SOLAR AND THERMAL ENERGY SCAVENGING SYSTEM FOR LOW POWER SENSOR APPLICATION KO KO WIN (B. Eng.(Hons.), NUS, Singapore) A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF ENGINEERING DEPARTMANT OF ELECTRICAL AND COMPUTER ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2011 ACKNOWLEDGEMENTS First and foremost, I would like express my deepest gratitude to my supervisor A/P Sanjib Kumar Panda for his persistent help, advice, encouragement and providing me with this opportunity to pursue M.Eng. in the field of renewable energy. In addition, I would like to also express my heartfelt thanks to Research Scholar Mr Souvik Dasgupta for his support and concern for my research. I would also like to express my appreciation to Mr Woo Ying Chee and Mr. M. Chandra from the Electrical Machines and Drives Laboratory for assisting me with equipment and essential logistical support. Lastly, I would like to thank my fellow friends in the Electrical Machines and Drives Laboratory and Power Electronic Laboratory for their support and encouragement throughout the course of this project. Page ii Contents ACKNOWLEDGEMENTS .......................................................................................... ii Contents ....................................................................................................................... iii List of Figures ............................................................................................................. vii List of Tables................................................................................................................ xi List of Acronyms ........................................................................................................ xii List of Symbols .......................................................................................................... xiv Chapter 1 : Introduction ................................................................................................ 1 1.1 Background ......................................................................................................... 1 1.2 Literature review ................................................................................................. 3 1.3 Motivation of the research work ......................................................................... 6 1.4 Organization of the thesis .................................................................................... 7 Chapter 2 : Solar Energy Harvesting System ................................................................ 9 2.1 Solar panel characteristics ................................................................................. 12 2.2 Classification of solar panel .............................................................................. 16 2.2.1 Commercially available solar panel technologies ...................................... 19 2.2.1.1 Monocrystalline solar panel ................................................................. 20 2.2.1.2 Polycrystalline solar panel ................................................................... 21 2.2.1.3 Thin Film/Amorphous solar panel ....................................................... 22 Page iii 2.3 Solar panel selection .......................................................................................... 23 2.3.1 Evaluation of different types of solar panel ................................................ 24 2.3.2 Selection of the solar panel ......................................................................... 29 2.4 Selection of energy storage devices .................................................................. 30 2.5 Maximum Power Point Tracking circuit design ................................................ 31 2.5.1 Existing MPPT control algorithms ............................................................. 32 2.5.1.1 Perturb and Observe (P&O) ................................................................. 33 2.5.1.2 Incremental Conductance (INC) .......................................................... 35 2.5.1.3 Constant Voltage (CV) ......................................................................... 37 2.5.2 Selection of MPPT control algorithm ......................................................... 39 2.5.3 Implementation of Constant Voltage MPPT method ................................. 42 2.6 Start-up circuit for solar energy harvesting system ........................................... 51 2.7 Battery Overcharge Protection circuit design.................................................... 53 2.8 Experimental Results ......................................................................................... 56 2.8.1 Experimental validation of the maximum power point operation and efficiency of the solar energy harvesting circuit .................................................. 57 2.8.2 Field testing of the developed solar energy harvester with wireless sensor node in outdoor environments ............................................................................. 63 2.8.3 Experimental validation of the Battery Overcharge Protection .................. 65 Page iv 2.9 Summary ........................................................................................................... 68 Chapter 3 : Thermal Energy Harvesting System......................................................... 69 3.1 TEG characteristics ........................................................................................... 72 3.2 Characterization of the selected TEGs .............................................................. 75 3.3 Selection of MPPT control algorithm ............................................................... 78 3.4 Controller design to implement Constant Impedance Matching MPPT method ................................................................................................................................. 81 3.4.1 Selection of DC/DC converter .................................................................... 82 3.4.2 Simulating TEG load impedance using buck-boost converter to ensure MPPT ................................................................................................................... 84 3.4.3 Designing the circuit parameters to ensure MPP ........................................ 86 3.4.4 Design of square wave generator with adjustable duty ratio and frequency (adjusting Ts and D in the analog circuit) ............................................................ 87 3.5 Experimental Results and Analysis ................................................................... 88 3.5.1 Experimental validation of the maximum power point operation of the thermal energy harvesting circuit ........................................................................ 89 3.5.2 Efficiency of the thermal energy harvesting circuit.................................... 93 3.6 Summary ........................................................................................................... 95 Chapter 4 : Conclusions and Future Works ................................................................ 97 List of Publications ..................................................................................................... 99 Page v Bibliography.............................................................................................................. 100 Page vi List of Figures Figure 1-1: Conventional two-stage DC/DC converter MPPT circuit [6]. ................... 3 Figure 2-1: Conventional two-stage DC/DC converter MPPT circuit [7]. ................. 10 Figure 2-2: Block diagram of the proposed solar energy harvesting system. ............ 12 Figure 2-3: Creation of Electron-hole pairs by incident electromagnetic irradiation [21]. ............................................................................................................................. 13 Figure 2-4: Equivalent electric diagram of a solar panel ............................................ 13 Figure 2-5: Solar panel characteristics with solar intensity. ....................................... 15 Figure 2-6: Solar panel characteristics with solar panel temperature. ........................ 16 Figure 2-7: Examples of (a) Monocrystalline, (b) Polycrystalline and ....................... 20 Figure 2-8: Highly flexible thin-film amorphous silicon module [21]. ...................... 23 Figure 2-9: Solar panel characteristics and performance testing circuit. .................... 24 Figure 2-10: (a) AM-5605 (b) AM-8804 and (c) Custom made Polycrystalline solar panel. ........................................................................................................................... 25 Figure 2-11: Power (W) vs. Voltage (V) plot of the AM-5605 Sanyo Amorphous Solar Panel under varying solar insolation levels. ...................................................... 