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Need help-Wind Turbine Investigation

Need help-Wind Turbine Investigation

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The following experiment enables you to:

  • Measure the energy in the wind.
  • Assess a commercially available wind turbine in an environmental wind tunnel.
  • Determine the power curve of a wind turbine and obtain cut-in speeds
  • Calculate the coefficient of performance of a turbine
  • Calculate the Solidity and Tip-speed ratio.
  • See how the energy is converted stored and utilised.
  • Examine the Beaufort wind scale.


The power available to a wind turbine is the kinetic energy passing per unit time in a column of air with the same cross sectional area A as the wind turbine rotor, travelling with a wind speed U0. Thus the available power is proportional to the cube of the wind speed. See the figure below.


The equipment is provided by Marlec and the following information is from their web page but has been modified slightly for this labsheet.

The Rutland 913 is designed for marine use on board coastal and ocean going yachts usually over 10m in length. This unit will generate enough power to serve both domestic and engine batteries on board.
The Rutland 913 is a popular sight in marinas, thousands are in use worldwide, boat owners like it’s clean, aerodynamic lines and its quiet and continuous operation. Without doubt this latest marine model accumulates more energy than any other comparable windcharger available, you’ll always see a Rutland spinning in the lightest of breezes!

  • Low wind speed start up of less than 3m/s
  • Generates 90w @ 37m/s, 24w @ 20 m/s
  • Delivers up to 250w
  • Modern, durable materials for reliability on the high seas
  • SR200 Regulator – Shunt type voltage regulator prevents battery overcharge


During this experiment you will make use of the following equations to calculate key parameters

Key formulae

Energy in the wind E = (watts)

Swept area of rotor A=πR2


Electrical power output P=VxI (watts)


Coefficient of performance


Tip speed ratio




Solidity = blade area/swept area


R is the rotor radius (m)

ρ is air density say 1.23 kg/m3

Uo is the wind speed (m/s)

V is voltage (volts)

I is current (amps)

ω (rads/sec) is the angular velocity of the rotor found from


 where N is the rotor speed in revs/min






Step 1         Ensure that everything is setup for you and switch on the tunnel.

Step 2         Adjust the wind speed and let it stabilize

Step 3         Measure the wind speed, voltage and current

Step 4         If available measure the rotor speed with the stroboscope.

Repeat steps 2 – 4 for other wind speeds up to a maximum of 10m/s if achievable.


Gather your data by completing tables 1 and 2


Wind speed

Uo  (m/s)



Effect on land Output voltage

V (volts)

Output current

I (amps)

Rotor speed

N (revs/min)

Table 1 measured data


Calculate the following

Rotor radius use a ruler to measure from center to tip of turbine R =
Swept area A=πR2


A =
Blade area = blade area + hub area

do your best!

Solidity = blade area / swept area.   =

Table 2 measured data




Now analyse your data by completing table 3.


Energy in the wind Electrical power Coefficient of performance Tip speed ratio
E =  (watts) P = V x I




(or column 2 /column 1)

Table 3 Analyse your data


Present your data:

Now present your results in graphical format to give you a better understanding of the data you have gathered and analysed.


Use excel and the x-y scatter chart for this.


Graph 1

Plot the values Uo (x-axis) against P (y1-axis) and E (y2-axis).


Graph 2

Plot the values of Uo (x-axis) against Cp (y-axis).


What conclusions do you draw?


How efficiently are you converting the kinetic energy in the wind into electrical energy that is stored chemically in the batteries?


Write up the laboratory formally and submit to turnitin. Please ensure presentation is clear and quote fully any references.



