AC 2009-1621: RENEWABLE-ENERGY LABS FOR AN …web.engr.oregonstate.edu/~bosma/publications... · Renewable Energy Labs for an Undergraduate Energy Systems Course ... University for

AC 2009-1621: RENEWABLE-ENERGY LABS FOR AN UNDERGRADUATEENERGY-SYSTEMS COURSE

Bret Bosma, California State University, ChicoBret Bosma is a Lecturer in Electrical Engineering and Mechanical Engineering at CaliforniaState University, Chico. His research interests include power electronics and control systems withapplications in renewable energy systems. He teaches courses in signals and systems, controlsystems, and electronics. Bosma received his B.S. in Electrical Engineering from California StateUniversity, Chico and his M.S. in Electrical and Computer Engineering from California StateUniversity, Chico.

Gregory Kallio, California State University, ChicoGreg Kallio has been a Professor of Mechanical Engineering at California State University, Chicosince 1988. He teaches courses in thermodynamics, heat transfer, and energy systems. His currentresearch interests include building energy simulation, renewable energy systems, and air pollutioncontrol. Kallio received his B.S. in Engineering Physics from Oregon State University, M.S. inElectrical Engineering from Colorado State University, and the Ph.D. in Mechanical Engineeringfrom Washington State University. He has worked for General Electric Corporate R&D inSchenectady, NY and for Berkeley Nuclear Laboratories in Gloucestershire, U.K. as a visitingscientist.

© American Society for Engineering Education, 2009

Renewable Energy Labs for an Undergraduate Energy Systems

Course

Abstract

This paper reports the successful implementation of two renewable energy laboratory

experiments in an undergraduate Energy Systems course in Mechanical Engineering. One is a

tracking, photovoltaic (PV) mini-lab that is a stand-alone system mounted on a wheeled cart. The

cart contains all equipment normally required for a remote residential installation, namely, a

300W PV module, batteries, inverter, and charge controller. The system is wired with proper

grounding, disconnects, breakers, and GFI load receptacles. The tracking system is a “tilt and

roll” type, where the seasonal “tilt” is manually adjusted and the daily “roll” is produced by a

geared stepper motor controlled by closed-loop LED sensor and indexer. The cart also houses a

data acquisition panel where solar irradiation, PV voltage, PV current, PV module temperature,

and ambient temperature are displayed and available for computer data logging. Students log

data for a one-hour static test and a one-hour tracking test, then reduce the data and compare the

power output and conversion efficiency for each test.

The other experiment is a wind energy lab that evaluates the performance of an Air 403 wind

turbine from Southwest Windpower, Inc. The turbine is mounted on a 20’ high mast located on

the engineering building roof. The turbine has a rated output of 400W at 28 mph (12.5 m/s) and a

start-up wind speed of 7 mph (2.7 m/s). The aluminum body houses an accurate heading angle

sensor (in-house modification) and a generator with charge regulator that produces 12 VDC for

charging batteries. A cup-type wind anemometer, wind direction vane, and a shielded thermistor

are also mounted on the mast. Outputs from the DC generator and all sensors are routed to a data

acquisition panel located in a laboratory classroom. The panel displays DC voltage, DC current,

wind speed, and temperature with outputs for load connection and analog outputs for computer

data logging of all sensor outputs. Students record data during a 2-3 day windy period and then

reduce the data to yield a power curve that is compared with that of the manufacturer.

Conversion efficiency and yawing error are also computed and analyzed.

Forty (40) senior Mechanical Engineering students participated in these laboratories during Fall

2008 as part of a required Energy Systems course. Their perceived learning and satisfaction was

assessed through a survey instrument. Feedback was overwhelmingly positive and insightful

recommendations for improvement were obtained.

I. Introduction

Based on current data on global warming, as well as the current U.S. dependence on foreign oil,

there is a renewed interest and urgency in utilizing alternative energy sources. Throughout

campuses in the United States there has been a definite push for alternative energy research and

education. In particular, undergraduate engineering and engineering technology programs are

now including laboratory-based curricula in renewable energy1,2,3. Aligned with these aims, this

paper describes the successful design and implementation of a Photovoltaic Power System Lab

and a Wind Turbine Power System Lab for a senior-level Energy Systems course in Mechanical

Engineering.