26 Figure 2-12: Power(W) vs. Voltage(V) plot of the AM-8804 Sanyo Amorphous Solar Panel under varying solar insolation levels. ................................................................ 27 Figure 2-13: Power (W) vs. Voltage (V) plot of the Polycrystalline Solar Panel under varying solar insolation levels. .................................................................................... 28 Figure 2-14: Showing MPP on solar panel characteristics plots: Power (W) vs. Voltage (V) and Current (A) vs. Voltage (V). ............................................................ 32 Page vii Figure 2-15: Perturb and observe (P&O) algorithm. .................................................. 34 Figure 2-16: Oscillations around PMPP when finding MPP using P&O algorithm. .... 35 Figure 2-17: Incremental conductance algorithm [43]............................................... 37 Figure 2-18: Constant voltage algorithm. .................................................................. 38 Figure 2-19: Solar panel output power curves under the different solar intensity conditions with Vref = 1.79V (red line) and VMPP (black line)..................................... 41 Figure 2-20: DC/DC boost converter as an input voltage regulator. .......................... 43 Figure 2-21: Implementation block diagram of constant voltage MMPT. ................. 45 Figure 2-22: Constant Voltage MPPT control circuit schematic diagram. ................ 46 Figure 2-23: Control operation of op-amps 2 & 3. .................................................... 48 Figure 2-24: Boost Converter voltage and current waveforms. .................................. 50 Figure 2-25: S882Z and DC/DC boost converter connection diagram. ...................... 53 Figure 2-26: Commonly available methods of clamping the battery voltage: (a) MOSFET needs low side driver; (b) MOSFET needs high side driver. ..................... 54 Figure 2-27: Battery overcharge protection circuit block diagram with the proposed solar energy harvester. ................................................................................................ 55 Figure 2-28: Simple threshold detector for battery protection circuit........................ 56 Figure 2-29: Experimental waveform showing PV voltage (Vpv), PV current (Ipv), Output voltage (VB) and Output current (Io) under solar insolation of 1000Wm-2. .... 59 Figure 2-30: Experimental waveform showing PV voltage (Vpv), PV current (Ipv), Output voltage (VB) and Output current (Io) under solar insolation of 400Wm-2. ...... 61 Figure 2-31: Power Distribution of the developed solar energy harvesting system at solar insolation of 1000Wm-2. ..................................................................................... 63 Page viii Figure 2-32: Real Time battery voltage data during the field testing. ........................ 64 Figure 2-33: Photograph of the developed prototype. ................................................ 65 Figure 2-34: Battery Simulator Circuit Diagram. ....................................................... 66 Figure 2-35: Experimental waveform showing Gate voltage (G1), PV voltage (Vpv), Output voltage (VB) and Output current (Io) under solar insolation of 1000Wm-2. .... 67 Figure 3-1: Schematic diagram of the proposed thermoelectric energy harvester for low power application. ................................................................................................ 71 Figure 3-2: Schematic of a thermoelectric generator. ................................................. 72 Figure 3-3: Equivalent electric diagram of a TEG. ..................................................... 73 Figure 3-4: Schematic diagram of the series connected thermoelectric generators for low power application. ................................................................................................ 76 Figure 3-5: TEGs characteristics and performance testing circuit. ............................. 77 Figure 3-6: Series connected 3 TEGs output power curves under the different ∆T conditions. ................................................................................................................... 78 Figure 3-7: Schematic diagram of the buck-boost converter as load impedance regulator in the proposed thermal energy harvester. ................................................... 81 Figure 3-8: Inductor current, iL, input current, ii, diode current, idiode, of buck-boost converter at DCM. ....................................................................................................... 84 Figure 3-9: Tunable frequency square wave generator with adjustable duty ratio. .... 87 Figure 3-10: Photograph of the developed thermal energy harvesting system. .......... 89 Page ix Figure 3-11: Experimental waveforms showing TEGs output voltage (vi), buck-boost converter output voltage (vo), TEGs output current (ii) and Gating signal (vG) under o ∆T = 24 C.................................................................................................................... 90 Figure 3-12: Experimental waveforms showing TEGs output voltage (vi), buck-boost converter output voltage (vo), TEGs output current (ii) and Gating signal (vG) under o ∆T = 28 C.................................................................................................................... 91 Figure 3-13: Experimental waveforms showing TEGs output voltage (vi), buck-boost converter output voltage (vo), inductor current (iL) and Gating signal (vG) under ∆T = o 24 C. ............................................................................................................................ 92 Figure 3-14: Experimental waveforms showing TEGs output voltage (vi), buck-boost converter output voltage (vo), inductor current (iL) and Gating signal (vG) under ∆T = o 28 C. ............................................................................................................................ 93 Figure 3-15: Power Distribution of the developed thermal energy harvester at ∆T = 24oC. ............................................................................................................................ 95 Page x List of Tables Table 1-1: Power Densities of Harvesting Technologies [2] ........................................ 2 Table 2-1: Comparison on efficiency for the different types of solar panel ............... 29 Table 2-2: Comparison between different MPPT techniques ..................................... 39 Table 2-3: Summary of power difference between at Vref and VMPP ........................... 40 Page xi List of Acronyms AC Alternating Current ADC Analog to Digital Converter BIPV Building Integrated Photovoltaic CCM Continuous Conduction Mode CIGS-CIS Copper Indium Gallium Selenide - Copper Indium Selenium CdTe Cadmium Telluride CV Constant Voltage CVD Chemical Vapour Deposition CZ Czockralski DC Direct Current DCM Discontinuous Conduction Mode DC/DC DC to DC DSC Dye-sensitized Solar Cell IC Integrated Circuit INC Incremental Conductance MPP Maximum Power Point MPPT Maximum Power Point Tracking MOSFET Metal–Oxide–Semiconductor Field-Effect Transistor NiCd Nickel Cadmium (NiCd) NiMH Nickel Metal Hydride (NiMH) Li+ Lithium based SLA Sealed Lead Acid Page xii NMOS N-channel MOSFET PMOS P-channel MOSFET PI Proportional-Intergral PMC Power Management Circuit P&O Perturb and Observe PV Photovoltaic PWM Pulse Width Modulation TEG Thermoelectric Generator Page xiii List of Symbols W Watts V Volts C Coulomb k Boltzmann‘s Constant q electron charge T Temperature ISC Short Circuit Current VOC Open Circuit Voltage Vpv Photovoltaic/solar output voltage Ipv Photovoltaic/solar output current Vo, Vout Output voltage VB ,VBAT Battery voltage Vin , Vi Input voltage Ii Input current Io Reverse saturation current Ip Photocurrent Ts Sampling/switching Period fs Sampling/switching frequency RL ,RLoad Load resistance Ri Input resistance Rs Series resistance ITEG Current generated by a thermoelectric generator Page xiv RTEG Internal resistance of a thermoelectric generator Rp Parallel resistance ∆T Temperature difference between hot and cold sides VTEG Voltage generated by a thermoelectric generator IMPP Current at Maximum Power Point VMPP Voltage at Maximum Power Point PMPP Power at Maximum Power Point Pin , Pi Input Power Pout , Po Output Power D Duty Ratio η Efficiency n Nano µ Micro m Milli k Kilo M Mega F Farads H Henry Ω Ohms Page xv Chapter 1 : Introduction In this Chapter, a brief evaluation of the different types of energy scavenging system such as energy extraction from solar and thermal energy sources for wireless sensor nodes used for condition monitoring applications are investigated. In this chapter, a brief survey on the present state of art technology in energy scavenging system for wireless sensor nodes is discussed and the motivation of the work is presented. The structure of this thesis is also portrayed in this Chapter. 