The Beaufort Wind Speed Scale

Wind Speed at 10m height Description Wind Turbine
Effect on
Effect at
0 0.0 -0.4 Calm None Smoke rises vertically Mirror smooth
1 0.4 -1.8 Light None Smoke drifts; vanes unaffected small ripples
2 1.8 -3.6 Light None Leaves move slightly Definite waves
3 3.6 -5.8 Light Small turbines start – e.g. for pumping Leaves in motion; Flags extend Occasional breaking crest
4 5.8 -8.5 Moderate Start up for electrical generation Small branches move Larger waves; White crests common
5 8.5 -11.0 Fresh Useful power Generation at 1/3 capacity Small trees sway Extensive white crests
6 11.0 -14.0 Strong Rated power range Large branches move Larger waves; foaming crests
7 14.0 -17.0 Strong Full capacity Trees in motion Foam breaks from crests
8 17.0 -21.0 Gale Shut down initiated Walking difficult Blown foam
9 21.0 -25.0 Gale All machines shut down Slight structural damage Extensive blown foam
10 25.0 -29.0 Strong gale Design criteria against damage Trees uprooted; much structural damage Large waves with long breaking crests
11 29.0 -34.0 Strong gale Widespread damage
12 >34.0 Hurricane Serious damage Disaster conditions Ships hidden in wave troughs

Supplementary Theory

The power available to a wind turbine is the kinetic energy passing per unit time in a column of air with the same cross sectional area A as the wind turbine rotor, travelling with a wind speed u0. Thus the available power is proportional to the cube of the wind speed.

We can see that the power achieved is highly dependent on the wind speed. Doubling the wind speed increases the power eightfold but doubling the turbine area only doubles the power. Thus optimising the siting of wind turbines in the highest wind speed areas has significant benefit and is critical for the best economic performance. Information on power production independently of the turbine characteristics is normally expressed as a flux, i.e. power per unit area or power density in W/m2. Thus assuming a standard atmosphere with density at 1.225kg/s :

Wind speed m/s     Power W/m squared               5.0                76.6              10.0               612.5              15.0              2067.2              20.0              4900.0              25.0              9570.3

The density of the air will also have an effect on the total power available. The air is generally less dense in warmer climates and also decreases with height. The air density can range from around 0.9 kg/m3 to 1.4kg/m3. This effect is very small in comparison to the variation of wind speed.


In practice all of the kinetic energy in the wind cannot be converted to shaft power since the air must be able to flow away from the rotor area. The Betz criterion, derived using the principles of conservation of momentum and conservation of energy gives a maximum possible turbine efficiency, or power coefficient, of 59%. In practise power coefficients of 20 – 30 % are common. The section on Aerodynamics discusses these matters in detail.


Most wind turbines are designed to generate maximum power at a fixed wind speed. This is known as Rated Power and the wind speed at which it is achieved the Rated Wind Speed. The rated wind speed chosen to fit the local site wind regime, and is often about 1.5 times the site mean wind speed.

The power produced by the wind turbine increases from zero, below the cut in wind speed, (usually around 5m/s but again varies with site) to the maximum at the rated wind speed. Above the rated wind speed the wind turbine continues to produce the same rated power but at lower efficiency until shut down is initiated if the wind speed becomes dangerously high, i.e. above 25 to 30m/s (gale force). This is the cut out wind speed. The exact specifications for designing the energy capture of a turbine depend on the distribution of wind speed over the year at the site.


Performance calculations


Power coefficient Cp is the ratio of the power extracted by the rotor to the power available in the wind.

It can be shown that the maximum possible value of the power coefficient is 0.593 which is referred to as the Betz limit.


Pe is the extracted power by the rotor (W)

V¥ is the free stream wind velocity (m/s)

A is area normal to wind         (m2)

ρ is density of the air              (kg/m3)



The tip speed ratio (l) is the ratio of the speed of the blade tip to the free stream wind speed.




w is the angular velocity of the rotor (rads/sec), and

R is the tip radius (m)


This relation holds for the horizontal axis machine which is the focus of these notes.


The solidity (g) is the ratio of the blade area to the swept frontal area (face area) of the machine


Blade area = number of blades * mean chord length * radius = N.c.R


Mean chord length is the average width of the blade facing the wind.


