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=Technology Roadmap Sections and Deliverables=
=Technology Roadmap Sections and Deliverables=


The first point is that each technology roadmap should have a clear and unique identifier:
Team 3 is to present a "level 2” roadmap of Wind Turbine Generators.
* '''2SEA - Solar Electric Aircraft'''
The following code is the identifier.
This indicates that we are dealing with a “level 2” roadmap at the product level (see Fig. 8-5), where “level 1” would indicate a market level roadmap and “level 3” or “level 4” would indicate an individual technology roadmap.
 
* '''2WTG - Wind Turbine Generator'''
 


==Roadmap Overview==
==Roadmap Overview==
[[File:Turbine block art.jpg|800px]]
Wind turbines are used to harvest kinetic energy from the wind and transform that energy into electricity. A rotor, typically with three airfoil blades, rotates using the force of lift. A system of gears is used to transfer the rotational energy of the hub to a high-speed shaft which feeds into a generator. The generator then utilizes the rotational energy to generate electricity and deliver it down the tower through a cable. An anemometer and weather vane are used to determine the wind speed and direction. The data that is collected is processed in the control box, which then adjusts the pitch of the blades and yaw of the nacelle for optimal operating conditions. Wind turbines can be assembled on land or water and usually generate energy proportional to their sweep area.


The working principle and architecture of solar-electric aircraft is depicted in the below.
==Design Structure Matrix (DSM) Allocation==


[[File:Section 1.JPG]]
[[File:DSM Figure for xlp.jpg|800px]]


Solar-electric aircraft are built from light-weight materials such as wood or carbon-fiber reinforced polymers (CFRP) and harvest solar energy through the photoelectric effect by bonding thin film solar cells to the surface of the main wings, and potentially the fuselage and empennage as well. The electrical energy harvested during the day is then stored in on-board chemical batteries (e.g. Lithium-Ion, Lithium-Sulfur etc…) and used for propelling the aircraft at all times, including at night. For the system to work there needs to be an overproduction of energy during the day, so that the aircraft can use the stored energy to stay aloft at night. The flight altitude of about 60,000-70,000 feet is critical to stay above the clouds and not to interfere with commercial air traffic. Depending on the length of day, i.e. the diurnal cycle which determines the number of sunshine hours per day, which itself depends on the latitude and time-of-year (seasonality) the problem is easier or harder. The reference case in the technology roadmap is an equatorial mission (latitude = zero) with 12 hours of day and 12 hours of night.
The 2-WTB tree in the upper right corner displays some of the key components of a wind turbine (2WTB), that when individually improved, enhance the overall performance and figures of merit of the wind turbine. The wind turbine can be broken down into its three main portions: a tower (3TWR), a nacelle (3NCL) and a rotor (3ROT). The three main wind turbine parts stand on the shoulders of other technologies, which if removed or damaged, can significantly affect the wind turbine. The tree can then be expanded into a more complex matrix that shows how most of its components are interconnected. Many of the parts are connected physically, some transfer energy, and others share information. The tree also exposes the purpose of the wind turbine itself, which is to aid in overall electricity generation or electrification (1ELE). Wind turbines can be combined into wind farms which together can replace a carbon releasing power plant.


==Design Structure Matrix (DSM) Allocation==
==Roadmap Model using OPM==
Team 3 hereby displays OPD of 2WTG - Wind Turbine Generator (WPG)
This consists of level 2 decomposed WTG, associated products and figure of merit (FOM).
Associated OPL is displayed below. This represents the relationships among each object shown in the OPM above.[[File:Opl111.png|thumb|Object Process Language]]
[[File:Opd111.png|1000px]]


==Figures of Merit==
The table below is to show a list of FOMs of 2WTG.


[[File:Expanded DSN.png|center]]
[[File:Windfoms101.png|1000px]]


(Describe the DSN tree and interconnected roadmaps here)
The unit cost, and capacity per wind turbine are both extremely important figures of merit. When looking into what wind turbine to buy, these would influence which brand and model should be purchased. While one wind turbine may be significantly cheaper than another, the capacity of a more expensive turbine might be much greater. It is also important to consider the availability of the turbine. This is essentially average hours of operation due to unfavorable wind conditions. There is a range of wind speeds any turbine can operate at, from the cut in wind speed at the lower end of the range, to the maximum safe operating speed at the high end. The region in which a wind turbine is assembled affects the availability of the turbine, but by expanding the operational wind speeds, the availability can be increased.


==Roadmap Model using OPM==
Furthermore, a couple of detail FOM with related formula and relationship is shown in the table below.
We provide an Object-Process-Diagram (OPD)  of the 2SEA roadmap in the figure below. This diagram captures the main object of the roadmap (Solar-Electric Aircraft), its various instances including main competitors, its decomposition into subsystems (wing, battery, e-motor …), its characterization by Figures of Merit (FOMs) as well as the main processes (Flying, Recharging).


[[File:Section 3.JPG]]
[[File:Fomwind102.png|1000px]]


An Object-Process-Language (OPL) description of the roadmap scope is auto-generated and given below. It reflects the same content as the previous figure, but in a formal natural language.
==Alignment with Company Strategic Drivers==


[[File:Section 3_2.JPG]]
Our company acts as a wind farm developing contractor who seeks to propose to the government or power distributors exploring cost-efficient wind farm developments. The Figure of Merit (FOM) that directly represents the price of unit energy production - and, thus, represents the highest return on investment - is Levelized Cost of Energy (LCOE). The reduction of this figure means that the product can produce energy at a cheaper overall price.


==Figures of Merit==
[[File:lcoe_power03.png|1200px]]
The table below show a list of FOMs by which solar electric aircraft can be assessed. The first four (shown in bold) are used to assess the aircraft itself. They are very similar to the FOMs that are used to compare traditional aircraft which are propelled by fossil fuels, the big difference being that 2SEA is essentially emissions free during flight operations. The other rows represent subordinated FOMs which impact the performance and cost of solar electric aircraft but are provided as outputs (primary FOMs) from lower level roadmaps at level 3 or level 4, see the DSM above.


[[File:Section 4_.JPG]]
https://data.nrel.gov/submissions/115


Besides defining what the FOMs are, this section of the roadmap should also contain the FOM trends over time dFOM/dt as well as some of the key governing equations that underpin the technology. These governing equations can be derived from physics (or chemistry, biology ..) or they can be empirically derived from a multivariate regression model. The table below shows an example of a key governing equation governing (solar-) electric aircraft.
The reduction of LCOE is the everlasting goal for all power generation technologies. Today, wind power generation technology is in a relatively competitive position among other types of power generation. However, wind energy still does not explicitly represent an economic advantage over others/ Offshore wind power technology needs drastic improvement to thrive in the market.
To make wind power a more beneficial source of energy, all stakeholders including turbine makers, main contractors, and wind farm owners must corporate and scrum together to develop the overall better technologies to achieve lower LCOE.
To achieve lower LCOE, what most effective route is to reduce CAPEX and OPEX as well as increase Capacity Factor.
Each of the factors listed above is impacted by multiple elements that compose wind farms.


