Conclusion:
Although the COVID-19 Pandemic hurt the final integration of all systems, the project still met the majority of expectations. The final system and all peripherals could not be mounted on to a solar panel, but all the systems work well and can be easily tested once health concerns dissipate. On the whole, the entire system cost $161.47. This is well under budget especially for the practicality. The overall Solar Tracker System features a robust and bug-free user interface. Of course, this is contingent on the user actually using the system as directed in the User Manual. The only other bugs procured during final testing were due to faulty jumper cables. Specifically, the I2C communication between the MSP432 and the accelerometer sometimes faltered due to shoddy jumper cables. Additionally, the system provides three distinct modes that can each help in the development and testing of Single-Axis solar tracking. Let’s evaluate them one by one. First, the Manual Entry mode can be used to develop new algorithms. In this mode, the user enters an angle and the system moves the solar panel to that angle plus or minus 0.25 o. As a
result, the user can move the solar panel to any angle between -90 oand +90o at any time. Please
refer to the accelerometer section for how to properly mount it in correspondence to the panel. Next, the Algorithm mode can be used to test out any algorithm the user desires. Currently, the system is pre-loaded with a Solar Tracking algorithm provided by Professor Dolan. To change the algorithm, simply modify the code in the Algorithm.c section. The user only needs to modify a single function, and the new algorithm will run seamlessly.
Finally, the Demo mode can be used to stress test the mechanisms that actually move the solar panel. This type of stress test is critical before long-term mass deployment. As a result, the system provides a complete package in Solar Tracking Algorithm development.
Future Work:
For future implementation, the Laboratory Single-Axis PV Module Tracker, would ideally be placed on a solar panel in order for laboratory testing. Due to unforeseen circumstances and limited sources, the module tracker was unable to be put directly on the solar panel. However, once implemented on the actuator of the solar panel, the device will be able to control the tilt
angle. One improvement that could be made on this project would be to solder each wire
connection to minimize I2C communication errors. Other improvements would be in the design and build of the overall project, as well as possibly including more modes to test.
Future users of this module will benefit from being able to observe and measure the exact, desired angle of the solar panels in a laboratory setting. By altering the part of the code that determines the location of the panels, users can see how the panels would be angled at a given time in any location. This benefits users that are interested in finding the optimal angle for solar panels to be at a given time and location.
References
[1] V. P. Anand, O. B. Priyan, and B. Pesala, “Effect of shading losses on the performance of solar module system using MATLAB simulation,” in IEEE 2nd International Conference on Electrical Energy Systems (ICEES) 2014, Chennai, India, January 7-9, 2014, [Online]. DOI: 10.1109/ICEES.2014.6924142.
[2] P. Domorand and M. Averbukh, “Partial shading problem solution for solar arrays fed by MPPT via permanent monitoring of individual panels,” in IEEE 28th Convention of Electrical and Electronics Engineers in Israel, December 3-5, 2014, [Online]. DOI: 10.1109/EEEI.2014.7005767.
[3] “Cal Poly Gold Tree,” greenpowermonitor.com, 2019. [Online]. Available:
https://web3.greenpowermonitor.com/application/#/adminReports/3387. [Accessed Oct. 19,
2019].
[4] D. Schneider, “Control Algorithms for Large-scale Single-axis Photovoltaic Trackers”, Institute of Imaging and Computer Vision, Aachen University: May, 2012.
[5] Suncore Photovoltaics, Inc. (Irwindale, CA), J. Sherman, ‘Solar Tracking System’, 8946608, 2015.
[6] A. Mey, “Most U.S. utility-scale solar photovoltaic power plants are 5 megawatts or smaller”, US Energy Information Administration, EIA: February, 2019.
[7] Texas Instruments, “Microcontroller LaunchPad,” MSP432P401R datasheet, March 2015 [Revised March 2018].