Swept frontal area is pR2

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 Need help-Wind Turbine Investigation

















CAM & Robotics Group Project:

CAM & Robotics Group Project:
Automating the Transportation of Beverage Pallets with the use of Automated Guided Vehicles
Maria Correa
Oyinbrakame Edogi
Angel Hernandez
Diego Luna
Our analysis was conducted in a beverage-packaging warehouse. In the current state of the warehouse, pallets of packaged beverages are moved using manual labor and manually operated forklifts. Our team researched the potential of replacing manual labor and forklifts through the means of vision-guided Automated Guided Vehicles (AGVs). The implementation of the AGVs will increase productivity by decreasing operation time and downtimes. Additionally, implementing AGVs in the material handling system of the warehouse will decrease overall cost through the reduction of product damage, labor cost, and facility damage. Further more, the use of an AGV will provide the warehouse with a more reliable and durable material handling system. Research was also conducted in the consideration of alternative ways for material handling.
Our project takes place in a medium sized bottling plant, consisting of 3 machines each producing 1,000 of 8 oz. cans per minute. For this analysis, we only investigated the material handling process of the throughput from 1 machine. At the end of every production line a machine’s operation is to pack beverages into 45” by 42” pallets, which contain an approximate 1,000 cans, each weighing 227 grams; each pallet weighs an approximately 500 pounds. The Uline Straddle Stacker forklift operators are paid $12.25 per hour, and the forklifts have an initial cost of $2,995. In this project, we focused on this particular transportation of finished goods, from the end of the production line to the inventory site. We conducted research in order to justify automating this process using automated guided vehicles (AGVs). AGVs are mobile robots that are navigated by magnets, wires, or lasers, and are used in industry to transport materials/products within a facility or production site. A Fork Truck AGV can handle 2000 lbs., which means in one trip it can carry 4 pallets.
As stated in the introduction, the current throughput of one machine is 1,000 cans every 8 minutes. These cans are then palletized into 500 lb. pallets. After cans have been palletized a forklift and operator are ready to transport the pallets to the storage section. The Uline Straddler forklift can accommodate a height of 135” with a maximum payload of 1760 lbs. This allows for 3 pallets per trip. The distance from the machine to storage is about 100 ft. It takes the operator about 8 minutes to travel to the storage section and back to the machine. The Uline Straddler Forklift can operate about 2 hrs. on a fully charged battery and takes approximately 8-12 hours to fully charge. Due to these constraints, 3 other Uline Straddler Forklifts are being charged while one forklift is operating. This allows the operator 8 non-stop hours of work within a day, including an hour break for lunch. This current process allows 60,000 cans or 60 pallets to be stored in any given 8-hour day.
Figure 1 – Plant layout
A Cost Benefit Analysis was conducted in order to evaluate the potential of integrating an AGV in the current process. 2 years, each year containing 260 working days, was the time frame of the Cost Benefit Analysis. We began by analyzing the current system with 1 production machine, 4 Uline Straddler forklifts, and 1 Operator.
Initial Costs
The cost of purchasing a single Uline Straddler forklift is $2,995 (Uline 2015). Thus, the cost of purchasing four forklifts is $2,995 x 4 (units) = $11,980.
Maintenance Cost
Research showed that the cost of maintenance for a forklift was one dollar per hour of operation (Cat Lift Trucks 2012). Thus, the total maintenance cost for two years, while operating four units, is computed as the following:
$1 x 2 (years) x 260 (working days) x 2 (a single unit would only operate 2 hours per day) x 4 (units) = $4,160.
Cost of Wages
An operator earns $12.25 per hour. The total cost of wages for a 2-year period and 1 operator was calculated as follows:
$12.25 x 1 (operator) x 2 (years) x 260 (working days) x 8 (working hours) = $50,960.
Total Cost
Taking all the costs into consideration, the total cost of operating four forklifts in the facility is calculated as follows:
$11,980 (initial cost) + $4,160 (maintenance cost) + $50,960 (cost of wages) = $67,100 for a 2-year period.
Production Rates