[[File:Section 4_2.JPG]]


==Alignment with Company Strategic Drivers==
{| class="wikitable"
The table below shows an example of potential strategic drivers and alignment of the 2SEA technology roadmap with it.
|-
! Strategic Driver !! Alignment and Target
|-
| To keep competitive position in all other power generation stakeholders, off-shore wind sector needs to reduce its LCOE to be 50 [$/MWh] for offshore fixed plant and 80 [$/MWh] for offshore floating plant by year 2030.
|To achieve the designated LCOE targets on the left, following targets in each respective factors are required to be achieved by year 2030.


[[File:Section 5.JPG]]
For off-shore (fixed) wind plants, CAPEX to be 2000 [$/kW], OPEX to be 60 [$/kW/year], Cf to be 50%.


The list of drivers shows that the company views HAPS as a potential new business and wants to develop it as a commercially viable (for profit) business (1). In order to do so, the technology roadmap performs some analysis - using the governing equations in the previous section - and formulates a set of FOM targets that state that such a UAV needs to achieve an endurance of 500 days (as opposed to the world record 26 days that was demonstrated in 2018) and should be able to carry a payload of 10 kg. The roadmap confirms that it is aligned with this driver. This means that the analysis, technology targets, and R&D projects contained in the roadmap (and hopefully funded by the R&D budget) support the strategic ambition stated by driver 1. The second driver, however, which is to use the HAPS program as a platform for developing an autonomy stack for both UAVs and satellites, is not currently aligned with the roadmap.
For off-shore (floating) wind plants. CAPEX to be 3000 [$/kW], OPEX to be 50 [$/kW/year], Cf to be 50%.  
|}


==Positioning of Company vs. Competition==
==Positioning of Company vs. Competition==
The figure below shows a summary of other electric and solar-electric aircraft from public data.
The Horns Rev 3 farm currently has the best CAPEX where as the Wikinger has the highest CAPEX.
Race Bank has a high capacity factor with 60% and closely followed by Arkona  and Wikinger .
The Pareto Front (See next section under technical model)shows the best tradeoff between CAPEX ($/KW) and Capacity Factor (CF) for actual wind farm companies. In new projects in 2018 and 2019, Norther Offshore Wind and Rentel wind farms are on the pareto front with Norther Offshore Wind competing strongly for a lower CAPEX and Rental doing better in the Capacity Factor.  


[[File:Section 6.JPG]]
[[File:XLP2.JPG|1200px]]


The aerobatic aircraft Extra 330LE by Siemens currently has the world record for the most powerful flight certified electric motor (260kW). The Pipistrel Alpha Electro is a small electric training aircraft which is not solar powered, but is in serial production. The Zephyr 7 is the previous version of Zephyr which established the prior endurance world record for solar-electric aircraft (14 days) in 2010. The Solar Impulse 2 was a single-piloted solar-powered aircraft that circumnavigated the globe in 2015-2016 in 17 stages, the longest being the one from Japan to Hawaii (118 hours).
==Technical Model==


SolarEagle  and Solara 50 were both very ambitious projects that aimed to launch solar-electric aircraft with very aggressive targets (endurace up to 5 years) and payloads up to 450 kg. Both of these projects were canceled prematurely. Why is that?
To make the most cost-effective wind farm with the highest return on investment (ROI), LCOE is the key value to be pursued.


[[File:Section 6_2.JPG]]
It is important to note that CAPEX and Capacity Factor are the 2 major factors in which LCOE is sensitive.


The Pareto Front (see Chapter 5, Figure 5-20 for a definition) shown in black in the lower left corner of the graph shows the best tradeoff between endurance and payload for actually achieved electric flights by 2017. The Airbus Zephyr, Solar Impulse 2 and Pipistrel Alpha Electro all have flight records that anchor their position on this FOM chart. It is interesting to note that Solar Impulse 2 overheated its battery pack during its longest leg in 2015-2016 and therefore pushed the limits of battery technology available at that time.  We can now see that both Solar Eagle in the upper right and Solara 50 were chasing FOM targets that were unachievable with the technology available at that time. The progression of the Pareto front shown in red corresponds to what might be a realistic Pareto Front progression by 2020. Airbus Zephyr Next Generation (NG) has already shown with its world record (624 hours endurance) that the upper left target (low payload mass - about 5-10 kg and high endurance of 600+ hours) is feasible. There are currently no plans for a Solar Impulse 3,  which could be a non-stop solar-electric circumnavigation with one pilot (and an autonomous co-pilot) which would require a non-stop flight of about 450 hours. A next generation E-Fan aircraft with an endurance of about 2.5 hours (all electric) also seems within reach for 2020. Then in green we set a potentially more ambitious target Pareto Front for 2030. This is the ambition of the 2SEA technology roadmap as expressed by strategic driver 1. We see that in the upper left the Solara 50 project which was started by Titan Aerospace, then acquired by Google, then cancelled, and which ran from about 2013-2017 had the right targets for about a 2030 Entry-into-Service (EIS), not for 2020 or sooner. The target set by Solar Eagle was even more utopian and may not be achievable before 2050 according to the 2SEA roadmap.
The sensitivity study by the usage of the partial derivative method resulted in a tornado chart shown below.


==Technical Model==
[[File:tornadowind001.png]]
In order to assess the feasibility of technical (and financial) targets at the level of the 2SEA roadmap it is necessary to develop a technical model. The purpose of such a model is to explore the design tradespace and establish what are the active constraints in the system. The first step can be to establish a morphological matrix that shows the main technology selection alternatives that exist at the first level of decomposition, see the figure below.
 
This shows that the LCOE sensitivity against CF = 1.0, LCOE sensitivity against CAPEX = 0.7 to 0.84.
 