1.1 Background Portable computing systems/devices are becoming increasingly popular and range from laptops, personal digital assistants (PDAs), and cell phones to emerging platforms such as wireless sensor networks. Recent advances in wireless communication technologies, sensors and integrated microelectronics technologies have shifted the onus on to the human imagination to find innovative applications to employ wireless sensor networks. It is not hard to imagine the use of such sensors to collect information from potentially hazardous environments, and remote locations. These sensors have become an indispensible aspect of condition monitoring applications such as smart homes/offices, buildings, automotive, etc. - to improve the human life-style. These sensors rely on electric power sources such as alkaline/rechargeable batteries to provide electrical energy on a sustained basis for effective operation. Due to the finite amount of stored energy in batteries, it is Page 1 necessary to replace/recharge the batteries in a periodic manner to ensure that the sensor node-life is extended. The replacement of batteries becomes a burden due to many sensor nodes being deployed in the field or difficulties to access the sensor nodes in certain environmental conditions. Hence, the portability of these devices is limited by the size of the energy storage elements rather than the computational power of the digital signal processor. Hence, available battery energy has become a critical resource for such systems. The real challenge for such low power portable electronic devices is to reduce or even eliminate the dependency on batteries and to be truly autonomous and self-sufficient with regards to energy generation and utilization. Recently, energy harvesting/scavenging from the environment has become one of the possible solutions to extend the life time of the wireless sensor nodes and has attracted wide research interest [1]. A variety of energy harvesting technologies is available and Table 1-1 shows some of the potential energy generating sources [2]. Table 1-1: Power Densities of Harvesting Technologies [2] Methods Power Density Solar cells 15mW/cm2 Piezo-electric 330W/cm3 Electromagnetic 116W/cm3 Thermo-electric 40W/cm3 Acoustic noise 960nW/cm3 Page 2 In order to address this challenge, energy harvesting technology has become an emerging research field that strives to reduce battery dependency for low power sensor applications. Reducing battery dependency can be achieved through improved energy conversion from previously untapped renewable energy as well as unwanted available energy sources such as solar, thermal, vibration etc. in the environment and also through improved and efficient storage facilities of the extracted electrical energy. 1.2 Literature review Various types of renewal energy sources such as solar, thermal, etc. can be investigated for powering the portable systems [1-13]. The research work on the energy harvesting of the portable system is drawn the prime importance among the researchers in the recent past. Figure 1-1: Conventional two-stage DC/DC converter MPPT circuit [6]. Page 3 The solar energy harvester reported in [3 - 7] describe the popular topologies 45 utilizing the power electronic converter for maximum power point tracking (MPPT) in the field of low power application. Brunelli et. al and Dondi et. al in [6] and [7] emphasize the usage of two-stage power management circuits for harvesting solar energy for wireless sensor nodes as shown in Figure 1-1. It consists of two stages namely buck converter and external DC/DC converter. The buck converter is employed to perform the MPPT with the highest possible efficiency, whereas external DC/DC converter is engaged to regulate the output voltage to match the load (wireless sensor node). It can be seen from Figure 1-1 that the MPPT control circuit has engaged one pilot cell to track the maximum power point of the main solar panel which is connected at the input of the buck converter. The MPPT in this arrangement may be erroneous due to the reason that the pilot solar cell and the main solar panel are subjected to different semiconductor characteristics. Nevertheless this arrangement also calls for extra foot print and sizing. Besides these, the drawback of such a two-stage scheme is comparatively lower overall power conversion efficiency due to power loss in each of the two stages of DC/DC converters. Besides these, two-stage power conversion circuits are also likely to have more circuit elements, resulting in larger circuit foot print. Additionally, it can be remarked that such two stages of the DC/DC converters may undergo mutual dynamic instability issues if not design properly. Power control circuit described in [3-5] relies on digital microcontroller based MPPT system. However, use of microcontroller for the control circuit calls for extra Page 4 power loss in the controller, analog to digital converter (ADC) and voltage as well as current sensors. Hence, the overall efficiency of the scavenging system for low power application is comparatively lower due to digital control system in power conversion unit. The proposition in [6- 9] shows an analog circuit based power management 8 circuit for solar energy harvesting. The cited papers present the solar energy harvester with very attractive power management features but the power consumed in the power management control circuitry is neglected. The thermoelectric energy harvesters are also playing a role in portable devices such as wireless sensors nodes and laptop power supply application [10]11-12[13]. The thermoelectric energy harvesters are relatively easier to implement to harvest any wasted heat in any plants or residential buildings to activate the smart sensor networks for smart environment monitoring. There are different energy harvesting techniques which are reported so far, can be seen in the cited papers, [14-20]. The most attractive way of harvesting maximum thermal energy is using the MPPT algorithms such as perturb and observe (P&O) algorithm [14 -16], constant 15 impedance algorithm [17] and [18] tracking method using a high performance low power consumption microcontroller. Nevertheless the usage of any kind of microcontroller results in significant energy loss in the energy harvesting system. Moreover the MPPT searching methods are quite computational intensive, need feedback sensors for voltage as well as current and use of ADCs. In [19] and [20], the authors have exercised analog practice to replace the microcontroller at the expense of Maximum Power Point (MPP) operation. It can also be noted from the cited papers Page 5 that the overall operation of the energy harvester is subjected to varying efficiency with the change of effective load of the system. Besides these, the loss of energy in computing devices as well as circuit elements leads to poor overall efficiency of the energy harvester and large circuit elements which leads to larger foot prints. 1.3 Motivation of the research work If the architectures of the cited energy harvesters are concerned, the circuits use two-stage power conversion, the first stage is dedicated for the MPPT tracking followed by the second stage to ensure voltage control. Since most of the control circuits of the harvesters are implemented with digital microcontrollers along with peripherals and sensors, the power consumption inside the harvester unit itself is increased. The microcontrollers are utilized to track the maximum power point using either P&O, incremental conductance (INC), or constant voltage (CV) or constant impedance method. In the present report, the extensive study has been carried out on different types of solar and thermal energy harvesting systems. The main focus of this report is to develop energy efficient solar and thermal energy harvesters for low power wireless sensor applications. In case of solar energy harvester, a one stage constant MPPT voltage method based energy harvester is proposed. The whole circuit is implemented with low cost and low power consumption analog integrated circuit (IC) to minimize the power loss Page 6 of the overall energy harvesting system. The proposed method also ensures high performance control of the power converter circuit with adequate band of accuracy. An efficient thermal energy harvester is also proposed in this report to track the maximum power point (MPP) of the thermoelectric generator (TEG). The energy harvesting circuit is also implemented using the analog integrated circuit. The main beauty of the proposed circuit lies in the open loop operation (without any sensors and ADCs) of the energy harvester. The proposed circuit can be tuned to different TEG samples based on their internal impedance, by characterizing the specific TEG sample. The proposed solar and thermal energy harvesting circuits are extensively verified with rigorous experiments under different operating conditions to show the efficacy of the overall system. 