[8] Storm Interface. “PLX Series - 16 KEY TELEPHONE FORMAT,” PLX16T20 datasheet,
November 2008.
[9] Newhaven Display International, “NHD-0420H1Z-FSW-GBW-33V3,” Character Liquid Crystal Display Module Datasheet, November 2017.
[10] NXP Semiconductors. “MMA8452Q, 3-axis, 12-bit/8-bit digital accelerometer,” MMA8452 datasheet, April 2016.
[11] 2 Channel 5V Relay Module, Sundatafounder, November 2019. [Online]. Available: http://wiki.sunfounder.cc/index.php?title=2_Channel_5V_Relay_Module
APPENDIX A - ANALYSIS OF SENIOR PROJECT DESIGN
Project Title: Design and Development of Laboratory single-axis PV Module Tracker
Students’ Name: Delaney Berger, Avishek Maitra, Helen Rice
Students’ Signature:
Advisor’s Name: Dale Dolan Advisor’s Initials:
Date: 12/13/219
1. Summary of Functional Requirements
The single-axis PV Module Tracker system allows users an effortless way to test various
algorithms to ultimately determine the best way to avoid inter-row shading and maximize
power output. The system will allow characterization of specific existing algorithms as well as
newly customized algorithms in order to inform students on critical solar tracking characteristics. Additionally, the system will provide the flexibility to test algorithms before
they are deployed on a large scale. 2. Primary Constraints Describe significant challenges or difficulties associated with your project or implementation. The single-axis PV Module Tracker system is limited by the algorithm that takes into account
the maximum angle of the motors. The location and orientation of the solar panels combined
with the single-axis tracking motors limits the angle of rotation for each panel. The difficulties
will be in creating an algorithm that maximizes the angle of rotation while minimizing the
amount of inter-row shading. Difficulties also include finding a durable, weather-proof
material external housing structure for test equipment and angle measurement device. Finally, students design a user interface that is easy to use while displaying important information in an
organized manner. The display and interaction with the system will provide the bulk of
complexity to the embedded system. Testing dates must be chosen in accordance with viable
weather conditions for testing. 3. Economic The economic costs primarily consist of human capital, financial capital, manufactured capital,
and natural capital. The human capital spent on development totals to over 300 hours. In terms
of financial capital, each finished product will cost $341 to build and collect all the parts
necessary. Our manufactured capital consists of all the necessary tools to fabricate the housing
as well as properly interface the electrical components together and pair of solar panels to test
the final design. Finally, producing this product inherently consumes natural capital. First, each finished product will have a plethora of silicon-based electronics. As a result, silicon and
all the natural resources used to convert silicon into a usable electronic will be consumed.
Additionally, the weatherproof housing will likely be some type of plastic (ABS or PETG).
The majority of plastics are petroleum-based so this product would consume a non-renewable resource.
When and where do costs and benefits accrue throughout the project’s lifecycle?
As mentioned previously, the costs are largely upfront with development hours. Afterwards, the primary cost will be manufacturing the actual product. This cost will accrue as long as the product is sold. The financial and environmental benefits will be seen as soon as the product is finished and deployed in May 2020. Cal Poly students will immediately be able to test a variety of solar-tracking algorithms to determine which is the best for their specific application. This benefits the environment as more renewable energy will be produced.
What inputs does the project require? How much does the project cost? Who pays?
The inputs required in the project are development hours and specific hardware including sensors, and MCU, and a power driver. The total cost of the project is not expected to exceed $350.Additional equipment costs, including labor and overhead, equal $12,821.47.
How much does the project earn? Who profits?
The final project ultimately earns its worth through the additional power output. The system will be testing and determining ways to minimize inter-row shading. It will be an interface for users to continually test different methods to control panel movements. This project specifically will be used in a laboratory setting to help justify the Cal Poly and other solar farms to update their systems. As a result, the Cal Poly Solar Farm or any solar farm that is able to update their systems designed on the test system will profit in higher energy outputs. The project also encourages technological advancements from students and professionals in the solar production industry.