 
 
{| class="wikitable"
|-
! Note !! How it looks !! LCOE [$/MWh] of 2019 !! Information Source !! LCOE Reduction Trend
|-
| Airborne WTG
| <ref>https://www.greentechmedia.com/articles/read/a-beginners-guide-to-the-airborne-wind-turbine-market</ref> [[File:Airborne101.png|200px]]
| <font size="20">183</font>
| <ref>https://ore.catapult.org.uk/analysisinsight/an-introduction-to-airborne-wind/</ref>
|[[File:Airborntrend101.png|200px]]
|-
| Off-shore WTG (Floating)
| <ref>https://windeurope.org/newsroom/news/learn-about-floating-wind-energy-and-tenders/</ref> [[File:Float101.png|200px]]
| <font size="20">149</font>
| <ref>https://www.energy.gov/sites/prod/files/2019/08/f65/2018%20Offshore%20Wind%20Market%20Report.pdf</ref>
|[[File:Floattrend102.png|200px]]
|-
| Off-shore WTG (Fixed)
| <ref>https://www.researchgate.net/figure/a-Fixed-Offshore-Wind-Turbines-b-Floating-Offshore-Wind-Turbines-Wiser-R-et-al_fig3_265795516</ref> [[File:Fixed102.png|200px]]
| <font size="20">124</font>
| <ref>https://www.energy.gov/sites/prod/files/2019/08/f65/2018%20Offshore%20Wind%20Market%20Report.pdf</ref>
|[[File:Fixedtrend101.png|200px]]
|-
| On-shore (Land-based) WTG
| <ref>https://www.incore-cables.com/wind-turbine-cables/</ref> [[File:Land101.png|200px]]
| <font size="20">52</font>
| <ref>https://www.nrel.gov/docs/fy18osti/72167.pdf</ref>
| [[File:Landtrend101.png|200px]]
|-
| Bladeless WTG
| <ref>https://vortexbladeless.com/cost-effectiveness-analysis-bladeless/</ref> [[File:Bladeless101.png|200px]]
| <font size="20">35</font>
Note: This figure is not verified by third party
| <ref>https://www.powerelectronics.com/blog/wind-turbine-without-blades</ref>
| Future projection not available
|}
 
 
The Tradespace study for '''Off-shore (Fixed) Wind Farms''' is commenced as follows.
It is interesting to see that CAPEX and CF have not been drastically improved from 2005 to 2017.
Technical reasons are referred to in "NREL (2015): 2014-2015 Offshore Wind Technologies Market Report" as follows.
 
Quote ----
 
- Increasing technical difficulties of installing turbines in deeper water, farther from shore, and in more demanding met-ocean conditions (e.g., wind speeds, wave heights, and currents), which pose challenges for both technical design and construction
 
- Shortages in the supply chain (e.g., components, vessels, and skilled labor)
 
Unquote ----
 
 
[[File:tradespacewind001.png]]
 
To optimize LCOE,
there are many options to choose in designing wind-farms. 
The following table shows the options that we are going to focus on for design optimization.
 
[[File:Morf101.png]]
 
After a certain level of research we made, we came to understand the potential impact that CAPEX and OPEX have for reduction of LCOE exceed that Capacity Factor due to following reason.
 
The sensitivity of the Capacity Factor (CF) is certainly higher than that of CAPEX, however, the potential of improvement value is higher in CAPEX and OPEX, thus, the overall potential to provide a larger positive impact on LCOE could be said as CAPEX and OPEX rather than CF.
 
<Caluculation basis of the Reason>
 
The technology to improve Capacity Factor (CF) has been brushed up over time by many wind turbine makers all over the world until Today, spending millions of money.
However, as is shown in the current R&D list shown in clause "1.9 List of R&T Projects and Prototypes" below, the range that CF could possibly be improved is very limited- such as 2.5 to 5.5 [%].
Whereas the range of potential reduction of CAPEX and OPEX is as high as CAPEX -> 63 to 80 [%], OPEX -> 58 [%].
 
The result of the sensitivity study which we have made in this clause tells us that, the sensitivity of CF -> 1.0, the sensitivity of CAPEX -> 0.7 to 0.84, OPEX -> 0.16 to 0.32.
 
The combination of the potentials to reduce CAPEX and OPEX and the sensitivity of each category tells us the potential impact that each parameter could make to LCOE are as follows.
 
The potential impact of CF to LCOE = 2.5 to 5.5 %
 
The potential impact of CAPEX to LCOE = 44.1 to 67.2 %
 
The potential impact of OPEX to LCOE = 9.3 to 18.6 %
 
 
'''Considering the limited R&D resources, among the listed R&D projects in "1.9 List of R&T Projects and Prototypes" below, we are only able to focus on several top impactful items.'''
 
'''Improvement of CF is already at close to the moot point and the space for improvement is limited.'''
 
'''Since CAPEX and OPEX improvement are the fields havened been top focused, and we see larger potential space to be improved in there.'''
 
 
There are various considerations we can make to reduce CAPEX as in the table below.
 
[[File:Pfactor101.png|700px]]
 
[[File:Capex111.png|500px]]


[[File:Section 7_.JPG]]
As you can see from this picture, the 10MW wind turbine is 7 times heavier while the capacity is only 4 times of that of 2.5MW wind turbine.


It is interesting to note that the architecture and technology selections for the three aircraft (Zephyr, Solar Impulse 2 and E-Fan 2.0) are quite different. While Zephyr uses lithium-sulfur batteries, the other two use the more conventional lithium-ion batteries. Solar Impulse uses the less efficient (but more affordable) single cell silicon-based PV, while Zephyr uses specially manufactured thin film multi-junction cells and so forth.
This simply means the construction of 10MW will likely cost 7 times that of 2.5MW's.  


The technical model centers on the E-range and E-endurance equations and compares different aircraft sizing (e.g. wing span, engine power, battery capacity) taking into account aerodynamics, weights and balance, the performance of the aircraft and also its manufacturing cost. It is important to use Multidisciplinary Design Optimization (MDO) when selecting and sizing technologies in order to get the most out of them and compare them fairly (see below).
If the difficulty caused by its vertical height be considered, the price becomes even higher.


[[File:Section 7_2.JPG]]
This means the levelized CAPEX of 10MW turbine is likely more than that of 2.5MW. So the theory of "larger the cheaper" would not likely be true in this case.


==Financial Model==
==Financial Model==
The figure below contains a sample NPV analysis underlying the 2SEA roadmap. It shows the non-recurring cost (NRC) of the product development project (PDP), which includes the R&D expenditures as negative numbers. A ramp up-period of  4 years is planned with a flat revenue plateau (of 400 million per year) and a total program duration of 24 years.


[[File:Section 8.JPG]]
Considering currently reported worldwide investment plan for the wind turbines, ROI study based on NPV assuming discount rate as 12% per year has been made as follows.
 
The total worldwide investment plan for R&D in the wind power sector is $36.9 billion until 2028.
<ref>https://www.windpowerengineering.com/wind-rd-spending-to-top-36-9-billion-by-2028/</ref>
 
 
By that, the targeted reduction on LCOE by 2030 is 20 [$/MWh] for onshore (land-based) wind power and 70 [$/MWh] for offshore wind power.
At 2017, the worldwide offshore wind farm capacity is 18.8 GW <ref>https://www.energy.gov/eere/wind/downloads/2017-offshore-wind-technologies-market-update</ref>
while the onshore (land-based) wind farm capacity is 495.7 GW. <ref>https://www-statista-com.ezproxyberklee.flo.org/statistics/476306/global-capacity-of-onshore-wind-energy/</ref>
This means the offshore ratio is only 3.6% of the total wind capacity.
 