1.4 Organization of the thesis The thesis is organized as follow: Chapter 2 involves classification of different solar energy harvesting components based on the solar panel characteristics, DC/DC converter properties as well as different energy storage elements for the low power application such as wireless sensor nodes. The chapter deals with selection of solar panel, energy storage devices, power converters as well as control algorithms. A detailed analysis and experimental Page 7 validation of a novel analog implementation of the non-linear control system is provided. At the end of this chapter, a prototype test results are provided to test the feasibility of the field implementation of the overall solar energy harvesting system. Chapter 3 describes thermoelectric generator (TEG) application to harvest the electrical energy for the power supply of the wireless sensor nodes. The details of the chapter include TEG characterization, MPPT control algorithms and implementation details of the thermal energy harvesting system. A novel method of using low cost analog integrated circuit to implement accurate MPPT energy harvesting circuit is proposed. A detailed analysis and experimental validation of the proposed system is provided to support the efficacy of the proposed method. Chapter 4 concludes the thesis and discovers the scope of some future works that can be executed as an extension of this thesis. Page 8 Chapter 2 : Solar Energy Harvesting System Wireless sensor nodes are becoming more and more popular due to the technological advancements in the field of microelectronics technology and the development of ultra-low power microcontrollers that can be used in the embedded system. Wireless sensor network (WSN) consisting of several sensor nodes are used to monitor various parameters. The wireless sensor networks are commonly deployed in civilian and military applications such as natural disaster detection, healthcare system, traffic control system, building security system etc. [2] Batteries are commonly used to power wireless sensor nodes. Due to the finite amount of stored energy in batteries, it is necessary to replace/recharge the batteries in a periodic manner to ensure that the sensor node-life is extended. The replacement of batteries becomes a burden due to many sensor nodes being deployed in the field or difficulties to access the sensor nodes in certain environmental conditions. Recently, energy harvesting/ scavenging from the environment has become one of the possible solutions to extend the life time of the wireless sensor nodes and has attracted wide research interest [1]. From literature review, it can be seen that the research on solar energy harvesting using solar panel, also known as photovoltaic (PV) cells, for low power applications such as wireless sensor nodes has been carried out extensively. Page 9 Figure 2-1: Conventional two-stage DC/DC converter MPPT circuit [7]. However, as shown in Figure 2-1, most existing applications implement the solar energy harvesting using two stage DC/DC converters. The first DC/DC converter is used for MPPT implementation and the other one is used for the output voltage regulation [6 - 7]. Besides the need of two-stage converter, they also require the sensors to extract the PV panel‘s instantaneous voltage and current readings from a pilot PV cell (solar panel) to enable maximum power point tracking [6 - 7]. This Chapter presents a simplified solar energy harvester design which employs single stage DC/DC converter to perform both MPPT and the output voltage regulation. Furthermore, no additional sensors will be used to realize the selected MPPT method. A detailed study has been conducted to validate the proposed method. A prototype of the solar energy harvester has been built and tested. Figure 2-2 shows the block Page 10 diagram of the proposed solar energy harvesting system. The system consists of 5 main modules: (i) Solar Panel (Photovoltaic cells) (ii) A MPPT Controller Circuit (iii) A DC/DC Converter (iv) A Charge Pump Circuit (v) A ‗Battery Protection‘ Circuit In the following Sections, the solar panel characterization, classification and selection, energy storage device selection, MPPT method selection, MPPT circuit design, component descriptions, and principle of operation of the solar energy harvesting system are discussed comprehensively. Besides these, the experimental testing of the developed prototype and the results are also presented in this Chapter. Page 11 L1 VOUT = VBATT Vpv = Vin M1 C1 - Charge Pump VOUT MPPT Control Circuit M2 Schottky Diode C2 Zener Diode + + Wireless Sensor Node - Battery Protection Circuit Figure 2-2: Block diagram of the proposed solar energy harvesting system. 2.1 Solar panel characteristics A solar cell or photovoltaic cell is a device that converts sunlight directly into electricity by the photovoltaic effect. Photovoltaic is a method of generating electrical power by converting solar radiation into direct current electricity using specially designed p-n junctions that exhibit the photovoltaic effect [21]. When electromagnetic irradiation falls on such a junction, it transfers energy to an electron in the valence band and promotes it to the conduction band hence creating an electron-hole pair. The electrons and holes created can now act as mobile charge carriers and thus a current is produced [21]. This process across a p-n junction is shown in Figure 2-3. Page 12 Figure 2-3: Creation of Electron-hole pairs by incident electromagnetic irradiation [21]. To understand the electronic behavior of a solar cell, it is useful to create a model which is electrically equivalent, and is based on discrete electrical components whose behavior is well known. An ideal solar cell may be modeled by a current source in parallel with a diode; in practice no solar cell is ideal, so a shunt resistance and a series resistance component are added to the model [22]. The resulting equivalent circuit of a solar cell is shown in Figure 2-4. Rs Ip Rp Vpv RLoad + Id Ip Ipv - Figure 2-4: Equivalent electric diagram of a solar panel. Page 13 The solar panel‘s electrical characteristics under solar radiation can be represented by (2.1) given below [23]:   V pv  Rs I pv   V pv  Rs I pv V pv  Rs I pv   1  I pv  I p  I O exp   I p  Id  VT Rp Rp     (2.1) Ipv and Vpv are the output current and voltage of the solar panel respectively. The solar panel generates the photocurrent Ip, which is directly proportional to the solar irradiation. IO is the reverse-saturation current. VT = (nKT)/q is the thermal voltage, where n is the ideality factor, K is the Boltzmann constant, T is the panel temperature in Kelvin and q is the electron charge. Resistor Rs and Rp represents the losses incurred in the solar panel. The series resistor, Rs symbolizes the voltage loss in the path to the panel‘s external contacts primarily caused by the ohmic losses in the surface of the solar cell. The parallel shunt resistor Rp represents the losses due to leakage currents [24]. Rload denotes the load resistance. For an ideal solar panel, Rs is zero and Rp is infinitely large. Therefore Ipv can be simplified as shown in equation (2.2) below:   V pv     1 I pv  I p  I O exp  V   T   (2.2) Page 14 The short-circuit current of the solar panel is [24]: *  G  * I sc  I Sc  *    1 T  T  G  (2.3) The open circuit voltage of the solar panel is [24]:     * VOC  VOC   2 T  T *  I sc  I sc* Rs (2.4) G* and T* are the reference solar intensity and reference solar panel temperature respectively. I sc* and Vsc* are the short circuit current and voltage under the reference condition. As the internal resistances are neglected, equation (2.2) shows that the solar panel has non-linear output characteristics. Figure 2-5 and Figure 2-6 gives the current-voltage (I-V) and power-voltage (P-V) characteristic of a PV module for different level of solar radiation and temperature [22]. Figure 2-5: Solar panel characteristics with solar intensity. Page 15 Figure 2-6: Solar panel characteristics with solar panel temperature. Figure 2-5 and Figure 2-6 distinctly show that short circuit current is proportional to the solar radiation. Hence, great solar radiation means more current and greater output power. In addition, great solar radiation also leads the maximum power point to be located at a higher operating voltage. On the other hand, temperature is negatively related to the open-circuit voltage and output power. Higher temperature leads lower operating voltage and the output power decreases. This reveals the effects of ambient conditions of illumination and temperature on the maximum power point (MPP) and the optimal operating voltage. 