Hands-on experiments such as those described in this paper provide for enhanced learning

experiences. Both units provide real time display of key system properties as well as

surrounding conditions through data acquisition panels. Data is displayed in real time to show

the effects of changing conditions on the system. Data is also logged through the use of a PC

with which the data is later analyzed. These labs have been running since the Fall 2005 semester

with overwhelmingly positive feedback.

There are four major components to this paper. The first focuses on the hardware aspects of the

experiments. Details of the equipment used and the design philosophy are discussed. The

second section focuses on the experimental procedures, detailing the student interaction with the

experiments as well as what is asked of the students. The third section details the student

learning and assessment. Data from a survey given to the students is analyzed that quantifies

perceived learning and offers suggestions for improvement. The fourth section details

conclusions and future developments for the labs.

II. Hardware

A. Mobile Photovoltaic Power System

The Photovoltaic Power System lab started as a senior mechanical engineering design project.

The design concept was a mobile laboratory unit for the Energy Systems course as well as for

use in general public educational venues. The PV power system has been used several times in

this latter capacity proving to be a valuable resource outside of the laboratory. Students designed

most of the mechanical attributes of the equipment. An alumnus provided welding and

fabrication expertise to create the supporting structure based on the students’ design. The

photovoltaic panel, charge controller, inverter/charger, and dc disconnect were donated to the

University for their use in the lab. The electrical design and wiring was provided by technical

staff in the college.

The mobile photovoltaic (PV) power system consists of a typical stand-alone battery backup

setup having the necessary equipment for a remote residential setting (Figure 1). The system, as

configured, would have application as a backup to utility supplied power where it may be

unreliable. Although equipped for this use, the system provides an excellent platform for

students to learn about PV renewable systems as well as providing sophisticated data acquisition

which monitors the status and performance of the system.

The power source is an

RWE Schott 300 Watt

photovoltaic module with a

maximum power point

rating of 17 V at 17.7 A.

The module is connected to

a PV combiner box which

would typically combine

the parallel modules and

provide fused protection for

the entire array. Since our

system contains only one

module, the combiner box

functions solely as a

breaker panel, providing a

DC disconnect for the

system. From this breaker

panel a switch allows the dc power to be available directly at the data acquisition panel, thereby

bypassing the rest of the system. In the other position this switch connects the PV panel to the

Xantrex C60 charge controller. This unit can be used as a charge, diversion, or load controller.

For this application the charge function of the unit was used because it is connected to batteries.

The power output from the charge controller is then supplied to the batteries and the

inverter/charger. The batteries consist of three Werker 12V, 125 A-hr sealed, lead-acid absorbed

glass mat batteries. The inverter/charger is a Xantrex DR1512 whose function is twofold. It

provides a modified sine wave output at 120V and 60hz which supplies three sets of standard

receptacles on the cart. It also provides a second option for charging the batteries. In the

situation where the PV module cannot sufficiently charge the batteries the inverter/charger can

be plugged into a standard outlet to charge the batteries. Figure 2 shows a detailed wiring

diagram showing the major system components and interconnections.

The PV module is attached to a tracking mechanism that allows it to follow the sun throughout

the day. The tracking system is a “tilt and roll” type where the seasonal “tilt” is manually

adjusted and the daily “roll” is produced by a geared stepper motor and indexer. The motor,

indexer, and interface panel are Compumotor units. Two types of tracking methodologies can be

used. The first is an open loop type where the module is set to move at a constant rate that

matches the earth’s rotational speed of 15 deg/hr. The second is a closed loop feedback system

using LEDs as photocells to find the brightest part of the sky. Four LEDs are arranged such that

when the sun is brightest on the center two, the panel has found the brightest part of the sky and

Figure 1. Mobile PV Power System.

Figure 2. PV Power System Wiring Diagram.

logic level signals are output to the indexer and the panel stays put. If the brightest part of the

sky is detected on either side pair of LEDs, the logic level signals tell the indexer to move in the

corresponding direction. This allows the panel to “actively” track the sun, always finding the

brightest part of the sky.