On the other hand, the ratio of the offshore wind turbine is expected to be increased to 31% of the total wind power generation by 2030.
<ref>https://www.ewea.org/fileadmin/files/library/publications/reports/EWEA-Wind-energy-scenarios-2030.pdf</ref>
 
This makes the targeted average LCOE reduction on both onshore and offshore wind farm as calculated to be 35.7 [$/MWh] by 2030.
 
At the same time, the total wind farm capacity in 2030 is expected to reach 2.1 [TW] (produces 5546 [TWh/year]) in the most aggressive scenario,
and 1.26 [TW] (produces 3311 [TWh/year]) in the most pessimistic scenario.
<ref>https://newenergyupdate.com/wind-energy-update/global-wind-could-hit-21-tw-2030-germany-pilots-wind-plus-pumped-hydro</ref>
 
The following ROI calculation has been commenced based on the most pessimistic scenario above (the orange graph), however, the benefit highly exceeds the investment cost.
 
Setting:
 
Year: 2030
 
Global Wind Power Production: 3300 [TWh/year] (Pessimistic Plan), 5546 [TWh/year] (Aggressive Plan)
 
Assumed reduction of LCOE in average of Off-shore and On-shore: 30 [$/MWh]
 
[[File:Financial101.png]]
 
As for the work split among consisting stakeholders are as shown in the following table.
 
 
[[File:Worksplit111.png]]
 
Survey link here:
http://bit.ly/2P9Qg5I


==List of R&T Projects and Prototypes==
==List of R&T Projects and Prototypes==
In order to select and prioritize R&D (R&T) projects we recommend using the technical and financial models developed as part of the roadmap to rank-order projects based on an objective set of criteria and analysis. The figure below illustrates how technical models are used to make technology project selections, e.g based on the previously stated 2030 target performance and Figure 8-17 (see the Chapter 8 of the text) shows the outcome if none of the three potential projects are selected.


[[File:Section 9.JPG]]
There are several studies analyzed effective targets to improve FOMs.
However many of these studies are not effectively well funded and focused.
Several reports in academic journals focus on the improvement of Capacity Factor which is expected to have only less than 10% impact on the FOM.
<ref>https://www.wind-energ-sci.net/3/489/2018/</ref>
<ref>https://www.researchgate.net/publication/330415378_A_Study_of_the_Impact_of_Pitch_Misalignment_on_Wind_Turbine_Performance</ref>
 
Whereas, there is no specific R&D report which contributes to explore the way to reduce CAPEX and OPEX that potentially provide up to 80% impact on FOM.
 
The following list is the R&D topic in which the wind power sector shall pay attention.
 
{| class="wikitable"
|-
! No !! Item !! Improved FOM !! Expected Improvement Ratio [%]
|-
| 1
| YAW system
| CF
| 2.5
|-
| 2
| Pitch system
| CF
| 5.5
|-
| 3
| Extension of design life by increased components durability
| FCR
| 36
|-
| 4
| Improved component durability and reliability
| OPEX
| 58
|-
| 5
| WTG, foundation and support structure design advancement, optimization
| CAPEX
| 80
|-
| 6
| WTG parts, foundation/support structure manufacturing standardization, increase constructability, producibility
| CAPEX
| 68
|-
| 7
| Installation and transportation equipment advancements
| CAPEX
| 63
|-
| 8
| Technology improvement and const reduction of subsea cable manufacturing and installation
| CAPEX
| 20
|}
 
Figures of impact are based on (Wiser (2017): FORECASTING WIND ENERGY COSTS & COST DRIVERS).
<ref>https://emp.lbl.gov/sites/all/files/lbnl-1005717.pdf</ref>
 
Following the currently projected improvement of CAPEX, OPEX, and CF,
our corporate target for floating wind farms, set to be achieved by 2030, is to be set as follows:
 
'''For Off-shore (Fixed) Wind Farm'''
 
'''CAPEX = 2000 [$/kW]'''
 
'''OPEX = 60 [$/kW/year]'''
 
'''CF = 50 [%]'''
 
'''For Off-shore (Floating) Wind Farm'''
 
'''CAPEX = 3000 [$/kW]'''
 
'''OPEX = 50 [$/kW/year]'''
 
'''CF = 50 [%]'''
 
 
 
[[File:windrd121.png|1300px]]
 
[[File:Windgantt101.png|900px]]


==Key Publications, Presentations and Patents==
==Key Publications, Presentations and Patents==
A good technology roadmap should contain a comprehensive list of publications, presentations and key patents as shown in Figure 8-19. This includes literature trends, papers published at key conferences and in the trade literature and trade press.
'''Publications:'''
 
 
<u>P. Veerset al.,Science10.1126/science.aau2027 (2019).: </u>
 
 
This publication in Science addresses the need for continued improvement of wind technology to compete for a larger market share in industrial electricity production. They call out three areas of improvement that would have a major impact. The first major area of focus is a deeper understanding of atmospheric flow regimes where plants operate. The second being engineering improvement of the world’s largest rotating dynamic structures (wind turbines), and the last being optimization of fleets of wind turbines that make up wind harvesting plants. Better understanding of these three fields are explained to have the most drastic effect on the industrial wind power industry.
 
 
<u>Stanley APJ, Ning A, Dykes K. Optimization of turbine design in wind farms with multiple hub heights, usingexact analytic gradients and structural constraints. Wind Energy. 2019;22:605–619. doi.org/10.1002/we.2310: </u>
 
The publication above pertains to improving wind farm efficiency by introducing multiple turbine hub heights. By spacing the turbines vertically in the z-plane as well as the x/y-plane, wake interference caused by an upstream turbine can be reduced for downstream turbines. The paper specifies that the data is representative of on-shore turbines but this data can most likely be translated to offshore wind farms as well. 
 
 
'''Patents:'''
 
[[File:Patent trends.png|center|Patent application trends over the past few decades]]
<div style="text-align: center;">Source: Lincoln, B., ''Taking the Temperature of Patent Trends in Wind Turbine Technology'', 21 September 2018<ref>https://www.potterclarkson.com/update/taking-the-temperature-of-patent-trends-in-wind-tu/</ref></div>
The figure above shows the rise in wind turbine related patent applications from 1994 through 2015. Around 2007 there is a dramatic rise in applications across many major enabling technologies related to wind technology. After the peak in 2011, there is a steady decline in applications. This may be evidence that wind technology is approaching the tail end of its S-Curve.
 
