University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2011 Design And Optimization Of A Wave Energy Harvester Utilizing A Flywheel Energy Storage System Steven Alexander Helkin University of Central Florida Part of the Computer-Aided Engineering and Design Commons Find similar works at: https://stars.edu/etd University of Central Florida Libraries http://library.edu This Masters Thesis (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact STARS@ucf. STARS Citation Helkin, Steven Alexander, "Design And Optimization Of A Wave Energy Harvester Utilizing A Flywheel Energy Storage System" (2011).
Electronic Theses and Dissertations, 2004-2019.edu/etd/1744 DESIGN AND OPTIMIZATION OF A WAVE ENERGY HARVESTER UTILIZING A FLYWHEEL ENERGY STORAGE SYSTEM by STEVEN ALEXANDER HELKIN B. University of Central Florida, 2009 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Mechanical, Materials, and Aerospace Engineering in the College of Engineering and Computer Science at the University of Central Florida Orlando, Florida Fall Term 2011 © 2011 Steven Helkin ii ABSTRACT This thesis details the design and optimization of a buoy used to collect renewable energy from ocean waves. The proposed buoy is a point absorber—a device that transforms the kinetic energy of the vertical motion of surface waves into electrical energy. The focus of the research is on the mechanical system used to collect the energy, and methods to improve it for eventual use in an actual wave energy harvester.
A flywheel energy storage system was utilized in order to provide an improved power output from the system, even with the intermittent input of force exerted by ocean waves. A series of laboratory prototypes were developed to analyze parameters that are important to the success of the point absorb mechanical system. By introducing a velocity-based load control scheme in conjunction with flywheel energy storage, it was seen that the average power output by the prototype was increased. The generator load is controlled via a relay switch that removes electrical resistance from the generator—this sacrifices time during which power is drawn from the system, but also allows the buoy to move with less resistance.
A simulation model was developed in order to analyze the theoretical wave absorber system and optimize the velocity threshold parameters used in the load control. Results indicate that the power output by the system can be substantially improved through the use of a flywheel energy storage control scheme that engages and disengages the electrical load based on the rotational velocity of the flywheel system. The results of the optimization are given for varying-sized generator systems input into the simulation in order to observe the associated trends. iii ACKNOWLEDGMENTS I am grateful for the continued support of the entire faculty and staff of the Department of Mechanical, Materials, and Aerospace Engineering at the University of Central Florida.
Kurt Lin has taught me much and offered great insight and help to me as both a researcher and as a student. I would also like to thank my fellow researchers and friends, Carlos Velez and Shiyuan Jin for their motivation and for all of the wonderful work they have done. I also would like to thank the Florida Energy Systems Consortium (FESC), the Harris Corporation, and Dr. Zhihua Qu for their financial support of the project presented in this thesis and their interest in renewable energy.
iv TABLE OF CONTENTS LIST OF FIGURES. viii LIST OF TABLES. xi LIST OF ACRONYMS/ABBREVIATIONS. xii CHAPTER ONE: INTRODUCTION.
1 Wave Energy Harvester. 2 Flywheel Energy Storage System. 6 Objectives of Research. 8 CHAPTER TWO: LITERATURE REVIEW.
11 Survey of Wave Energy Harvester Systems. 11 Survey of Intermittent Energy Storage Systems. 16 CHAPTER THREE: LABORATORY PROTOTYPE. 30 Method of Analysis.
38 v Addition of Flywheels. 39 Addition of Load Control. 40 Chain Tension Data. 44 Conclusions from Prototype Results.
46 CHAPTER FOUR: FLYWHEEL ENERGY STORAGE CONTROL SCHEME. 48 Discussion of Importance of Generator Load Control. 48 Control Scheme Parameters. 51 CHAPTER FIVE: SIMULATION APPROACH.
53 Objective of Simulation Model. 59 Mechanical System Model. 67 Implementation of Simulation. 78 Implementation of Optimization Scheme.
82 CHAPTER SIX: RESULTS AND DISCUSSION. 84 Simulation Optimization Results. 87 Discussion of Effects of Generator Parameters on Load Control Results. 92 Validation of Simulation Results.
93 vi CHAPTER SEVEN: CONCLUSION. 95 Impact of Current Research. 95 Suggestions for Future Research. 96 APPENDIX A: MATLAB CODE FOR BUOY SIMULATION MODEL CONFIGURED FOR LOAD CONTROL OPTIMIZATION.
99 APPENDIX B: MATLAB FUNCTION TO DEVELOP EQUATIONS OF MOTION. 104 APPENDIX C: MATLAB CODE TO GENERATE RANDOM WAVE INPUT. 111 vii LIST OF FIGURES Figure 1: Pelamis wave energy converter. 3 Figure 2: Conceptual point absorber illustration.
4 Figure 3: Florida Atlantic coast wave height data sample. 5 Figure 4: Basic conceptual design for point absorber system. 21 Figure 5: First generation laboratory prototype. 21 Figure 6: Second generation prototype conceptual design.
24 Figure 7: Pro/Engineer assembly design for second generation prototype. 25 Figure 8: Second generation laboratory prototype. 26 Figure 9: First alternative laboratory prototype using pulley and cable. 28 Figure 10: Second alternative laboratory prototype using rack-and-pinion.