The data acquisition panel is a major part of the PV power system and allows students to monitor

the system and record data (Figure 3). LCD displays give real time feedback on the status of the

system from various sensors. These sensor outputs are also available through jacks which are

connected to a Fluke 2625 Hydra Logger which

in turn is connected to a PC. This provides an

automated way to log data for further analysis. A

LI-COR LI-200 pyranometer is used to measure

solar irradiance in watts per square meter. The

PV voltage and current are displayed and

available for logging with the current output

taken from a shunt. There are six thermocouples

on the cart providing module, battery, and

ambient temperatures. A battery monitor is also

present which displays battery voltage, battery

current flow, accumulated battery charge, and

time elapsed.

B. Wind Turbine Power System

The wind turbine power system consists of a typical residential setup combined with monitoring

and sophisticated logging of the system performance. The turbine is mounted on the roof of our

engineering building on a 20 foot high mast (Figure 4). The power output and data acquisition of

the system is located in a laboratory inside the building.

The heart of the system is a Southwest Windpower Air 403 wind turbine. This turbine is rated at

an output of 400 watts at 28 mph. Its housing contains a voltage regulator for battery charging.

Its blades feature over-speed control in the form of passive pitch control in which aerodynamic

blade flutter limits RPM. The start-up speed for this unit is approximately 8 mph. The power

from the turbine runs to a three-position switch

that allows the unit to be connected to the

battery bank, open-circuited, or short-circuited

(braking). Also in line with the load are a

100A circuit breaker and a 60A fuse. The

100A breaker provides circuit protection on the

rooftop. The 60A fuse provides circuit

protection within the laboratory. A load

disconnect switch is located at the data

acquisition panel to give control over the load.

The system was designed to allow for any load

to be connected to the turbine. Currently two

Werker 12V, 100Ah, sealed lead-acid absorbed

glass mat batteries are connected to the load.

Figure 5 shows a wiring diagram and the major

system components.

Figure 3. PV Data Acquisition Panel.

Figure 4. Wind Turbine Mast Components.

Figure 5. Wind Turbine Power System Wiring Diagram.

The data acquisition panel is a central learning point of the lab (Figure 6). Various sensors are

used to deliver data to the panel providing key information about the system status. An NRG

Systems 110S temperature sensor unit and an NRG Systems Type 40 cup-type wind anemometer

with amplifier are installed on the turbine mast. The turbine voltage and current, temperature,

and wind speed are available by display on the data acquisition panel and for data logging via a

Fluke Hydra Logger and PC.

Preliminary data suggested that the passive yawing of the Air 403 produced some error between

the turbine heading and wind direction. Thus the proper sensors were installed to provide the

data needed to study this phenomenon. An NRG #200P wind direction vane was installed in

order to get an accurate wind direction indication. A GMW Ametes Angle Sensor Module was

installed in the turbine body. These sensors allowed measurement of the real-time yawing error.

These signals are available for logging with a Fluke Hydra Logger and PC.

The components described create an effective

educational and research facility exemplifying a

typical set of equipment used in wind turbine

systems. The system also includes the proper

sensors for analyzing the system performance

and exploring the characteristics of the turbine.

Special care was taken to make the proper fuse

and breaker connections to create a safe

educational environment.

III. Experimental Procedures

A. Photovoltaic (PV) Power System

The PV power system experiment is scheduled

early in the Fall semester (September) when the

skies are reliably clear. We have been fortunate

to experience sunny weather and no rain for all

scheduled experiments since Fall 2005. The

mobility of the experiment allows us to find

suitable locations for the lab at any scheduled time during the day.

The experiment is introduced to the students with a short PowerPoint presentation on

photoelectric theory, PV module characteristics, and the balance-of-system (BOS) components

that include the charge controller, DC disconnect, batteries, and inverter. A short demo is

performed by the instructor to acquaint the students with the equipment, experimental procedure,

safety aspects, and data acquisition.

The primary performance measure to be determined from this laboratory experiment is the PV

module efficiency:

AG

IV

sun

PV ??rateenergy solar Incident

bankbattery todeliveredpower DCϕ

where I = dc current supplied to battery bank (amps)

V = dc voltage supplied to battery bank (volts)

Gsun = normal solar irradiation (W/m2)

A = PV module surface area (m2)

Figure 6. Wind Turbine Data Acquisition

Panel.