 
 
 
<u>Power Management for an Airborne Wind turbine:  </u>
 
[[File:Airborne Turbine.png|center|Airborne WInd Turbine]]
<div style="text-align: center;">Casey, L., & Dolan, G. (2019) US 10,422,320<ref>http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&f=G&l=50&co1=AND&d=PTXT&s1=10,422,320&OS=10,422,320&RS=10,422,320</ref></div>
 
The patent listed above deals with power management of an airborne wind turbine. Power management of the turbine is not as interesting as the airborne wind turbine itself. Based on a figure provided in the patent, the turbine looks more like a tethered airplane than a turbine. The patent has mention of the tether being the transmitting line between the airborne machine and a battery on the ground. It could also be used to power the machine for takeoff and landing. Airborne wind turbines are an interesting subject because they would be able to reach heights with more stable wind regimes. Having steady wind is a reason for offshore wind turbines, but looking to the sky may be a solution as well.
 
 
<u>Cable Routing for Wind Turbine System having Multiple Rotors: </u>


[[File:Section 10 1.JPG]]
[[File:Multi Rotor.png|center|Multi Rotor Concept]]
<div style="text-align: center;">Baun, T. L. (2019) US 10,428,789<ref>http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&f=G&l=50&co1=AND&d=PTXT&s1=10,428,789&OS=10,428,789&RS=10,428,789</ref></div>
 
This patent pertains to cable management of multi-rotor wind turbines. Again, while the topic of cable management does not spark too much interest, the idea of having an array of multiple rotors on one tower is interesting. The rotors are a relatively inexpensive part of the overall machine, and by having multiple rotors on one tower, CAPEX could potentially be reduced. Having multiple rotors could also increase the effective harvesting area per tower which may impact other figures of merit.
 
 
<u>Floating Offshore Structures: </u>
[[File:Offshore float.png|center|Offshore Float]]
<div style="text-align: center;">Bergua, R (2019) US 10,392,082<ref>http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&f=G&l=50&co1=AND&d=PTXT&s1=10,392,082&OS=10,392,082&RS=10,392,082</ref></div>
 
 
GE submitted this patent pertaining to offshore floating structures. There are a few different established methods of erecting larger, more powerful wind turbines. One method is floating the wind turbine. Companies are always looking to reduce CAPEX along with manufacturing/assembly costs and floating wind turbines are one method of reducing those costs. This specific patent is a method of securing the buoyant portion of the tower with an array of cables under tension. The system needs to adjust for different wind and wave conditions so the claims of this patent include an active adjustment system to account for these ever-changing forces. With patents like this one, subsystems can emerge to improve upon offshore technology.


==Technology Strategy Statement==
==Technology Strategy Statement==
A technology roadmap should conclude and be summarized by both a written statement that summarizes the technology strategy coming out of the roadmap as well as a graphic that shows the key R&D investments, targets and a vision for this technology (and associated product or service) over time. For the 2SEA roadmap the statement could read as follows:


'''Our target is to develop a new solar-powered and electrically-driven UAV as a HAPS service platform with an Entry-into-Service date of 2030. To achieve the target of an endurance of 500 days and useful payload of 10 kg we will invest in two R&D projects. The first is a flight demonstrator with a first flight by 2027 to demonstrate a full-year aloft (365 days) at an equatorial latitude with a payload of 10 kg. The second project is an accelerated development of Li-S batteries with our partner XYZ with a target lifetime performance of 500 charge-discharge cycles by 2027. This is an enabling technology to reach our 2030 technical and business targets.'''
As a result of above research, we conclude that the highest expected return on investment can be achieved by focusing on CAPEX and OPEX. And thus, all the R&D investment among this engineering sector ($36.8 billion) shall be spent on the red highlighted items in the following list - hereby call them as strategic drivers of our company. Other items listed in blackletters are out of our aligned strategic drivers.
{| class="wikitable"
|-
! No !! Item !! Improved FOM !! Expected Improvement Ratio [%]
|-
| 1
| YAW system
| CF
| 2.5
|-
| 2
| Pitch system
| CF
| 5.5
|-
| 3
| Extension of design life by increased components durability
| FCR
| 36
|-
| 4
| <font size="3" color="red">Improved component durability and reliability</font>
| <font size="3" color="red">OPEX</font>
| <font size="3" color="red">58</font>
|-
| 5
| <font size="3" color="red">WTG, foundation and support structure design advancement, optimization</font>
| <font size="3" color="red">CAPEX</font>
|<font size="3" color="red"> 80</font>
|-
| 6
| <font size="3" color="red">WTG parts, foundation/support structure manufacturing standardization, increase constructability, producibility</font>
| <font size="3" color="red">CAPEX</font>
| <font size="3" color="red">68</font>
|-
| 7
| <font size="3" color="red">Installation and transportation equipment advancements</font>
| <font size="3" color="red">CAPEX</font>
| <font size="3" color="red">63</font>
|-
| 8
| Technology improvement and const reduction of subsea cable manufacturing and installation
| CAPEX
| 20
|}
 
Today, since most engineers are not invested in the reduction of CAPEX/OPEX, our company shall take this opportunity in stride and dominate that sector.
 
'''The goal of this company is to develop a low cost, efficient wind turbine for wind farms that will compete with rival energy producers in the energy sector by 2030. This will be achieved with R&D investments in new materials, transportation, assembly and construction methods for offshore turbines to achieve a CAPEX and OPEX value of 2000 [$/kw] and 60 [$/kw/year] respectively for Off-shore (Fixed) wind farm, and 3000 [$/kw] and 50 [$/kw/year] respectively for Off-shore (Floating) wind farm. After better materials and construction methods are developed, they will be implemented in tandem with larger turbines which will increase CF by 50 [%] by the year 2030. '''
 
 
To realize this strategy, team collaboration among wind turbine makers, structure steel makers, transportation and marine contractors, and power distributors is inevitable.
[[File:Sweeping arrow model 2.jpg|center]]<ref>https://www.technologyreview.com/s/600881/wind-powers-next-hope-blades-as-long-as-two-football-fields/</ref><ref>https://www.lowtechmagazine.com/2019/06/wooden-wind-turbines.html</ref><ref>https://www.vox.com/energy-and-environment/2018/3/8/17084158/wind-turbine-power-energy-blades</ref>
 
==References==

Latest revision as of 21:42, 9 December 2019

Technology Roadmap Sections and Deliverables

Team 3 is to present a "level 2” roadmap of Wind Turbine Generators. The following code is the identifier.