Timing
The completed project test system will emerge at the end of May 2020, and will function as long as the hardware and software components are still viable. Students aim to have a more approximate estimate of the external components’ life spans, including the test PV panels. In regards to software, as long as the C programming language is an industry level. Long term maintenance costs of the test system will include replacing the portable battery, maintaining external weatherproof housing, and keeping functionality of the display panel.
Original estimated development time (as of the start of your project), as Gantt or Pert chart
What happens after the project ends?
A successful project-end produces a unified algorithm running on a pair of solar panels that shows the benefits in terms of additional power output in a laboratory setting.
4. If manufactured on a commercial basis:
Estimated number of devices sold per year Estimated manufacturing cost for each device Estimated purchase price for each device Estimated profit per year
Estimated cost for user to operate device, per unit time (specify time interval)
The embedded system, once created, will be easy to use in a variety of two-panel test setups. Any customer looking to test a newly developed or existing algorithm to implement on a larger scale will find value in this product. With a viable and profitable proof of concept testing interface model, expectations include a high demand for the full embedded system so existing solar farms will have a way to test algorithms in a laboratory setting. Since there are about 2,500 US solar power plants, we expect to sell approximately 250 systems a year [6]. Based on the cost of parts and components, the system would cost approximately $13,001 to manufacture, minus the initial team labor, summing to approximately $761. In order to compensate the engineers properly and make a sizable profit the purchase price for each test system should cost at least $1000 for buyers. Thus, the profit per year would be $250,000.
5. Environmental
Describe any environmental impacts associated with manufacturing or use, explain where they occur and quantify.
Which natural resources and ecosystem services does the project use directly and indirectly? Which natural resources and ecosystem services does the project improve or harm?
The negative natural impacts occur when manufacturing the parts for the overall product. This primarily consists of fabricating the silicon components (microcontroller) and the LCD. Secondly, the weatherproof housing will most likely be made of ABS or PETG (primary weatherproof materials) which are both petroleum-based. The use of petroleum-based materials as well as creating silicon-based products will contribute to climate change as both these processes emit greenhouse gasses. However, the positive impact on the environment will outweigh the negative impact on the environment.
The impacts of this project will benefit the environment. By providing solar plants a way to test a variety of solar tracking algorithms before implementation on a large scale, the most efficient algorithm (in terms of power production) can be chosen. Choosing the right algorithm for the specific solar farm environment will drastically increase the overall power output. By increasing the overall power output, communities can rely more heavily on solar power instead of a nonrenewable energy source leading to lower greenhouse gas emissions.
Finally, this product may indirectly increase the proliferation of solar farms. Unfortunately, solar farms take space to employ. If more solar farms were created in natural habitats, it would displace the flora and fauna that currently live there. As a result, this product may indirectly cause displacement for some animal and plant life that live in sunny, flat areas.
6. Manufacturability
Describe any issues or challenges associated with manufacturing.
The bulk of the manufacturing process exists in creating the test bench interface for users to input their means of tracking angle. The challenges students foresee include defining the test system algorithm. It should be able to integrate a variety of user tests, be dynamic, and run tests independently. Once a set of algorithms has been tested, optimized, and finalized, future possible manufacturing costs will be related to external hardware.
7. Sustainability
Describe any issues or challenges associated with maintaining the completed device or system. Describe how the project impacts the sustainable use of resources.
Describe any upgrades that would improve the design of the project. Describe any issues or challenges associated with upgrading the design.