The PV power output may depend upon three parameters that can be measured from this lab

experiment: 1) solar intensity, 2) tracking error, and 3) PV panel temperature. Solar intensity

naturally varies due to seasonal effects, time of day effects, and atmospheric clarity. Solar

irradiation at the PV module surface depends upon solar intensity and the module orientation

(leading to tracking error). PV photocurrent is usually assumed to be linearly-dependent upon

solar irradiation, so the net effect on system efficiency, as defined above, is expected to be very

small.

PV module temperature shows a natural variation due to the amount of solar irradiation, ambient

temperature, wind speed, and transient heating during start-up. Increased PV module temperature

is known to decrease system efficiency by up to 0.4% per ″C above the standard temperature

condition of 25″C. Average temperature can be monitored on the underside of the module from

four adhesive thermocouples. Separating the effect of solar irradiation and PV temperature on

performance could be manually investigated by use of enhanced air circulation (e.g., fan or

blower) or by insulating the underside of the panel. While interesting, these effects are not

investigated in this experiment.

The lab period is three hours long and students conduct the experiment in a static mode and

tracking mode for at least one hour each. The experiment is initially set up by aligning the PV

module axis with true south. The module is leveled side-to-side and then tilted to the precise

angle that yields perpendicular solar incidence at solar noon. For example, this angle (known as

the seasonal angle) is 37.5″ with respect to horizontal on September 15 in Chico, CA. Accurate

angle adjustment is accomplished with a digital inclinometer and adjusting nuts on a finely-

threaded pipe that supports the module.

For the static test, the PV module remains in the true-south position. For the tracking test, the

automatic tracking system is energized and the module is allowed to “roll” about the axis

prescribed by the seasonal angle setting. This single-axis, “tilt-and-roll” movement closely

approximates the trajectory of the sun through the sky. The largest tracking errors occur near

sunrise and sunset.

All data is acquired by a Fluke Hydra Logger connected to a PC that runs the Fluke Hydra

Logger software. A sampling interval of 30 seconds is normally used. The recorded data include

the normal solar irradiation measured by the pyranometer, voltage at the battery, current supplied

to the battery, module temperature, and ambient air temperature. Students measure the module

length and width to obtain the active surface area. Data reduction and results are requested as

follows:

a. Plot the raw data versus elapsed time for the static and tracking test: Plot all temperature data with appropriate scaling and legend. Plot voltage and current for each test using two y-axes with appropriate scaling and legend. Plot solar irradiation for each test with appropriate scaling and legend. Use 3-pt size data markers connected with a straight line (no smoothing).

b. Compute the DC power output and PV efficiency at each time step for the static and tracking tests. Plot the DC power output and PV efficiency versus time for each test using two y-axes with appropriate scaling and legend. Use 3-pt size data markers connected with a straight line (no smoothing).

c. Compute the average solar irradiation, average DC power output, and average PV module efficiency for each test. Put these results in a summary table. Compare and discuss all your findings in the Conclusions section of the report.

The experiment is performed and a report is written by student teams of four to five members.

The report contains a title page with group members’ names and signatures, the laboratory

description document, summary table with data reduction spreadsheets, the graphs described

above, a Discussion-Conclusions- Recommendations section, a sample “hand” calculation for the

PV efficiency, and answers to the following questions:.

1. Are the PV module efficiencies significantly different for the static and tracking tests? Why, or why not? Compare the average dc power outputs for the two tests (compute the average percent difference). Discuss and define a different efficiency that includes the benefit of tracking.

2. Explain how the battery state of charge might affect the DC power output and PV efficiency. For example, would you expect the same results if the batteries were fully charged and no loads were connected to the system?

3. Refer to the I-V graph in the pdf specification sheet for the RWE Schott ASE-300-DFG/17

module on WebCT. Reproduce this graph for Gsun=1000 W/m2 and T=50″C and indicate the I-V region(s) where the module operated during the tests. Did the module operate near its Maximum Power Point (MPP)? See module specs for MPP voltage and current.