  • 2WTG - Wind Turbine Generator


Roadmap Overview

Turbine block art.jpg

Wind turbines are used to harvest kinetic energy from the wind and transform that energy into electricity. A rotor, typically with three airfoil blades, rotates using the force of lift. A system of gears is used to transfer the rotational energy of the hub to a high-speed shaft which feeds into a generator. The generator then utilizes the rotational energy to generate electricity and deliver it down the tower through a cable. An anemometer and weather vane are used to determine the wind speed and direction. The data that is collected is processed in the control box, which then adjusts the pitch of the blades and yaw of the nacelle for optimal operating conditions. Wind turbines can be assembled on land or water and usually generate energy proportional to their sweep area.

Design Structure Matrix (DSM) Allocation

DSM Figure for xlp.jpg

The 2-WTB tree in the upper right corner displays some of the key components of a wind turbine (2WTB), that when individually improved, enhance the overall performance and figures of merit of the wind turbine. The wind turbine can be broken down into its three main portions: a tower (3TWR), a nacelle (3NCL) and a rotor (3ROT). The three main wind turbine parts stand on the shoulders of other technologies, which if removed or damaged, can significantly affect the wind turbine. The tree can then be expanded into a more complex matrix that shows how most of its components are interconnected. Many of the parts are connected physically, some transfer energy, and others share information. The tree also exposes the purpose of the wind turbine itself, which is to aid in overall electricity generation or electrification (1ELE). Wind turbines can be combined into wind farms which together can replace a carbon releasing power plant.

Roadmap Model using OPM

Team 3 hereby displays OPD of 2WTG - Wind Turbine Generator (WPG) This consists of level 2 decomposed WTG, associated products and figure of merit (FOM).

Associated OPL is displayed below. This represents the relationships among each object shown in the OPM above.

Object Process Language

Opd111.png

Figures of Merit

The table below is to show a list of FOMs of 2WTG.

Windfoms101.png

The unit cost, and capacity per wind turbine are both extremely important figures of merit. When looking into what wind turbine to buy, these would influence which brand and model should be purchased. While one wind turbine may be significantly cheaper than another, the capacity of a more expensive turbine might be much greater. It is also important to consider the availability of the turbine. This is essentially average hours of operation due to unfavorable wind conditions. There is a range of wind speeds any turbine can operate at, from the cut in wind speed at the lower end of the range, to the maximum safe operating speed at the high end. The region in which a wind turbine is assembled affects the availability of the turbine, but by expanding the operational wind speeds, the availability can be increased.

Furthermore, a couple of detail FOM with related formula and relationship is shown in the table below.

Fomwind102.png

Alignment with Company Strategic Drivers

Our company acts as a wind farm developing contractor who seeks to propose to the government or power distributors exploring cost-efficient wind farm developments. The Figure of Merit (FOM) that directly represents the price of unit energy production - and, thus, represents the highest return on investment - is Levelized Cost of Energy (LCOE). The reduction of this figure means that the product can produce energy at a cheaper overall price.

Lcoe power03.png

https://data.nrel.gov/submissions/115

The reduction of LCOE is the everlasting goal for all power generation technologies. Today, wind power generation technology is in a relatively competitive position among other types of power generation. However, wind energy still does not explicitly represent an economic advantage over others/ Offshore wind power technology needs drastic improvement to thrive in the market. To make wind power a more beneficial source of energy, all stakeholders including turbine makers, main contractors, and wind farm owners must corporate and scrum together to develop the overall better technologies to achieve lower LCOE. To achieve lower LCOE, what most effective route is to reduce CAPEX and OPEX as well as increase Capacity Factor. Each of the factors listed above is impacted by multiple elements that compose wind farms.


Strategic Driver Alignment and Target
To keep competitive position in all other power generation stakeholders, off-shore wind sector needs to reduce its LCOE to be 50 [$/MWh] for offshore fixed plant and 80 [$/MWh] for offshore floating plant by year 2030. To achieve the designated LCOE targets on the left, following targets in each respective factors are required to be achieved by year 2030.

For off-shore (fixed) wind plants, CAPEX to be 2000 [$/kW], OPEX to be 60 [$/kW/year], Cf to be 50%.

For off-shore (floating) wind plants. CAPEX to be 3000 [$/kW], OPEX to be 50 [$/kW/year], Cf to be 50%.

Positioning of Company vs. Competition

The Horns Rev 3 farm currently has the best CAPEX where as the Wikinger has the highest CAPEX. Race Bank has a high capacity factor with 60% and closely followed by Arkona and Wikinger . The Pareto Front (See next section under technical model)shows the best tradeoff between CAPEX ($/KW) and Capacity Factor (CF) for actual wind farm companies. In new projects in 2018 and 2019, Norther Offshore Wind and Rentel wind farms are on the pareto front with Norther Offshore Wind competing strongly for a lower CAPEX and Rental doing better in the Capacity Factor.

XLP2.JPG

Technical Model

To make the most cost-effective wind farm with the highest return on investment (ROI), LCOE is the key value to be pursued.

It is important to note that CAPEX and Capacity Factor are the 2 major factors in which LCOE is sensitive.

The sensitivity study by the usage of the partial derivative method resulted in a tornado chart shown below.

Tornadowind001.png

This shows that the LCOE sensitivity against CF = 1.0, LCOE sensitivity against CAPEX = 0.7 to 0.84.


Note How it looks LCOE [$/MWh] of 2019 Information Source LCOE Reduction Trend
Airborne WTG <ref>https://www.greentechmedia.com/articles/read/a-beginners-guide-to-the-airborne-wind-turbine-market</ref> Airborne101.png 183 <ref>https://ore.catapult.org.uk/analysisinsight/an-introduction-to-airborne-wind/</ref> Airborntrend101.png
Off-shore WTG (Floating) <ref>https://windeurope.org/newsroom/news/learn-about-floating-wind-energy-and-tenders/</ref> Float101.png 149 <ref>https://www.energy.gov/sites/prod/files/2019/08/f65/2018%20Offshore%20Wind%20Market%20Report.pdf</ref> Floattrend102.png
Off-shore WTG (Fixed) <ref>https://www.researchgate.net/figure/a-Fixed-Offshore-Wind-Turbines-b-Floating-Offshore-Wind-Turbines-Wiser-R-et-al_fig3_265795516</ref> Fixed102.png 124 <ref>https://www.energy.gov/sites/prod/files/2019/08/f65/2018%20Offshore%20Wind%20Market%20Report.pdf</ref> Fixedtrend101.png
On-shore (Land-based) WTG <ref>https://www.incore-cables.com/wind-turbine-cables/</ref> Land101.png 52 <ref>https://www.nrel.gov/docs/fy18osti/72167.pdf</ref> Landtrend101.png
Bladeless WTG <ref>https://vortexbladeless.com/cost-effectiveness-analysis-bladeless/</ref> Bladeless101.png 35

Note: This figure is not verified by third party

<ref>https://www.powerelectronics.com/blog/wind-turbine-without-blades</ref> Future projection not available


The Tradespace study for Off-shore (Fixed) Wind Farms is commenced as follows. It is interesting to see that CAPEX and CF have not been drastically improved from 2005 to 2017. Technical reasons are referred to in "NREL (2015): 2014-2015 Offshore Wind Technologies Market Report" as follows.