2.2 Classification of solar panel Solar cell materials can be classified into three generations based on the type of material they are made from—crystalline, thin films. At present there is concurrent research into all three generations while the first generation technologies are most Page 16 highly represented in commercial production, accounting for 89.6% of 2007 production [25] . First generation cells are made up of crystalline silicon by means of vacuum deposition. It consists of single junction devices of large area and high quality. First generation technologies involve high energy and labor inputs which prevent any significant progress in reducing production costs. Single junction silicon devices are approaching the theoretical limiting efficiency of 33% [26] and achieve cost parity with fossil fuel energy generation after a payback period of 5–7 years [27]. The typical efficiency of solar panel is from 12% to 20%. Second generation is thin-film cell. The efficiency of this type of solar panel is relatively low, normally from 5% to 8%. The materials of this generation have been developed to address energy requirements and production costs of solar cells. Alternative manufacturing techniques such as vapour deposition, electroplating, and use of Ultrasonic Nozzles are advantageous as they reduce high temperature processing significantly. It is commonly accepted that as manufacturing techniques evolve production costs will be dominated by constituent material requirements [26], whether this be a silicon substrate, or glass cover. The most successful second generation materials have been cadmium telluride (CdTe), copper indium gallium selenide (CIGS), amorphous silicon and micromorphous silicon [25]. These materials are applied in a thin film to a supporting substrate such as glass or ceramics reducing material mass and therefore costs. These Page 17 technologies do hold promise of higher conversion efficiencies, particularly copper indium gallium selenide - copper indium selenium (CIGS-CIS), dye-sensitized solar cell (DSC) and CdTe offer significantly cheaper production costs. Among major manufacturers there is certainly a trend toward second generation technologies, however commercialization of these technologies has been proven difficult [28]. In 2007 First Solar produced 200 MW of CdTe solar cells making it the fifth largest producer of solar cells in 2007 and the first ever to reach the top 10 from production of second generation technologies alone [28]. Wurth Solar commercialised its CIS technology in 2007 producing 15 MW. Nanosolar commercialised its CIGS technology in 2007 with a production capacity of 430 MW for 2008 in the USA and Germany [29]. Honda also began to commercialize their CIGS base solar panel in 2008. In 2007, CdTe production represented 4.7% of total market share, thin-film silicon 5.2% and CIGS 0.5% [28]. Second generation technologies are expected to gain market share in the near future [25]. Third generation technologies aim to enhance poor electrical performance of second generation (thin-film technologies) while maintaining very low production costs. Current research is targeting conversion efficiencies of 30-60% while retaining low cost materials and manufacturing techniques [26]. They can exceed the theoretical solar conversion efficiency limit for a single energy threshold material, Page 18 that was calculated in 1961 by Shockley and Queisser as 31% under 1 sun illumination and 40.8% under maximal concentration of sunlight (46,200 suns, which makes the latter limit more difficult to approach than the former) [30]. There are a few approaches to achieving these high efficiencies including,  Multi-junction photovoltaic cell  Modifying incident spectrum (concentrator)  Use of excess thermal generation (caused by UV light) to enhance voltages or carrier collection.  Use of infrared spectrum to produce electricity at night 2.2.1 Commercially available solar panel technologies To further develop a better understanding of solar panel technologies, a brief survey of the existing solar cell technologies was done to learn more about the commonly available technologies and their performance were compared and evaluated for their suitability for implementation. There are various classifications for PV cell technologies [31]; they can be classified based on their thickness (thin vs. thick), crystalline structure (monocrystalline vs. polycrystalline vs. amorphous), junction types (homo junction vs. hetero junction), number of junctions (single vs. multi-junction) or application. In this thesis, the cell technologies will be reviewed based on their different structures: crystalline (first generation) and thin film/amorphous (second generation). The third generation thin film solar panels are Page 19 not compared with the other generations as it is not commercially available. Figure 2-7 shows three common types of solar cells which are commercially available in the market. (a) (b) (c) Figure 2-7: Examples of (a) Monocrystalline, (b) Polycrystalline and (c) Thin Film/Amorphous solar cells/panels [32 -34]. 33 2.2.1.1 Monocrystalline solar panel Monocrystalline solar panel uses pure single crystal silicon which the crystal structure is homogenous throughout the material; the orientation, lattice parameter, and electronic properties are constant throughout the material [35]. It is usually used for semiconductor devices. The purity of the silicon required is extremely high. Hence, it needs to manufacture using the Czockralski (CZ) method or the ‗Floatzone‘ process [21] to produce pure silicon cylinder. The silicon cylinder is then sliced and polished to obtain silicon wafers. In the slicing process, there is a considerable Page 20 amount of silicon wastage due to high quality wafer is required to produce the moncrystalline solar panel. Therefore, it leads to the manufacturing process expensive and its energy consumption relatively high. Currently the highest efficiency achieved for a monocrystalline solar cell is 25%. This was achieved in a laboratory of the University of New South Wales (UNSW). Commercialization attempts of the above mentioned achievements however have proven to be extremely difficult due to the complexity and high costs involved. Commercially available monocrystalline solar cells on the other hand operate at an efficiency of 15% on average [21]. 2.2.1.2 Polycrystalline solar panel Polycrystalline solar panel uses the silicon which is composed of many smaller silicon grains of varied crystallographic orientation. This material can be synthesized easily by allowing liquid silicon to cool using a seed crystal of the desired crystal structure or high temperature chemical vapour deposition (CVD) method. Polycrystalline solar cells are relatively cheaper than monocrystalline solar cells due to low cost manufacturing process. The manufacturing technique involves a casting method that yields large rectangular blocks which are subsequently sawed into smaller plates. However, during the solidification process of the material, crystals of varying sizes form and border defects emerges. These border defects lead to increased recombination of charge carrier at the grain boundaries and hence lower efficiencies [21]. Efficiency of commercially available polycrystalline solar cells is approximately Page 21 13% while the efficiencies of solar cells realized in the research laboratories reaches highs of around 20%. 2.2.1.3 Thin Film/Amorphous solar panel The modern day thin-film technology is based on amorphous silicon. Unlike crystalline variant discussed above, the silicon used in this case has very little order to the arrangement of the atoms hence the term ―amorphous‖ [21]. Thin film solar panel manufacturing process utilises lesser material and energy. Besides these, this technology does not require additional connections or packaging to deliver large solar panel as the required steps to make cell interconnections can be integrated into manufacturing process itself. Thus, it reduces the total cost of production compared to moncrystalline or polycrystalline solar panel. A thin-film amorphous silicon module can be highly flexible and malleable, like one shown in the Figure 2-8. Hence, amorphous thin film solar cells can be used as façade elements in buildings and design. A relatively recent but popular application is in window materials for Building Integrated Photovoltaic (BIPV), where PV coated windows allow excess sunlight to pass through while generating electricity. Page 22 Figure 2-8: Highly flexible thin-film amorphous silicon module [21]. However, thin film solar cells have the lowest efficiency among the three cell technologies discussed in this Section and this often become a deciding factor in solar cell selection. Commercially available amorphous thin film solar cells have efficiencies of only about 5-6% while laboratory efficiencies might achieve efficiencies of close to 13%. The low efficiency becomes an unfavourable trade off when crucial in areas where land is expensive or in applications where size and portability are key considerations. 