The current system enables the storage of 60 pallets for a single working day. If we consider this production rate over a 2-year period, then we calculated the following:
60 (pallets) x 2 (years) x 260 (working days) = 31,200 pallets.
Research shows that a beverage-can produced an average of $.45 revenue. Using the revenue per can, we calculated the revenue for a 2-year period production as following:
$.45 x 31,200 (pallets) x 1000 (cans per pallet) = $14,040,000.
Using the production rate, and revenue calculated previously, the total profit for the 2-year period is $14,040,000 – $67,100 = $13,972,900.
We found the current system to yield a profit of 14.0 million dollars, not including wages of other employees, overhead cost, facility cost etc. We then investigated the implementation of the Savant DC-10 in our current system. This would replace the existing 4 forklifts and not require an operator. The Savant DC-10 has a battery life of 8 hours, charging time of 8 hours, and a payload of 2,000 lbs. With an operator not necessary, we assumed to increase production 16-hrs day and the 8 hours the AGV would be charging.
Initial Costs
We assumed an average AGV to cost $100,000 (Davich 2010).
Maintenance Cost
We assumed an average AGV to have a maintenance cost of $25,000 per year (Davich 2010). Consequently, we calculated that for a 2-year period there would be a maintenance cost of $50,000.
Total Cost
Additionally, the total cost for the implementation and operation of an AGV was calculated as follows: $100,000 (Initial Costs) + $50,000 (Maintenance Cost) = $150,000.
Production Rates
By automating of the process, the new operating hours would increase to 16 hours and the payload for the AGV is 4 pallets. Since the machine produces 1 pallet every 8 minutes, the production rate per day was calculated as follows:
(16 (hours) x 60 (minutes) ) / 32 (minutes to generate 4 pallets) x 4 (pallets of payload) = 120 pallets in an operating day
Using the production rate calculated previous, the revenue for a 2-year period was calculated as follows:
120 (120 pallets) x 260 (days) x .45 (revenue per can) x 1000 (cans per pallet) x 2 (years) = $28,080,000/ 2 yrs.
Additionally, the total profit of automating the process was calculated to be $28,080,000 – $150,000 = $27,930,000 for a 2-year period.
By replacing 4 forklifts and 1 operator with a AGV, we found an increased profit of $13,958,000 for a 2-year period. This cost analysis, however, did not included the wages of other employees, overhead cost, facility cost etc.
In a research article by Prabir K. Pal (2011), two specific topics where discussed, which included briefly describing the current state of AGV’s and the various components/underlying components that make up the AGV. The author provides the foundation of what AGV’s are built upon. “The AGV is a battery-powered mobile platform with the ability to execute commanded motions and transfers. This is achieved through appropriate design and control of the vehicle” (Pal 2011). An automated guided vehicle is meant to eliminate the use of routine movement in a factory setting. The idea of using these materials generally avoids the numerous safety hazards of a factory. It allows for the movement of materials to be completely autonomous, effective and efficient. The underlying components that make up an AGV are navigation, trajectory editor, plan executor, and path tracking. The generations of AGVs is complicated by the fact that the controller must aim at making efficient use of the load carrying capacity of AGV, and at the same time respond to requests for materials from any station within a reasonable time (Pal 2011).
Secondly, in a publication by Davich, new technology is enabling the automated horizontal transport of materials to be significantly easier, quicker, inexpensive, reliable, and more flexible to implement and make changes. Although, the direct amount of material handling cannot be measured, the fundamental factors contributing to material handling amounts are time wasted. In actuality, a machine operator is being paid to sit while not producing value to the environment. According to the authors, this blame should not be put on the worker, but the company should take responsibility and figure out ways to address the issue of idle time. A solution to this issue is through simulation. It can be used to estimate cost savings based on improved performance measures, such as throughput time and manufacturing lead-time (Davich 2010).