Experimental data and computed results from a past class are shown in Figures 7 through 11.

Figures 7-9 display the raw solar irradiation, voltage, current, and temperature data versus

elapsed time. The lab period for this is particular class was 8am to 11am. The static test solar

irradiation, voltage, and current values are all increasing with time because the tracking error is

decreasing as the sun is rising toward solar noon. As expected, the tracking test shows

significantly higher and nearly constant values of solar radiation, voltage and current. Module

temperature was significantly higher during the tracking test due to the combined effect of higher

ambient temperature and increased solar irradiation.

Figure 7. Solar Irradiation.

Figure 8. PV Voltage and Current.

Figure 9. Module Temperature.

Figure 10 shows the dc power output for static and tracking tests. Again, the static test shows an

increasing trend with time due to decreasing tracking error. The tracking dc power is nearly

constant and approximately 40% higher than the static dc power for this test. Figure 11 shows

the PV system efficiency versus time. Both tests show similar values because of the normalizing

effect of the solar irradiation in the denominator of the efficiency equation. The slightly higher

efficiency for the tracking test is unknown – it may be due to pyranometer angle-of-incident

errors, increased reflection from the PV module glass at non-normal incident angles, or possibly

some nonlinearity in the relationship between photoelectric current and solar intensity.

Figure 10. PV Power.

Figure 11. PV Efficiency.

The questions posed to the students attempted to test their understanding of the entire PV system.

Question 1 prompts students to explain why the measured PVefficiency, as defined, is nearly the

same for the static and tracking modes. In turn, they are asked to develop a different efficiency

formula that reveals the benefit of tracking. Approximately one-half of the students in the class

were able to explain this result but very few were able to formulate a new “tracking” efficiency

equation. Question 2 prompts students to consider how the battery state of charge affects the

power output of the system. Most students recognized that if the batteries are fully-charged, then

the system power output would be much lower and would only reflect the instantaneous load of

the tracking motor/driver, data acquisition panel, data logger, and PC. Question 3 requires the

students to study the I-V characteristic of the PV module and understand the concept of

maximum power-point (MPP) operation. Most all students were able to plot the measured data

on the I-V graph and recognize that the system was not operating near its MPP. An additional

question might ask how the system could be configured to achieve MPP operation; however,

further instruction would be required to provide the necessary background to answer this.

B. Wind Turbine Power System

The wind turbine experiment is primarily a data reduction exercise since the system operates

automatically after it is turned on. Furthermore, the experiment cannot be scheduled for the

three-hour lab meeting time since it is dependent upon adequate local wind. Chico, CA is not

located in a windy area so the experiment must be run during a Pacific storm event, which

typically occurs after November 1 during the Fall semester when the course is offered. The

experiment has been run since Fall 2005 and we have been fortunate to experience at least one

strong storm event during this time each year. The course instructor has the responsibility of

“capturing” the storm event by turning the system on and recording data for a period of one to

two days at 1-sec intervals. The data is acquired by a Fluke Hydra Logger. The raw data is then

posted to the course WebCT site from which the students can download the data. The Southwest

Windpower Air 403 manual is also posted on WebCT.

The experiment is introduced to the students with a short PowerPoint presentation on wind

power followed by an inspection of the turbine on the engineering building roof and the data

acquisition system in the Measurements & Instrumentation Laboratory. The laboratory

experiment document (prepared by the instructor) describes the equipment and sensors, presents

the equation for computing efficiency, describes the required data reduction, gives the Air 403

power curve from the manufacturer, and poses several questions that the student must address in

their report.

The primary performance measures to be determined from this laboratory experiment are the

power curve (dc power output versus wind speed) and the power coefficient, or wind turbine

efficiency:

2

21power windavailable

load todeliveredpower DC

w

dc

WTVm

IV

&??ϕ

where I = dc current supplied to battery bank (amps)

Vdc = dc voltage supplied to battery bank (volts)

Vw = wind velocity (m/s)

m& = mass flow rate of air incident on rotor area (kg/s)

= wrVAτ

τ = air density at measured T (kg/m3)

Ar = swept rotor area (m2)

