The numbers of publications decrease after 2007. The speculation is the technology is close to maturity and it will be incorporated with other technology. Magnus wind turbine shows a slow development over time. The publications related to Magnus Wind Turbine first appeared in 1981 and since then, not too many publications were published in this area. Similar thing also happened with LIDAR wind turbine and airborne wind turbine. The publications growth of these two wind turbine are not constant. Some years show no activity in the publications, therefore the graphs are not continuous. The speculation for Magnus, LIDAR and airborne wind turbine is these technologies still in development stage, therefore the publications related to these wind turbines are still developing over time. Gearless wind turbine shows that this technology is still developing especially in the past 5 years. The publications related to gearless wind turbine show significant improvement in the past 5 years.

Fig. 1
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Number of publications of jet engine wind turbine by year

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Fig. 2
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Number of publications of magnus wind turbine by year

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Fig. 3
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Number of publications of magnus wind turbine by year

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Fig. 4
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Number of publications of gearless wind turbine by year

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Fig. 5
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Number of publications of LIDAR wind turbine by year

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From the publication analysis above, we can see that gearless wind turbine leads in the publications numbers especially in the past 5 years. Even though the graph of the publications does not show the continuity compare to jet engine graph, however the total number of publications of gearless wind turbine exceed publications of jet engine wind turbine. Jet engine wind turbine comes behind gearless wind turbine and show continuity of publications over time. Magnus, LIDAR and airborne wind turbine does not show the publications trends in its area since the graph of the publication growth showing a limited number of publications.

4.2 Patent Analysis

A group of researchers focused on the value of patenting. Ernst et al. [31] explored the value of patent protection. Chen and Chang [32] correlated patent quality to the market value of a firm.

One major stream of researchers used patent analysis for technological planning and forecasting. Lee et al. [33] used patent analysis for technology roadmapping. Li [34] also used patent analysis for the same purpose. Choi et al. [35] integrated patent analysis into cross impact analysis to estimate the technological impact of information and communication technologies. Lee at al [36] used patent analysis to develop technology maps to identify opportunities for new technological innovations. Pilkington [37] introduced a statistically driven patent-based method to predict technology diffusion.

A group of researchers focused on evaluating the history of the technology development. Ma et al. [38] explored China’s technological capability and the level of its international collaboration using patent analysis. Ma and Lee [39] repeated a similar analysis for South Korea and Taiwan. Sun et al. [40] used a similar approach to explore the patterns in environmental technology innovations. Haustein and Neuwirth [41] used patent analysis to identify the long term trends which they called as long cycles. Lee et al. [42] used patent analysis with several other methods to identify the forced diffusion patterns of technological innovations in the automotive industry. Lo Storto [43] also explored technological innovation strategies this time in Europe using patent analysis. Hung and Tang [44] used patent analysis to explore technology acquisition in the electronic industries of Japan, Korea and Taiwan. Tsuji [45] identified that Canon’s patent acquisition strategy effectively promotes their research and development (R&D). Abraham and Moitra [46] used patent analysis to explore patterns in technological innovations in India. Archibugi and Planta [47] also used patent analysis to explore trends in technological innovations. Hanel [48] explored technology flows with methods including patent analysis.

A related group focused on the network of patents. Choi and Park [49] used citation networks to identify the technology development paths. Chang et al. [50] used patent citations to explore technology diffusion.

Patent analysis will count number of patents (including application and approved patents) USTPO, EPO, and WIPO.

Figures 6, 7, 8, 9, 10 illustrate the number of patents (cumulative) for each wind turbine with X-axis represents the year and Y-axis represents number of cumulative patents.

Fig. 6
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Number of cumulative patents of jet engine wind turbine by year

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Fig. 7
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Number of cumulative patents of magnus wind turbine by year

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Fig. 8
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Number of cumulative patents of airborne wind turbine by year

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Fig. 9
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Number of cumulative patents of gearless wind turbine by year

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Fig. 10
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Number of cumulative patents of LIDAR wind turbine by year

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From the graphs presented, we can see that jet engine wind turbine, gearless wind turbine, Magnus wind turbine, airborne wind turbine and LIDAR wind turbine have been continuously increasing over time. The growth of the number of patents for those wind turbines show similar pattern which is slow and constant in the early 1960–1980s and increased significantly after 2000s.

From the patent analysis above, jet engine wind turbine has the most cumulative patents compare to the other wind turbines. Airborne wind turbine is number two in term of number of patents. Magnus, LIDAR and gearless wind turbine fall in the same range of number of cumulative patents. However, all of those wind turbines do not dominate significantly in term of number. From patent analysis, the progress and growth of each wind turbine is illustrated better than bibliometrics analysis. The activity and indicators of the growth of each wind turbine are not documented well in publications. From bibliometrics analysis, only the growth of jet engine wind turbine is shown in a comprehensive and continuing manner. Other wind turbines are presented quite weakly. Patent analysis has more comprehensive illustration of the development of each wind turbine. The graph show the increasing and continuity growth of each turbine. The shapes of these plots are similar to that of the s-shaped growth curve [24]. From the plot above we can see that all the wind turbines can still be improved over time and have not reached saturation point. It means that all of those wind turbines will stay in the market for some time until they reach saturation point.