Quote ----

- Increasing technical difficulties of installing turbines in deeper water, farther from shore, and in more demanding met-ocean conditions (e.g., wind speeds, wave heights, and currents), which pose challenges for both technical design and construction

- Shortages in the supply chain (e.g., components, vessels, and skilled labor)

Unquote ----


Tradespacewind001.png

To optimize LCOE, there are many options to choose in designing wind-farms. The following table shows the options that we are going to focus on for design optimization.

Morf101.png

After a certain level of research we made, we came to understand the potential impact that CAPEX and OPEX have for reduction of LCOE exceed that Capacity Factor due to following reason.

The sensitivity of the Capacity Factor (CF) is certainly higher than that of CAPEX, however, the potential of improvement value is higher in CAPEX and OPEX, thus, the overall potential to provide a larger positive impact on LCOE could be said as CAPEX and OPEX rather than CF.

<Caluculation basis of the Reason>

The technology to improve Capacity Factor (CF) has been brushed up over time by many wind turbine makers all over the world until Today, spending millions of money. However, as is shown in the current R&D list shown in clause "1.9 List of R&T Projects and Prototypes" below, the range that CF could possibly be improved is very limited- such as 2.5 to 5.5 [%]. Whereas the range of potential reduction of CAPEX and OPEX is as high as CAPEX -> 63 to 80 [%], OPEX -> 58 [%].

The result of the sensitivity study which we have made in this clause tells us that, the sensitivity of CF -> 1.0, the sensitivity of CAPEX -> 0.7 to 0.84, OPEX -> 0.16 to 0.32.

The combination of the potentials to reduce CAPEX and OPEX and the sensitivity of each category tells us the potential impact that each parameter could make to LCOE are as follows.

The potential impact of CF to LCOE = 2.5 to 5.5 %

The potential impact of CAPEX to LCOE = 44.1 to 67.2 %

The potential impact of OPEX to LCOE = 9.3 to 18.6 %


Considering the limited R&D resources, among the listed R&D projects in "1.9 List of R&T Projects and Prototypes" below, we are only able to focus on several top impactful items.

Improvement of CF is already at close to the moot point and the space for improvement is limited.

Since CAPEX and OPEX improvement are the fields havened been top focused, and we see larger potential space to be improved in there.


There are various considerations we can make to reduce CAPEX as in the table below.

Pfactor101.png

Capex111.png

As you can see from this picture, the 10MW wind turbine is 7 times heavier while the capacity is only 4 times of that of 2.5MW wind turbine.

This simply means the construction of 10MW will likely cost 7 times that of 2.5MW's.

If the difficulty caused by its vertical height be considered, the price becomes even higher.

This means the levelized CAPEX of 10MW turbine is likely more than that of 2.5MW. So the theory of "larger the cheaper" would not likely be true in this case.

Financial Model

Considering currently reported worldwide investment plan for the wind turbines, ROI study based on NPV assuming discount rate as 12% per year has been made as follows.

The total worldwide investment plan for R&D in the wind power sector is $36.9 billion until 2028. <ref>https://www.windpowerengineering.com/wind-rd-spending-to-top-36-9-billion-by-2028/</ref>


By that, the targeted reduction on LCOE by 2030 is 20 [$/MWh] for onshore (land-based) wind power and 70 [$/MWh] for offshore wind power. At 2017, the worldwide offshore wind farm capacity is 18.8 GW <ref>https://www.energy.gov/eere/wind/downloads/2017-offshore-wind-technologies-market-update</ref> while the onshore (land-based) wind farm capacity is 495.7 GW. <ref>https://www-statista-com.ezproxyberklee.flo.org/statistics/476306/global-capacity-of-onshore-wind-energy/</ref> This means the offshore ratio is only 3.6% of the total wind capacity.

On the other hand, the ratio of the offshore wind turbine is expected to be increased to 31% of the total wind power generation by 2030. <ref>https://www.ewea.org/fileadmin/files/library/publications/reports/EWEA-Wind-energy-scenarios-2030.pdf</ref>

This makes the targeted average LCOE reduction on both onshore and offshore wind farm as calculated to be 35.7 [$/MWh] by 2030.

At the same time, the total wind farm capacity in 2030 is expected to reach 2.1 [TW] (produces 5546 [TWh/year]) in the most aggressive scenario, and 1.26 [TW] (produces 3311 [TWh/year]) in the most pessimistic scenario. <ref>https://newenergyupdate.com/wind-energy-update/global-wind-could-hit-21-tw-2030-germany-pilots-wind-plus-pumped-hydro</ref>

The following ROI calculation has been commenced based on the most pessimistic scenario above (the orange graph), however, the benefit highly exceeds the investment cost.

Setting:

Year: 2030

Global Wind Power Production: 3300 [TWh/year] (Pessimistic Plan), 5546 [TWh/year] (Aggressive Plan)

Assumed reduction of LCOE in average of Off-shore and On-shore: 30 [$/MWh]

Financial101.png

As for the work split among consisting stakeholders are as shown in the following table.


Worksplit111.png

Survey link here: http://bit.ly/2P9Qg5I

List of R&T Projects and Prototypes

There are several studies analyzed effective targets to improve FOMs. However many of these studies are not effectively well funded and focused. Several reports in academic journals focus on the improvement of Capacity Factor which is expected to have only less than 10% impact on the FOM. <ref>https://www.wind-energ-sci.net/3/489/2018/</ref> <ref>https://www.researchgate.net/publication/330415378_A_Study_of_the_Impact_of_Pitch_Misalignment_on_Wind_Turbine_Performance</ref>

Whereas, there is no specific R&D report which contributes to explore the way to reduce CAPEX and OPEX that potentially provide up to 80% impact on FOM.

The following list is the R&D topic in which the wind power sector shall pay attention.