2.3 Solar panel selection It is important to understand the performance and characteristics of the solar panel before designing the energy harvesting scheme [36] and [37]. In this Section, the solar panel characteristics and the performance of the most commonly available solar panel: polycrystalline and amorphous solar panel are compared. Page 23 Monocrystalline solar panel is not available in small sizes (less than 5W) and it is very expensive. Hence, monocrystalline solar panels are not being considered in this project due to lack of commercially available product. In order to compare the actual performance of the different types of solar panel, the output power of amorphous type and polycrystalline type solar panels have been recorded under the same solar intensity with different load conditions. 2.3.1 Evaluation of different types of solar panel As mentioned above, most commonly available solar panel: polycrystalline and amorphous solar panels are tested and compared the performance. An experiment with an experimental set up as shown in the Figure 2-9 below was carried out to obtain the I-V characteristic of the solar panels by varying the resistive load and further calculations were made to obtain their respective P-V characteristics. Solar Insolation A V RL Solar Panel Figure 2-9: Solar panel characteristics and performance testing circuit. Page 24 The experiment was conducted with the use of a solar light simulator and the characteristics of the solar panels were studied at 3 different solar light intensities, 500 Wm-2, 800 Wm-2 and 1000 Wm-2. Two commercially available amorphous solar panels were evaluated and comparisons were made between them before comparing with the output performance of the polycrystalline solar panel. Figure 2-11, Figure 2-12 and Figure 2-13 show the plots of the power (W) vs. voltage (V) graphs for the AM-5605 Sanyo amorphous solar panel, AM-8804 Sanyo amorphous solar panel and a custom made polycrystalline solar panel respectively under varying solar intensities. (a) (b) (c) Figure 2-10: (a) AM-5605 (b) AM-8804 and (c) Custom made Polycrystalline solar panel. Page 25 P-V Characteristics (AM5605 Sanyo Amorphous) 0.35 3.51V 0.3 3.69V 0.25 P (W) 0.2 3.84V 0.15 0.1 0.05 0 0 1 2 1000W/m2 3 4 Operating Voltage (V) 800W/m2 5 6 500W/m2 Figure 2-11: Power (W) vs. Voltage (V) plot of the AM-5605 Sanyo Amorphous Solar Panel under varying solar insolation levels. Page 26 P-V Characteristics (AM8804 Sanyo Amorphous) 0.16 5.27V 0.14 5.29V 0.12 0.1 P (W) 5.32V 0.08 0.06 0.04 0.02 0 0 1 2 1000W/m2 3 4 5 Operating Voltage (V) 800W/m2 6 7 8 500W/m2 Figure 2-12: Power(W) vs. Voltage(V) plot of the AM-8804 Sanyo Amorphous Solar Panel under varying solar insolation levels. Page 27 P-V Characteristics (Polycrystalline Solar Panel) 450 1.79V 400 1.76V 350 P(mW) 300 1.72V 250 200 150 100 50 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 Operating Voltage (V) 1000W/m2 800W/m2 500W/m2 Figure 2-13: Power (W) vs. Voltage (V) plot of the Polycrystalline Solar Panel under varying solar insolation levels. From Figure 2-11 to Figure 2-13, it can be seen that for the different solar panels, the maximum power point occurs at different operating voltage. It can also be seen that for the same solar panel, the different levels of insolation results in maximum power points move slightly along the operating voltage. Table 2-1 summarized the performance and efficiency of the three tested solar Page 28 panels. In order to make the data comparable, the sizes of the solar panels have to be taken into consideration. Hence, all the calculations are normalized into power density (Wm-2) in order to compare the efficiency of the solar panels. Hence, the performance and characteristics of the solar panel can be evaluated for the solar energy harvesting system. Table 2-1: Comparison on efficiency for the different types of solar panel Solar panel type Amorphous Amorphous Polycrystalline AM-8804 AM-5605 Panel size (mm x mm) 53 x 44.7 112 x 57 45 x 76 Solar intensity*( Wm-2) 1000 1000 1000 Max output power (mW) 139 307 405 Power Density * (Wm-2) 58.67 48.09 118.42 Maximum efficiency (%) 5.86 4.81 11.84 *Solar light intensity is set using solar light simulator 2.3.2 Selection of the solar panel As seen from the calculations results in Table 2-1, between the two amorphous solar panel variants the AM-8804 Sanyo amorphous solar panel has the higher power density than AM-5605 Sanyo amorphous solar panel. In terms of efficiency, AM8804 has about 1% higher efficiency than AM-5605. Subsequently, the performance comparison is made between the superior Page 29 amorphous solar panel (AM-8804) and the polycrystalline solar panel. The polycrystalline solar panel has the highest power density among tested amorphous solar panel. The power density of the polycrystalline solar panel is 100% more than the superior amorphous solar panel (AM-8804). The results are similar to the theoretical finding of the various types of the solar cell technologies summarized in the previous section. Therefore the polycrystalline solar panel is selected to use in this solar energy harvester for wireless sensor nodes due to power density and longer lifetime. 2.4 Selection of energy storage devices Since solar radiation is not available throughout the day, energy storage device is needed to support the power requirement of the wireless sensor nodes. There are two commonly available energy storage devices, namely batteries and ultracapacitors. Batteries are considered to have better performance in comparison with the ultra-capacitor due to low leakage and higher energy density. It should be noted that ultra-capacitors have higher power density as compared to that of the batteries. Commonly available rechargeable batteries are Nickel Cadmium (NiCd), Nickel Metal Hydride (NiMH), Lithium based (Li+), and Sealed Lead Acid (SLA). Due to the low energy density, SLA and NiCd are less commonly used. NiCd also suffers from temporary capacity loss due to the shallow discharge cycles. Hence, the choice of the battery is limited to Lithium based and NiMH. There are several factors Page 30 involved in selecting amongst these two batteries. Li+ has a longer life cycle and lower rate of internal self-discharge compared to NiMH. However, NiMH is cheaper than Li+ even after accounting for the increased life cycle of Li+ batteries. Besides, Li+ requires more stringent charging control mechanism than NiMH. Furthermore, charging of the Li+ at very low rates is not possible due to charge acceptance issues [3]. The internal resistance is relatively high in the Li+ battery compared to NiMH battery which leads to larger voltage drop under loading and eventually reducing the maximum current that can be drawn from the battery. The internal resistance keeps on increasing with charge cycle and chronological age of the battery [38] and [39]. For these reasons, NiMH batteries (2 x AA) are selected to use in wireless sensor node of the solar energy harvesting system. 2.5 Maximum Power Point Tracking circuit design According to solar panel characteristics mentioned in Section 2.1, the output power of the solar panel depends on solar intensity as well as its loading conditions. In order to achieve the maximum power output from the solar panel at a given solar intensity, the solar panel has to be correctly loaded and this operating point is called maximum power point (MPP) as shown in Figure 2-14 [21]. Operation at or around MPP harvests the maximum amount of solar energy from the solar panel which leads to energy efficient operation. Hence, to operate at MPP, the maximum power point tracking circuits need to be designed and implemented. In this Section, the existing MPPT methods are discussed and the method to attain MPP with the consideration of Page 31 low power consumption in MPPT circuit is proposed. Output Power (W) ISC P-V Characteristics I-V Characteristics MPP IMPP Solar Panel Current (A) PMPP VOC VMPP Solar Panel Voltage (V) Figure 2-14: Showing MPP on solar panel characteristics plots: Power (W) vs. Voltage (V) and Current (A) vs. Voltage (V). 