Furthermore, Srivastava and Choudhary have taken a deeper look into the framework design of an AGV. They are designed to autonomously transport goods through a workstation without the need of a forklift driver. AGVs are beneficial in areas of long distance, repetitive actions and harmful areas. Navigation can be achieved in numerous ways but rely heavily of path networks and routing algorithms. This article in particular presents the ideas of resolving the issues of conflicts/interruption occurring in the guided path. An intelligent agent-based framework, which is a system used to generate shortest path, can be used to overcome the shortcoming associated with current approach (Srivastava 2008).
In addition, Longacre and Keiger introduce innovative ways to integrate AGVs in the material-handling field which include automated carts, operation in hospitals, and in grocery distribution product movement. In relation to this report, an AGV application method also on the list is beverage distribution center automation. Based on the current state of material handling, the integration can greatly benefit beverage distribution centers with the accuracy in inventory, fewer repairs to machinery, flexibility/mobility factors and reduction in energy costs. AGVs are able to accommodate multiple loads in regards to transporting cans. Factors to take into consideration with AGVs are adaptable and flexible solutions for ever-changing floor and facility layouts (Longacre 2014).
Although there are several navigation methods for AGVS, we focused on the inertial navigation (a.k.a. gyro navigation) due to its easier integration to the existing facility. This type of navigation method uses the solid-state gyroscope, located within the AGV, and a set of magnets placed on the plant floor to guide the AGV. The gyroscope helps detect changes in the
AGVs travels and the magnets serve as markers to help keep the AGV in its course. The AGV is meanwhile traveling using the maps that are stored in its memory.
Three alternatives were considered when evaluating the implementation of a new material handling system: a conveyor system and an automated storage and retrieval system (ASRS). A conveyor system would enable an automated movement system of the pallets. Pallets would be placed on the conveyor when distribution trucks arrived. The pallets would then take alternative routes depending on their respective storage places. Workers would be ready at the respective destinations of the pallets as they arrived and begin storing them. An automated storage and retrieval system followed the same concept as the conveyor system, but the need for workers to store the pallets would be eliminated. Our team found both systems to be feasible for implementation, but not cost justified. We would have to rearrange the floor layout so the conveyor system or automated storage and retrieval system could be embedded at our facility. We found the work and costs to outweigh the potential increase in throughput of both systems. AGVs proved to be an easier implementation in our current facility layout and just as efficient as the alternative solutions.
Having AGVs in a manufacturing, factory, or warehouse settings, brings many benefits to a company. In our study, we are replacing forklifts and operators with an AGV. Some of the benefits of integrating an AGV to the plant are the following. According to National Forklift Exchange and Adaptalift Hyster an AGV reduces the risk of injuries and accidents. Due that an AGV has many safety devices such as object detection, anti-collision and stopping tools, cameras, laser sensors, bumpers, and warnings lights. Also, by minimizing human interaction
with an AGV labor cost is reduced. AVGs are very reliable and durable and can potentially work continuously almost 24/7, the 365 days of the year. Therefore, productivity increases and possible profits increase as well. A key feature of an AGV is multi-directional movement, which includes forward, reverse, and sideways (90 degrees). In addition, AGVs keeps track of inventory providing inventory control. Another important benefit is that an AGV can be set up in very reduce aisle width, as small as 2 meters. A great benefit of an AGV is the reduction noise and exhaust fumes in a plant. A very crucial advantage of AGVs is fact that can work in very hazardous or cold storage environments.
When considering the implementation of the AGVS a series of safety standards needed to be considered and emphasized. According to standards ANSI/ITSDF B56.5-2012, the AGVs had to have the following safety features: collision avoidance system, accessible emergency stop buttons, visual warning/alarm lights, and audible warning/alarm signals.