The recorded data include wind speed and direction, turbine heading, load voltage, load current, and temperature. The wind direction and turbine heading data allow the students to investigate the passive yawing effectiveness of the wind turbine. Data reduction and results are requested as follows:

a. Sort the data in Excel with respect to wind speed in ascending order. Determine the electrical power delivered to the batteries for each wind speed logged. Convert the wind speed to mph and plot the “power curve” for the wind turbine using all data points (power in watts versus wind speed in mph). Do not connect the data points and use the smallest marker size available. Overlay the manufacturer’s power curve.

b. Compute the wind turbine efficiency for each wind speed logged. Plot the efficiency versus wind speed for all data points. Do not connect the data points and use the smallest marker

size available. Use atmospheric pressure (101.3 kPa) and the recorded temperature to determine air density.

c. Plot the turbine heading on the y-axis against the wind direction on the x-axis for all data.

Each scale should be 0-360″. Do not connect the data points and use the smallest marker size available. Fit the data with a linear Trendline; use a y-intercept of zero and display the equation and R2-value. On a separate graph plot the wind direction and the wind turbine heading as a function of elapsed time for a short segment of time (approximately 2-3 minutes) when the wind speed was substantial. Connect the data markers with lines and include a legend.

The experimental data reduction is performed and a report is written by student teams of four to

five members. The report contains a title page with group members’ names and signatures, the

laboratory description document, the four graphs described above, a Discussion-Conclusions-

Recommendations section, and a sample “hand” calculation for the wind turbine efficiency.

Students are specifically asked to discuss: 1) the differences between the measured power data

and the manufacturer’s power curve (i.e., why are they different?), 2) why some of the computed

efficiencies are above 100%, and 3) how well the wind turbine tracked with the wind direction

and responded to changes in the wind direction.

Reduced data and computed results from past classes are shown in Figures 12 through 15. Figure

12 compares the measured power data versus wind speed with the manufacturer’s power curve.

The prevalent scatter is due to the transient response of the turbine in gusty winds, where its

inertia can cause a relatively high power value to be recorded if the wind speed is decreasing

and/or changing direction and a relatively low power value if the wind speed is increasing and/or

changing direction. Turbine inertia consists of both body and blade rotation. The power curve

tends to over-predict the average measured data, presumably because the manufacturer tests its

turbines in a wind tunnel where yawing is not important and low turbulence levels exist. The

aerodynamic braking is evident for wind speeds greater than 40 mph.

Figure 12. Wind Turbine Power Output vs. Wind Speed.

Figure 13 shows the measured instantaneous turbine efficiency versus wind speed. Again, a large

degree of scatter is observed for the reason stated above. Furthermore, measured efficiencies

greater than 100% are possible due to the inertial effects, specifically when the wind speed

suddenly decreases and/or changes direction and the turbine output lags in response. The average

efficiency appears to be in the 20-25% range.

Figure 13. Instantaneous Efficiency vs. Wind Speed.

Figure 14 compares the turbine heading with wind direction, showing the expected scatter due to

turbine inertia. The Excel Trendline fit displays a nearly 1:1 correspondence with a R2 = 0.44

positive correlation, indicating that yawing is effective on the average. Figure 15 compares wind

direction, turbine heading, and wind speed versus time for a three-minute windy episode. As

expected, the tracking (yawing) is far from perfect but confirms the positive correlation and also

reveals a slight lag in turbine response to the wind direction.

Figure 14. Turbine Heading vs. Wind Direction.

Figure 15. Turbine Heading, Wind Direction, and Wind Speed vs. Time.

IV. Student Learning and Assessment

Forty (40) senior Mechanical Engineering students participated in the renewable energy

laboratories during Fall 2008 as part of the Energy Systems course. Their perceived learning and

satisfaction were assessed with a survey instrument administered after the semester ended. The

survey consisted of seven statements related to the effectiveness of each lab. Student response

was scored using a Likert scale; the percentage results and weighted scores are presented in

Tables 1 and 2.

Table 1. PV Power System Survey Results

Survey Query

Strongly

disagree

=1

Disagree =

2

Neutral

= 3

Agree

= 4

Strongly

Agree = 5 Score

Before undertaking the PV Power System

Experiment, I felt comfortable with the

concepts related to photovoltaic power.