2.5.1 Existing MPPT control algorithms There are different types of MPPT algorithms available [40]. However, in solar energy harvesting system, there are only three commonly used algorithms namely 1) Perturb and Observe (P&O), 2) Incremental Conductance (INC) and 3) Constant Voltage (CV). The other types of MPPT algorithms described in [40] are usually designed for other applications. Thus these algorithms are not considered. Page 32 2.5.1.1 Perturb and Observe (P&O) Perturb & Observe (P&O) algorithm creates an external or internal perturbation in the solar panel operating point and observes the trend in change of output power from solar panel to find the maximum power point. For example, triggering a change in operating duty cycle in pulse width modulation controlled power converters to change the solar panel operation voltage and observing whether the change caused positive or negative change in terms of power. If the output power increases, subsequent perturbation is carried out in the same direction, else the subsequent perturbation is carried out in the opposite direction [40]. The flow chart of the P&O algorithm is shown in Figure 2-15. Page 33 Set initial V(k), I(k), P(k) Measure V(k+1), I(k+1) Calculate P(k+1) P(k+1)=P(k) No Yes Yes V(k+1)>V(k) Increase VOP P(k+1)>P(k) No No Yes Decrease VOP Decrease VOP V(k+1)>V(k) No Yes Increase VOP V(k)=V(k+1) I(k)=I(k+1) Figure 2-15: Perturb and observe (P&O) algorithm. P&O algorithm is widely used because of its simple feedback structure and few measured parameters. Many low cost applications use this MPPT algorithm. However, one disadvantage of P&O MPPT algorithm is that it always results in oscillations around the MPP at steady state (shown in highlighted red portion in Figure 2-16) due to continuous perturbation of P&O algorithm. These oscillations cause loss in energy. Page 34 Output Power (W) PMPP VMPP Solar Panel Voltage (V) Figure 2-16: Oscillations around PMPP when finding MPP using P&O algorithm. 2.5.1.2 Incremental Conductance (INC) The Incremental Conductance method working based on the observation that, at MPP, , because the slope of the solar panel power curve is zero at the MPP, positive on the left of the MPP, and negative on the right of the MPP [41]. Theoretically, INC eliminates the oscillation about the MPP during steady state operation as it can find the MPP by computation. However, in practice is never satisfied due to noise, measurement and quantization problem. | usually used because the theoretical steady state is hard to achieve, where | is is a small positive number [42]. The algorithm of incremental conductance has been shown in Figure 2-17 [43]. And the conditions used for incremental conductance algorithm can be summarized as the following equations [41], Page 35 And since is given as: can be re-written as: Page 36 Figure 2-17: Incremental conductance algorithm [43]. 2.5.1.3 Constant Voltage (CV) The Constant Voltage (CV) algorithm keeps the operating point of the solar panel to near MPP by regulating the solar panel operating voltage, Vop to fixed reference voltage Vref. The Vref value is set equal to the best fitted VMPP of the characteristics of the solar panel. This method assumes temperature variations and Page 37 Vmp variations due to different solar insolation on the solar panel are insignificant, and that the constant reference voltage, Vref is an adequate approximation of the true MPP. Operation is therefore never exactly at the MPP and different data has to be collected for different solar panel to obtain the Vref. The flow chart of the Constant Voltage algorithm is shown in Figure 2-18. Set Reference Voltage Vref Measure Vop Yes Vop=Vref No Vop>Vref Yes No Decrease Vop Increase Vop Figure 2-18: Constant voltage algorithm. Page 38 2.5.2 Selection of MPPT control algorithm Table 2-2: Comparison between different MPPT techniques Perturbation and Incremental Observation Conductance Ease of implementation Moderate Moderate Simple Yields True MPP True MPP Approximate MPP Required sensing Current and Voltage Current and Voltage Voltage Resolution Oscillate around MPP Minor oscillations compared to P&O No oscillations Can be implemented by Digital controller Digital controller Digital/Analog controller MPPT Techniques Constant Voltage Faranda et. al [40] suggests that P&O and INC algorithms are the most effective algorithms in harvesting maximum output power from solar panel with up to 95% efficiency since they tracks the true MPP of the solar panel under any insolation level. However, the realization of either algorithm needs the micro-controller to compute and compare the power output or ∆P/∆V per cycle which significantly increases the complexity as well as the power consumption of the MPPT controller. Furthermore, both algorithms need current sensing in addition to voltage sensing of the solar panel which further increases the power consumption of the MPPT controller. Therefore both MPPT algorithms do not meet the objective of low power solar energy harvesting system. Table 2-2 shows a summary of the MPPT algorithms discussed. Page 39 Among MPPT algorithms, the constant voltage algorithm is the simplest and least energy consumption method for solar energy harvesting system. However, it needs the MPP voltage at different insolations to be closely placed in order to have maximum efficiency at all insolaion levels. Figure 2-19 shows the characteristics of the selected solar panel. From the Figure 2-19, it can be observed that the output power at the maximum power point increases with increase in solar intensity as it is marked by the black line. It can be noted from Figure 2-19 that the operating voltages at the maximum power point with different insolation levels are very close to each other. In the low solar intensity range, the voltage of maximum power point deviates from the voltage of maximum power point under high solar intensity. However, the power loss due to the operating voltage shifting is very low and it is illustrated in the Table 2-3 . Table 2-3: Summary of power difference between at Vref and VMPP Solar MPPT MPPT Power Power at Vref = Difference Difference Voltage (V) (mW) 1.79V (mW) (mW) (%) 500 1.72 216.6 213 3.6 1.6 800 1.76 328 324 4 1.2 1000 1.79 405 405 0 0 Intensity (Wm-2) Page 40 Power vs. Voltage (Selected Polycrystalline Solar Panel) 450 400 Output Power (mW) 350 300 250 200 150 100 50 0 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 Operating Voltage (V) 1000W/m2 800W/m2 500W/m2 Figure 2-19: Solar panel output power curves under the different solar intensity conditions with Vref = 1.79V (red line) and VMPP (black line). It can be observed from Table 2-3 that the maximum power can be obtained if the solar panel is operating around 1.79V at 1000Wm-2. For the lower insolation level 500Wm-2, the maximum power can be obtained around 1.72V. If the panel is operated at 1.79V with 500Wm-2, the power lost due to maximum power point mismatch is around than 3.6mW (1.6% of the output power at that insolation level). It Page 41 shows that the constant voltage algorithm is suitable for this particular selected solar panel because the MPP voltage deviation is small and mismatch power losses are smaller than 5%. Hence, it is not efficient (in terms of power consumed by control circuit and cost) to track the insolation level and adjust the MPP voltage according to solar intensity level. Therefore, the method to track the constant voltage is the best way for obtaining the maximum power point of the selected solar panel under the most solar intensity conditions. Therefore, the MPP is set around 1.79V for all insolation levels in our application. In the low power applications, this constant voltage method is preferred due to its simplicity, which can lower the power consumption of the control circuitry, even though a compromise has to be made on the accuracy of the maximum power point tracking. 