No Item Improved FOM Expected Improvement Ratio [%]
1 YAW system CF 2.5
2 Pitch system CF 5.5
3 Extension of design life by increased components durability FCR 36
4 Improved component durability and reliability OPEX 58
5 WTG, foundation and support structure design advancement, optimization CAPEX 80
6 WTG parts, foundation/support structure manufacturing standardization, increase constructability, producibility CAPEX 68
7 Installation and transportation equipment advancements CAPEX 63
8 Technology improvement and const reduction of subsea cable manufacturing and installation CAPEX 20

Figures of impact are based on (Wiser (2017): FORECASTING WIND ENERGY COSTS & COST DRIVERS). <ref>https://emp.lbl.gov/sites/all/files/lbnl-1005717.pdf</ref>

Following the currently projected improvement of CAPEX, OPEX, and CF, our corporate target for floating wind farms, set to be achieved by 2030, is to be set as follows:

For Off-shore (Fixed) Wind Farm

CAPEX = 2000 [$/kW]

OPEX = 60 [$/kW/year]

CF = 50 [%]

For Off-shore (Floating) Wind Farm

CAPEX = 3000 [$/kW]

OPEX = 50 [$/kW/year]

CF = 50 [%]


Windrd121.png

Windgantt101.png

Key Publications, Presentations and Patents

Publications:


P. Veerset al.,Science10.1126/science.aau2027 (2019).:


This publication in Science addresses the need for continued improvement of wind technology to compete for a larger market share in industrial electricity production. They call out three areas of improvement that would have a major impact. The first major area of focus is a deeper understanding of atmospheric flow regimes where plants operate. The second being engineering improvement of the world’s largest rotating dynamic structures (wind turbines), and the last being optimization of fleets of wind turbines that make up wind harvesting plants. Better understanding of these three fields are explained to have the most drastic effect on the industrial wind power industry.


Stanley APJ, Ning A, Dykes K. Optimization of turbine design in wind farms with multiple hub heights, usingexact analytic gradients and structural constraints. Wind Energy. 2019;22:605–619. doi.org/10.1002/we.2310:


The publication above pertains to improving wind farm efficiency by introducing multiple turbine hub heights. By spacing the turbines vertically in the z-plane as well as the x/y-plane, wake interference caused by an upstream turbine can be reduced for downstream turbines. The paper specifies that the data is representative of on-shore turbines but this data can most likely be translated to offshore wind farms as well.


Patents:


Patent application trends over the past few decades
Source: Lincoln, B., Taking the Temperature of Patent Trends in Wind Turbine Technology, 21 September 2018<ref>https://www.potterclarkson.com/update/taking-the-temperature-of-patent-trends-in-wind-tu/</ref>

The figure above shows the rise in wind turbine related patent applications from 1994 through 2015. Around 2007 there is a dramatic rise in applications across many major enabling technologies related to wind technology. After the peak in 2011, there is a steady decline in applications. This may be evidence that wind technology is approaching the tail end of its S-Curve.



Power Management for an Airborne Wind turbine:

Airborne WInd Turbine
Casey, L., & Dolan, G. (2019) US 10,422,320<ref>http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&f=G&l=50&co1=AND&d=PTXT&s1=10,422,320&OS=10,422,320&RS=10,422,320</ref>

The patent listed above deals with power management of an airborne wind turbine. Power management of the turbine is not as interesting as the airborne wind turbine itself. Based on a figure provided in the patent, the turbine looks more like a tethered airplane than a turbine. The patent has mention of the tether being the transmitting line between the airborne machine and a battery on the ground. It could also be used to power the machine for takeoff and landing. Airborne wind turbines are an interesting subject because they would be able to reach heights with more stable wind regimes. Having steady wind is a reason for offshore wind turbines, but looking to the sky may be a solution as well.


Cable Routing for Wind Turbine System having Multiple Rotors:

Multi Rotor Concept
Baun, T. L. (2019) US 10,428,789<ref>http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&f=G&l=50&co1=AND&d=PTXT&s1=10,428,789&OS=10,428,789&RS=10,428,789</ref>

This patent pertains to cable management of multi-rotor wind turbines. Again, while the topic of cable management does not spark too much interest, the idea of having an array of multiple rotors on one tower is interesting. The rotors are a relatively inexpensive part of the overall machine, and by having multiple rotors on one tower, CAPEX could potentially be reduced. Having multiple rotors could also increase the effective harvesting area per tower which may impact other figures of merit.


Floating Offshore Structures:

Offshore Float
Bergua, R (2019) US 10,392,082<ref>http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=%2Fnetahtml%2FPTO%2Fsearch-bool.html&r=1&f=G&l=50&co1=AND&d=PTXT&s1=10,392,082&OS=10,392,082&RS=10,392,082</ref>


GE submitted this patent pertaining to offshore floating structures. There are a few different established methods of erecting larger, more powerful wind turbines. One method is floating the wind turbine. Companies are always looking to reduce CAPEX along with manufacturing/assembly costs and floating wind turbines are one method of reducing those costs. This specific patent is a method of securing the buoyant portion of the tower with an array of cables under tension. The system needs to adjust for different wind and wave conditions so the claims of this patent include an active adjustment system to account for these ever-changing forces. With patents like this one, subsystems can emerge to improve upon offshore technology.

Technology Strategy Statement

As a result of above research, we conclude that the highest expected return on investment can be achieved by focusing on CAPEX and OPEX. And thus, all the R&D investment among this engineering sector ($36.8 billion) shall be spent on the red highlighted items in the following list - hereby call them as strategic drivers of our company. Other items listed in blackletters are out of our aligned strategic drivers.

No Item Improved FOM Expected Improvement Ratio [%]
1 YAW system CF 2.5
2 Pitch system CF 5.5
3 Extension of design life by increased components durability FCR 36
4 Improved component durability and reliability OPEX 58
5 WTG, foundation and support structure design advancement, optimization CAPEX 80
6 WTG parts, foundation/support structure manufacturing standardization, increase constructability, producibility CAPEX 68
7 Installation and transportation equipment advancements CAPEX 63
8 Technology improvement and const reduction of subsea cable manufacturing and installation CAPEX 20

Today, since most engineers are not invested in the reduction of CAPEX/OPEX, our company shall take this opportunity in stride and dominate that sector.

The goal of this company is to develop a low cost, efficient wind turbine for wind farms that will compete with rival energy producers in the energy sector by 2030. This will be achieved with R&D investments in new materials, transportation, assembly and construction methods for offshore turbines to achieve a CAPEX and OPEX value of 2000 [$/kw] and 60 [$/kw/year] respectively for Off-shore (Fixed) wind farm, and 3000 [$/kw] and 50 [$/kw/year] respectively for Off-shore (Floating) wind farm. After better materials and construction methods are developed, they will be implemented in tandem with larger turbines which will increase CF by 50 [%] by the year 2030.


To realize this strategy, team collaboration among wind turbine makers, structure steel makers, transportation and marine contractors, and power distributors is inevitable.

Sweeping arrow model 2.jpg

<ref>https://www.technologyreview.com/s/600881/wind-powers-next-hope-blades-as-long-as-two-football-fields/</ref><ref>https://www.lowtechmagazine.com/2019/06/wooden-wind-turbines.html</ref><ref>https://www.vox.com/energy-and-environment/2018/3/8/17084158/wind-turbine-power-energy-blades</ref>

References

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