0 16 32 47 5 3.4

The Introduction to the PV Power System

Experiment given by the instructor was

useful in understanding the operation of

photovoltaic power systems.

0 0 0 37 63 4.6

The Laboratory Description document was

useful in understanding the experimental

procedure and data reduction.

0 0 5 63 32 4.3

After completing the PV Power System

Experiment and Lab Report, I have a better

understanding of the operation of

photovoltaic power systems.

0 0 11 47 42 4.3

After completing the PV Power System

Experiment and Lab Report, I have a better

understanding of the performance (power

output and efficiency) of static and tracking

photovoltaic power systems.

0 0 0 42 58 4.6

The PV Power System Experiment increased

my interest in photovoltaic power systems. 0 5 5 58 32 4.2

A design assignment that required each

student to determine the PV siting, array

size, and appropriate components for a

particular application would complement

this experiment and enhance learning.

0 0 21 37 42 4.2

Table 2. Wind Turbine Power System Survey Results

Survey Query

Strongly

disagree

=1

Disagree =

2

Neutral =

3

Agree

= 4

Strongly

Agree = 5 Score

Before undertaking the Wind Turbine

Power System Experiment, I felt

comfortable with the concepts related to

wind turbine power.

0 0 17 67 17 4.0

The Introduction to the Wind Turbine

Power System Experiment given by the

instructor was useful in understanding the

operation of wind turbine power systems.

0 0 0 47 53 4.5

The Laboratory Description document was

useful in understanding the experimental

procedure and data reduction.

0 0 5 58 37 4.3

After completing the Wind Turbine Power

System Experiment and Lab Report, I have

a better understanding of the operation of

wind turbine power systems.

0 0 5 42 53 4.5

After completing the Wind Turbine Power

System Experiment and Lab Report, I have

a better understanding of the performance

(power curve, efficiency, and yawing error)

of wind turbines.

0 0 5 58 37 4.3

The Wind Turbine Power System

Experiment increased my interest in wind

turbine power systems.

0 0 32 32 37 4.1

A design assignment that required each

student to determine the number, size, and

type of turbines for a particular application

would complement this experiment and

enhance learning.

0 0 11 47 42 4.3

The results show that the labs were generally very successful in improving the understanding of

PV and wind turbine system operation and performance. Furthermore, students were

overwhelmingly supportive of an additional system design assignment to complement each

experiment. Of greatest value were the responses to two additional survey questions that asked

students how the experiments and learning experience could be improved. Responses to these

questions yielded some excellent suggestions and insight into the student learning process. They

are summarized in Tables 3 and 4.

Table 3. Written Responses to “How could the PV Power System Experiment be further

improved to enhance the learning experience?”

Response Frequency

Run experiment on different days to compare sunny versus cloudy performance. 2

Run experiment for an entire day to measure overall tracking benefit 2

Make lab teams smaller to allow more hands-on experience 1

Use module cooling techniques to see if efficiency gains are significant 1

Measure state of battery charge before and after experiment; compare with dc power output and

reconcile. 1

Add a related analysis activity so students have more to do during experiment. 1

Add calculation of mitigated carbon emissions or greenhouse gases due to PV. 1

Use PV power for something useful on campus. 1

Provide more information on grid-tied systems, inverters, and component selection. 1

Add a field trip to a company that builds PV modules. 1

Table 4. Written Responses to “How could the Wind Turbine Power System Experiment

be further improved to enhance the learning experience?”

Response Frequency

Use wind tunnel to test scale-model turbines for determining power curve and efficiency 3

Be able to view wind turbine up-close on a windy day 2

Test different wind turbine designs. 1

Need more hands-on activities. 1

Make lab teams smaller so each student is required to do more. 1

Have student teams build their own wind turbine. 1

Provide more information on different turbine designs, wind farms, and scaling laws. 1

V. Conclusions and Future Improvements

The PV Power System and Wind Turbine Power System labs have proved to be valuable

renewable energy teaching tools in our Energy Systems course. Mechanical engineering student

surveys reveal increased operational understanding and interest in solar and wind energy.