4.3 Growth Curve

Since all the wind turbines show the similar pattern in growth from the cumulative patent counts, this paper is going to conduct growth curve of each wind turbine to find the contender that have the most promising application. In order to do that, we are going to plot the number of cumulative patents into pearl curve formula to generate S-Curve. From the historical data, the formula will find S-curve that fit the cumulative patent counts. Bootstrap analysis was also performed to find the forecast area for each of wind turbine. Bootstrap analysis will create pseudo-replicate datasets by randomly re-sampling the original data [51]. Bootstrap analysis will give us information about the confidence interval for the forecasting of the wind turbines. This paper utilizes loglet lab software to help computing the re-sampling of the original data set. The results will be shown in Figures 11, 12, 13, 14, 15 along with the S-curve for each wind turbine.

Fig. 11
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Jet engine wind turbine growth curve

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Fig. 12
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Gearless wind turbine growth curve

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Fig. 13
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Airborne wind turbine growth curve

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Fig. 14
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Magnus wind turbine growth curve

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Fig. 15
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LIDAR wind turbine growth curve

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From the graph above, we can see that Jet Engine Wind Turbine is in the early maturity stage. The midpoint for jet engine wind turbine was in 2009. Jet Engine is predicted will reach the saturation point around 2032. Gearless wind turbine, LIDAR wind turbine and Magnus wind turbine are at the same stage. Those wind turbines almost reach the maturity stage with the midpoint in 2016 and reach the saturation point in 2038. It makes sense since the pattern of cumulative patents for those wind turbines are pretty similar. Airborne wind turbine is currently in the very end of growth stage and going to be in maturity stage with midpoint in 2011 and saturation point in 2032. The growth time of jet engine wind turbine, gearless wind turbine, airborne wind turbine, magnus wind turbine and LIDAR wind turbine are 46.42, 36.31, 42.22, 36.31, and 35.74 respectively.

4.4 Current Status of Wind Turbine in the Market

After the forecasting method being applied to all the wind turbines, this sub section is going to find the current status of the wind turbine technology in the Market. There are several companies that are currently developing airborne wind turbine, e.g. Magenn Power, Makani Power and Joby Energy [K41] [K42] [K43]. All of those companies are still in prototype test phase and hope can go into production in the end of 2011. FloDesign is the one that is well-known in developing Jet Engine Wind Turbine. FloDesign is also in prototype phase as of 2010 [K44]. Siemens, Honeywell, GE and AWE are known in their contribution to produce Gearless Wind Turbine [K45] [K46] [K47] [K48]. Currently, Gearless wind turbines are being tested in the field. The mass production should begin as early as 2012. Mecaro is one of many companies that currently focus on Magnus Wind Turbine. Prototype of Magnus Wind Turbine was exhibited at the Philippine 1st Energy Efficiency Forum in 2010 [K49].

All the real life applications are consistent with the growth curve for each wind turbine. The current state (2010) of each wind turbine in the growth curve reflects what is currently happening in the market. The product is usually developed once the technology is close to maturity. Without any significant development of the technology, companies usually reluctant to develop to product because companies do not want to waste resources to develop a product that utilizes technology that will never develop. For the illustration, please see Figure 16.

Fig. 16
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Illustration of product development that follow technology development

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As for LIDAR Wind Turbine, after more research being done, we discovered that LIDAR is not wind turbine that actually produce electricity like other four wind turbines. LIDAR is just a technology that can be embedded in any kind of wind turbine to help wind turbine produce energy more efficiently.

Table 2 below summarizes the current state of the wind turbine technology with the product development in the market.

Table 2 Summary of wind turbine products in the market according to wind turbine technology
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5 Conclusion

With the issue of global warming and instability and scarcity of fossil fuels, renewable energy seems to be one promising solution. It is undeniable that wind energy is gaining more attention in the last decade. Wind turbines were developed to produce energy from natural wind power.

This paper builds upon the earlier work published in use of patents [67] and assessment of wind energy [68]. This paper identified 5 emerging technologies in wind turbine, e.g. Jet Engine Wind Turbine, Gearless Wind Turbine, Magnus Wind Turbine, Airborne Wind Turbine and LIDAR Wind Turbine. Technology forecasting methods were applied to find which wind turbine is the contender among others.

Patents data are more comprehensive than publication data. The publication analysis did not give a clear insight of which wind turbine is leading because of limitation of data availability. From patent analysis, the shapes of each wind turbine plot are similar to that of the s-shaped growth curve. The results of growth curve show that jet engine wind turbines are currently in early maturity stage. Meanwhile, gearless wind turbines, LIDAR wind turbines and Magnus wind turbines are at the end of growth curve. Airborne wind turbines are currently in the very end of growth curve and almost move to maturity stage.

Additional research is performed to find the real life application of those wind turbines. All of those wind turbines are not currently being mass produced. Those wind turbines are in prototype phase or field test. The applications of the wind turbines in the market show consistency with the forecasting results. The findings suggest that all of those wind turbines are expected to be produced started in 2011 or 2012 and implemented widely around 2014–2016 which also show the consistency of the growth curves being presented.