29 Figure 11: Conceptual buoy wave farm array. 30 Figure 12: Sketch of conceptual point absorber design with vertical housing. 34 Figure 13: Image of motion platform with second generation prototype. 36 Figure 14: RPM vs.
time plot for system with three flywheels; no load control. 40 Figure 15: Experimental results of second generation prototype, ampltude 10cm and frequency 0.3 Hz, one flywheel, RPM-based load control. 43 Figure 16: Cable tension versus time for no electrical load and for controlled load; one flywheel. 44 viii Figure 17: Cable tension versus time for one, two, and three flywheels; load control applied.
45 Figure 18: Illustration of modified conceptual PTO design based on suggestions from results of laboratory prototypes. 47 Figure 19: Control scheme flow chart. 50 Figure 20: Buoy mathematical model block diagram. 58 Figure 21: Buoy forces illustration for mathematical model.
60 Figure 22: Illustration of pulley cross-section with applied torques. 68 Figure 23: Ginlong 500W-rated generator power vs. 71 Figure 24: Ginlong 500W-rated generator torque vs. 71 Figure 25: Schematic of ratcheting freewheel design.
73 Figure 26: Randomized wave surface profile with respect to time. 79 Figure 27: Fast Fourier transform of input wave spectrum. 80 Figure 28: Histogram of average power output by 100 runs of simulation ran for 100 cycles. 81 Figure 29: RPM versus time plotted for gear ratios of 0.0, and 10; 3500W generator with no load control applied.
85 Figure 30: Buoy vertical position versus time plotted for no load control and optimum load control; 20kW generator. 86 Figure 31: Surface plot, optimization results of avg. power versus upper and lower RPM thresholds, small 500W generator. 88 Figure 32: Surface plot, optimization results of avg.
power versus upper and lower RPM thresholds, medium 3500W generator. 89 ix Figure 33: Surface plot, optimization results of avg. power versus upper and lower RPM thresholds, large 20kW generator. 90 Figure 34: Surface plot, optimization results of avg.
power versus upper and lower RPM thresholds, very large 30kW generator. 91 x LIST OF TABLES Table 1: Second generation prototype results for various configurations; input amplitude 10cm and frequency 0. 42 Table 2: Relevant constants for hydrodynamic simulation model. 60 Table 3: Parameters for Ginlong generators used in simulation.
72 Table 4: Buoy characteristics and simulation parameters used in Matlab simulationError! Bookmark not define Table 5: Normal distribution parameters for randomized wave input. 78 Table 6: Simulation durations versus the standard deviation of average powers output for 100 runs of the simulation. 81 Table 7: Optimization results from simulation for varying generator size. 92 xi LIST OF ACRONYMS/ABBREVIATIONS CAD Computer-aided design DAQ Data acquisition FEA Finite element analysis FES Flywheel energy storage FFT Fast Fourier transform: A numerical algorithm used for signal processing Hz Hertz: a measurement of frequency equal to the inverse of a second PTO Power take-off: system through which power is generated Re Reynolds number: The non-dimensional ratio of viscous forces to inertial forces RPM Revolutions per minute SI International System of Units xii CHAPTER ONE: INTRODUCTION Renewable energy technologies became popular in the United States after the oil crisis of the 1970’s.
Since then, moderate success was found in both solar power and wind power methods. In fact, from July 2010 to July 2011, the United States saw an increase in renewable power generation by 5. However, advances in ocean energy technology have been much slower with only a handful of actual working systems found throughout the world, and even fewer in the United States [2]. In fact, the Renewables 2010 Global Status Report [3] considered ocean power production to be the ―least mature of the renewable energy technologies.‖ While solar and wind energy systems are generally implemented on land, ocean technology is limited to shoreline or offshore locations.
This presents severe challenges to the systems intended to extract energy via this method. Saltwater is very corrosive, and organisms can eat away from mechanical structures, a process known as biofouling [4]. Furthermore, not only can oceanic wildlife interfere with the systems, special precautions must be made to ensure that the systems do not harm the ecosystem; this challenge extends beyond just the local region—larger systems or systems in key locations can disrupt animal migration routes and ocean currents, having a substantial impact range on the environment. The difficulties of implementing ocean energy technology have limited progress in the field compared to other renewable energy sources: by the end of 2008, ocean power only accounted for about 300 megawatts produced worldwide, as opposed to photovoltaic systems with 13 gigawatts and wind power with 121 gigawatts [5].
1 This is unfortunate because of the tremendous energy potential available from the ocean— whether it is from ocean waves or currents. In fact, it is estimated that 2100 terrawatt-hours of total annual average wave energy are available along the United States coastline [6]; moreover, if only 0.2% of the energy available from the ocean worldwide is harvested, it would be sufficient to provide continuous power for the entire world [7]. Although more realistically, ocean power would be used in conjunction with other renewable energy resources to reduce the amount of fossil fuels used in power production. Wind, solar, and ocean energies have regions in which each is predominant; for instance, wind energy is abundant in the Midwest of the United States, solar is more readily available in regions closer to the equator, hydroelectric is generally limited to river locations, and ocean energy is found only near coastal regions.
It would be impractical to attempt to harvest only one form of renewable energy as each has its own geographic preference, and transmitting power long distances can become cost ineffective. As a result, ocean power production should be pursued not only because of its tremendous potential, but also because it is the more effective option for certain regions. By implementing systems to collect renewable energy, including ocean energy, the dependency of fossil fuels for power usage could be diminished or even outright eliminated. Wave Energy Harvester There are numerous methods to produce renewable power from the ocean, several of which are described in the Literature Review section of this paper.
This thesis details such a system to extract energy from ocean waves. This so-called wave energy harvester utilizes surface waves, 2 as opposed to water currents or thermal gradients within the water that some other systems use. There are still some variations in design when it comes to methods of drawing power from surface waves.