For the safety of the workers near the operating AGVs, the AGV has to have a collision avoidance system, which uses sensors and lasers located on the front, side, back, and upper locations of the vehicle to detect an object within its path. Whenever the AGV detects something, the vehicle decelerates anticipating a full stop and comes to a full stop if the object remains within its path. The AGV takes 3- 6 seconds (depending on the programmer’s instructions) to resume operation, assuming the obstacle is no longer within its path. If the obstacle remains there after the 3-6 seconds are over, the vehicle will shut down and require assistance from a technician before it resumes operation.
Another of the safety features required under these standards is the accessible emergency stop buttons. These buttons are required for the safety of workers working near the AGV. In
addition, the AGV is required to have both visual and audible warning signals. The visual warning/alarm signals will serve to visually notify workers of the nearby AGV in operation. The audible warning/alarm signals serve also as a safety feature. They include two different tones for two different purposes. There is the acknowledge tone, which notified workers of the AGVs normal operation, and then there is the alarm tone, which notifies workers that something has gone wrong in the AGVs operations.
The introduction to of AGVs to the bottling plant was required to comply with material handling standards. The first material-handling standard that was observed was Occupational Safety and Health Administration (OSHA) 1910.178 Powered Industrial Trucks. The 1910.178 standard applies to specialized industrial trucks powered by electric motors or internal combustion engines and relates to fire protection, design safety, and trucks’ maintenance. Based on this standard the AGVs would have a designated location for operation and battery changing. No modification would be made to the AGVs without the manufacturer’s approval. Also, the AGVs would follow all industrial truck traffic regulations, including authorized speed limits. In addition, the AGVs will be maintained only by authorized personnel following the standard requirements.
Another OSHA standard that the AGVs would follow is the 1910.176 Material Handling – general. AGVs should have sufficient safe clearances space for aisles, loading and unloading areas. Also, aisles would be kept clear from obstruction that could potentially create a hazard.
Based on the analysis made in this project, we concluded that automating the existing manual process with the use of AGVs is beneficial to the company’s profitability, efficiency and worker safety. The implementation of an AGV in replacement of four Uline Straddler forklifts and one operator would further double the productivity and result in a $13 million profit, when not considering additional maintenance and facility costs.
“Automated Storage & Retrieval Systems – ASRS – AS/RS.” Bastian Solutions. Web. 28 Apr. 2015.
Davich, Thomas. Material Handling Solutions: A Look into Automated Robotics (2010): 26. Web. 28 Apr. 2015.
Egemin Automation Inc. “Automated Guided Vehicle Safety.” AGV Safety. Egemin Automation Inc. Web. 28 Apr. 2015.
“Forklifts vs. Automated Guided Vehicles.” Logistics & Materials Handling Blog. Adaptalift Hyster, 15 July 2013. Web. 28 Apr. 2015
Longacre, Mark, and Brian Keiger. “Interesting New AGV Applications: Where to Start.” (2014): 1-29. ModexShow. Automatic Guided Vehicle Systems (AGVS), 2014. Web. 28 Apr. 2015.
Lift Truck Cost Comparison Tool. N.p., n.d. Web. 2015 Apr. 28.
Miller, Carol. “New Standard for Automatic Guided Vehicles Released.” Material Handling Industry of America. N.p., 22 June 2012. Web. 28 Apr. 2015.
Occupational Safety & Health Administration. “Handling Materials – General. – 1910.176.” Handling Materials – General. – 1910.176. United States Department of Labor. Web. 28 Apr. 2015.
Occupational Safety & Health Administration. “Powered Industrial Trucks. – 1910.178.” Powered Industrial Trucks. 1910.178. United States Department of Labor. Web. 28 Apr. 2015.
Pal, Prabir K., et al. “Development Of An AGV-Based Intelligent Material Distribution System.” Current Science (00113891) 101.8 (2011): 1028-1035. Academic Search Complete. Web. 28 Apr. 2015.
Reddon, Tom. “AGVs vs Forklifts: Benefits and Drawbacks.” National Forklift Exchange. 4 Aug. 2014. Web. 28 Apr. 2015.
Srivastava, Sharad Chandra, et al. “Development Of An Intelligent Agent-Based AGV Controller For A Flexible Manufacturing System.” International Journal Of Advanced Manufacturing Technology 36.7/8 (2008): 780-797. Academic Search Complete. Web. 28 Apr. 2015.
Uline Straddler Stacker – 137″ Lift. N.p., n.d. Web. 2015 Apr. 28.

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