The final product is a customized embedded system. Once completed, the algorithm will be able to test user defined methods for reducing inter row shading. The goal of this project is to allow users to easily find ways to test power improvement methods on a small scale. Along with its limited external material usage, the project is aiming to maximize solar power sustainability. It aims to fully maximize solar farm power production. Upgrades to the system encourage optimization of mathematical models and new iterations of user tracker control. Challenges here would fall on the engineers during the modeling and refining process. This project’s sole customer base is existing solar farms. The test system promotes the possible building of solar farms by providing an efficient and low cost means to achieve optimal sustainable, renewable energy power outputs. Project will use a MSP432 microcontroller,
accelerometer, LCD display, and external housing system. These components, especially the electronics, have the capability to become e-waste. Students intend for the project to be used by future students to test panel algorithms. Should components reach the end of their lifetime, students will take care to properly dispose of or recycle these components at the end of the project lifetime. In addition, students aim to utilize a recyclable material for containment of test equipment to maintain a sustainable project.
8. Ethical
Describe ethical implications relating to the design, manufacture, use, or misuse of the project. Analyze using one or more ethical frameworks in addition to the IEEE Code of Ethics.
The first IEEE Code of Ethics states: “to hold paramount the safety, health, and welfare of the public, to strive to comply with ethical design and sustainable development practices, and to disclose promptly factors that might endanger the public or the environment.”
The purpose of the system is to test different algorithms in order to minimize carbon footprint by maximizing the power output of the corresponding solar farms. A possible misuse of this project is if the solar farm is powering a facility that is harmful to society. To accommodate the IEEE code of ethics, the implementation of the algorithm on solar farms will allow the facilities utilizing the power to be more sustainable. The system is also valuable for others to test different algorithms and understand the effects of shading and orientation of solar panels.
9. Health and Safety
Describe any health and safety concerns associated with design, manufacture, or use of the project.
If the system is unable to correctly execute the algorithm with the desired tilt, then potential safety risks may occur when implementing the algorithm on a physical solar farm. The lab system may work correctly, but it could be possible that on the physical solar farm, the algorithm responds differently. When designing, manufacturing, and using the system, it is imperative to follow lab safety guidelines. In addition, as previously mentioned in the Environmental section, manufacturing silicon and petroleum based products harm the environment. More directly, they harm the workers directly involved in the production process as they are closest to the chemical fumes these processes emit.
10. Social and Political
Describe social and political issues associated with design, manufacture, and use.
The direct stakeholders are Cal Poly’s students and faculty, specifically those who have an interest in solar energy. This laboratory Single-Axis PV Tracker will help students learn about common solar tracking principles as well as design and test new algorithms to track the sun. The possible social and political issues associated with the design, manufacture, and use of the system are among people that don’t support building solar farms on open land. The project directly impacts the users of solar energy by decreasing their energy costs and society by decreasing the overall carbon footprint. The indirect stakeholders are the entire San Luis Obispo community, who would benefit from higher community use of renewable energy. This could decrease dependencies on more expensive non-renewable energy.
11. Development
Describe any new tools or techniques, used for either development or analysis that you learned independently during the course of your project.
Upon the completion of this project, we expect to gain vast and intricate awareness and knowledge about mathematical modeling of a physical space. The first steps of our process include adapting data collection into a functional model. This model will translate directly into algorithm inputs as panel rotation magnitude and frequency of motion. We will also become familiar with testing methods for finding optimum frequency of rotation along with mathematical modeling of rotational optimization based on power supply of panel motors. These inputs surmise the algorithm’s bulk, where we will quickly become familiar with the algorithm and its inputs to be easily adjustable.
Additionally, we will learn how to create an embedded system that implements various levels of software. On the frontend, there will be a user interface with a variety of options to control two panels. On the backend, we have to program complex mathematics with limited processing power. Also, we must externally interact with an LCD screen which requires knowledge on basic communication protocols and with a motor relay which requires strict current requirements. As a result, the software will delve into user interface design, clever processing simplifications, and powerful and accurate current delivery.
APPENDIX B - LITERATURE SEARCH Book:
K. Jager, I. Olindo, et al. Solar Energy. Delft, ND: Delft University of Technology, 2014. This book explains the fundamentals of solar energy and solar panels. The book starts