Written student comments have produced several excellent suggestions for improvement. Based

on these comments, the following activities are being planned for implementation in future

semesters:

PV Power System Lab

1. Include a design assignment that requires each student to determine the PV siting, array size,

and appropriate components for a particular electric power application. Provide more lecture

material that pertains to PV siting, array sizing, selecting components, and grid-tied systems.

2. Run the experiment over an entire day (sunrise to sunset) to better quantify the benefit of

tracking. Measure state of battery charge at start and end of experiment; compare with PV energy

output.

Wind Turbine Power System Lab

1. Include a design assignment that requires each student to determine the number, size, and

type of turbines for a particular electric power application. Provide more lecture material on

different turbine designs, balance-of-system (BOS) components, and scaling laws.

2. Include a separate activity where students test different wind turbine designs in the wind tunnel to determine torque, speed, power output, and efficiency characteristics under varying loads. Acknowledgements

The materials and equipment required to build these labs were partially funded by a grant from

the CSU, Chico Center for Excellence in Learning and Teaching (CELT). We would like to

thank the following companies and individuals for their generous equipment donations and

service: Mark Bettis of RWE Schott Solar, Gary Speer of Metal Works, Jeff Thomas, and

Richard Coons. The mechanical design of the PV tracker, PV module support, and cart was done

by Chico State mechanical engineering student Shawn Molina. We also wish to thank Steve

Eckart, lead electromechanical technician at CSU, Chico, for his design assistance and many

hours of electrical work.

References

1. Pecen, R. & Timmerman, M.A., “A Hands-On Renewable Energy Based Laboratory for Power Quality Education” Proceedings of the 2001 American Society for Engineering Education Annual Conference & Exposition, 2001, Session 1333. 2. Lakeou, S., Ososanya, E., Latigo, B., Mahmoud, W., Karanja, G., & Oshumare, W., “Design of a Low-Cost Solar Tracking Photo-Voltaic (PV) Module and Wind Turbine Combination System”, Proceedings of the 2006 American Society for Engineering Education Annual Conference & Exposition, 2006, Session 1992. 3. Al Kalaani, Y. & Rosentrator, K., “Introducing Renewable Energy Education into an Engineering Technology Program”, Proceedings of the 2007 American Society for Engineering Education Annual Conference & Exposition, 2007, Session 2568.

Appendix A: Equipment Lists

Photovoltaic mini-lab

COMPONENT MANUFACURER MODEL ESTIMATED COST

Photovoltaic Panel RWE Schott ASE-300-DGF/17 $1830

Inverter Xantrex DR1512 $628

Charge Controller Xantrex C60 $175

DC Disconnect Xantrex DC175 $285

AGM Batteries (3) Werker 12V, 125Ah $570

Shunt Deltec Company 50mV 500A $50

Amp-hour Meter Xantrex Link 10 (Emeter) $210

Thermocouples Omega SA1-T-72 $80

Jack Panel and Connectors Omega MJP1-06-T NMP-T-M

$47

Temperature Display Omega DPi32-DC $175

Thermocouple Rotary Selector Switch

Omega OSW3-10 $113

Pyranometer w/Leveling Base and Millivolt Out

LI-COR LI-200SA $266

Pyranometer Display Omega DPi32-DC $175

Inclinometer SPI Pro 360⁰ $230

Indexer Compumotor 6200 $1250

Drive Compumotor S series $750

Interface Panel Compumotor RP240 $380

Wind Turbine

COMPONENT MANUFACURER MODEL ESTIMATED COST

Turbine Southwest Wind Power Air 403 $649 – 25% educ. dis.

Stop Switch & Circuit Breaker Southwest Wind Power 100Amp $52

Anemometer w/Speed Amp NRG Systems #40 #892

$180

Wind Direction Vane NRG Systems #200P $195

Sensor Cables NRG Systems $83

Side Booms (2) NRG Systems 1.53m $170

Temperature Sensor with Radiation Shield

NRG Systems #110S $195

AGM Batteries (2) Werker 12V, 100Ah $260

Temperature Display Omega DPi32-DC $175

Wind Speed Display (Ratemeter w/Analog Out)

Omega DPF701-A $360

Current and Voltage Meters w/Power Supply

Datel DMS 30PC DMS-PS3-CM

$190