2.5.3 Implementation of Constant Voltage MPPT method The constant voltage MPPT method intends to maintain the output voltage of the solar panel at a fixed voltage. This voltage would be chosen to ensure that even at varying solar intensities, the panel is operating close to the maximum power point. Therefore, this proposed controller functions as an input voltage regulator. The duty cycle of the DC/DC converter is controlled to maintain the input voltage, that is, solar panel output voltage, Vpv at a constant value. The constant voltage MPPT can be implemented using discrete analog integrated circuits (IC) to perform different logical activities to ensure efficient Page 42 operation of the circuit in implementing the MPPT. Boost and buck converter are the most attractive choices to track the maximum power point of the solar panel [3]. In this thesis, a boost converter is used (shown in Figure 2-20) due to the requirement of output voltage boosting (the solar panel MPP occurs at around 1.79V and batteries voltage is 3V). The other reason to choose a boost converter over a buck converter is that the former needs a non-isolated gate driver and the later needs isolated gate driver circuits. Under varying solar insolation levels, the constant voltage MPPT control circuit ensures that the solar panel operates close to 1.79V so that solar panel is operating around at MPP. The control circuit is implemented together with a DC/DC boost converter that basically performs as an input voltage regulator to constantly maintain the solar panel‘s operating voltage at 1.79V. IL Idiode Io L Ipv + + VL + - + VPV Diode D2 C1 Vi Solar Panel (or) Photovoltaic cells Isw G2 C2 Vo=VB Wireless Sensor Node with Battery S2 - - Figure 2-20: DC/DC boost converter as an input voltage regulator. Page 43 A simple conventional analog Proportional-Integral (PI) controller can be used to regulate boost converter input voltage which is the solar panel‘s operating voltage, Vpv to be 1.79V by controlling the duty cycle (D) of the boost converter if the system is linear. Based on the characteristic equations of an ideal boost converter [44], if the output voltage is constant, the input voltage can be controlled by the duty cycle: Vi  (1  D)  Vo (2.5) Vo 1  Vi (1  D) (2.6) Vo  f (D) Vi where function f D  is 1 . Equation (2.7) can then be re-written as: 1 D Vi  1 VO f D  Vi  vcVo where vC  1 f D  (2.7) (2.8) (2.9) , and the duty cycle D can be calculated as shown below: 1 D  f 1    vc  (2.10) Page 44 Since the system is nonlinear, the simple conventional Proportional-Integral (PI) controller is not able to control the solar panel‘s operating voltage, Vpv accurately. 1 It needs to include the non-linear feedback linearization block f 1   in the control  vc  loop so that the resulting control loop becomes linear and it will be able to regulate the solar panel‘s operating voltage, Vpv to be 1.79V as shown in Figure 2-21. V pv*   Kp  Vpv Ki s Op-Amp 1 vc u f 1 1   u D DC/DC Vi  Vpv Op-Amp 2 & 3 Figure 2-21: Implementation block diagram of constant voltage MMPT. The control system shown in Figure 2-21 can be divided into three parts as shown in Figure 2-22. The entire control system can be realized by three operational amplifiers (Op-Amps). Page 45 R2 VPV R6 C3 VDD Vx Rv1 + R1 OA1 R8 VDD Vy R3 VDD + Vz OA2 + - R7 Vref MPPT Circuit G2 OA3 VDD Vf R4 PI Control R5 C4 Feedback Linearization R9 PWM Generator Figure 2-22: Constant Voltage MPPT control circuit schematic diagram. The first op-amp realizes the PI controller as depicted in Figure 2-21 and Figure 2-22. It senses the input (solar) voltage, Vpv and compares it with the reference value. The reference signal, Vref / is provided by the built in precise reference generator of the op-amp MAX921 which used in battery protection circuit which is discussed in the later section. The ratio of the two resistances R1 and R2 decides the proportional gain and the capacitor C3 gives the integral gain. The potentiometer, Rv1 provides the precise setting of the operating voltage of the solar panel, Vpv. The implemented PI controller uses only one op-amp. So the relationship between the input and output is shown in equation (2.11). Due to single op-amp realization, the controller implements the PI control action added with the reference feed forward as shown in equation (2.11). The topology of the implemented controlled action not only reduces the power consumption in control circuit (due to single op-amp PI realization) but also facilitates reference feed-forward, making the control loop faster. Page 46 vC  VY  sR2C3  1  VX  VR   VR sR1C3 (2.11) Applying Kirchoff‘s current law at the negative terminal of the op-amp 2 and using virtual short phenomenon while applying R3 = R6 the following equation is derived. VZ  2V f  VY (2.12) The operation done by op-amp 2 can be expressed by equation (2.12). Maintaining (referred to the equation (2.12)), the feedback linearization operation (1-D) is done in op-amp 2. The control timing diagram of realizing the feedback linearization block is shown in Figure 2-23. The last op-amp 3 generates the PWM signal with duty cycle proportional to the input voltage Vz. The frequency of the PWM signal is determined by R9 and C4. For this implementation different parameters of the circuit shown in Figure 2-2 are taken as R1 = R2 = 1MΩ, R3 = R6 = 39kΩ, R4 = R5 = 1MΩ, R7 = 3.9kΩ, R8 = 47kΩ, R9 = 15kΩ, C3 = C4 = 3.3nF and VDD = 2.8V (Battery Voltage). Page 47 Voltage Vy VB VB – Vy = Vz (1-d)Ts Time dTs d= 1-D Time DTs G2 (1-D)Ts Time Figure 2-23: Control operation of op-amps 2 & 3. PI controller and feedback linearization is implemented with ultra-low power Operational Amplifier MAX4289 which is optimized for ultra-low applications. The Pulse Width Modulation (PWM) is implemented with low power comparator NCS 2220A. It only requires a very low supply current of 0.75 µA per comparator. MAX4289 and NCS2220A come in a very small footprint surface mount (SuperSOT – 6 and UDFN8 respectively) feature to minimize the size of the printed circuit board (PCB). Since the entire Constant Voltage MPPT method is implemented using only ultra-low power Op-Amps, the power consumption of the controller is very low (less than 300µW). Page 48 The switch, N-MOSFET used in the DC/DC Boost Converter shown in Figure 2-20 is the FDC6327C which is a Dual N & P-Channel 2.5V Specified Power MOSFET, designed to offer exceptional low threshold voltage, Vth(turn on) = 0.9V, low turn on resistance, RDS(ON) =0.12 Ω @ VGS = 2.5V, and fast switching speed. It comes in a very small footprint surface mount (SuperSOT – 6) feature to minimize the size of the printed circuit board (PCB). The typical voltage and current waveforms of a boost converter in continuous conduction mode (CCM) are shown in Figure 2-24. As seen from Figure 2-24, when the MOSFET switch of the boost converter is in the ―ON‖- state, the current through the inductor increases and built up the energy stored in inductor, L. When the switch is off, current through the inductor L continues to flow via the diode D, to the remaining of the circuit. In other words, the inductor acts like a pump, receiving energy when the switch is closed and transferring it to the RC network when the switch is open. As seen from Figure 2-24, the current supplied to the output of the circuit is discontinuous. Therefore a capacitor is required to smooth the output voltage ripple. This capacitor must also provide the output dc current to the wireless sensor node‘s battery when diode D is off. As such there is a theoretical minimum capacitor value for the circuit to deliver the desired output voltage performance; this value can be calculated from the following equation (2.14). Page 49 CMIN  DVO Vrp Rf (2.14) where D is the duty cycle, Vo the output voltage, Vrp the ripple voltage, R the load resistance and f is the switching frequency. Switch State Ts DTs ON OFF ON OFF Voltage t VO VI VL Current t IL t Current Isw Idiode t Figure 2-24: Boost Converter voltage and current waveforms. Page 50 2.6 Start-up circuit for solar energy harvesting system The power management circuit of the solar energy harvesting system has to be capable of starting up its operation independently without any power drawn from the connected loads or additional power supply so that there is no limitation on the load (loads can be with/without any energy storage devices or loads which are not possible to access their internal energy storage device). A charge pump is the device which enables this start up feature as it does not need the power supply to operate. Basically charge pump is a kind of DC/DC converter which uses capacitors as energy storage elements to create either higher or lower voltage power source [45]. Charge pumps employ some form of switching devices to control the connection of voltages to the capacitor. For example, in order to generate a higher voltage, the first stage of the charge pump operation involves the capacitor being connected across a voltage source like solar cell or thermoelectric modules and charged up. Subsequently the capacitor is disconnected from the original charging voltage source and reconnected with its negative terminal to the original positive charging voltage source. As the capacitor is able to retain the voltage across it (assuming leakage effects are insignificant), the positive terminal voltage is now added to the original voltage. Hence, the output voltage of the charge pump is effectively doubled the original voltage. Depending on the controller and internal circuitry of the charge pumps, in general the charge pumps are capable of doubling, tripling or fractionally multiplying Page 51 voltages. Hence, the charge pump is an ideal device to be integrated into the solar energy harvester design to enable the start-up of the power management circuit to function independently of the additional power source. S882Z ultra-low voltage operation charge pump is selected as it is designed for boost converter start-up and the input voltage range is 0.3V to 3V. It is utilized to provide the start-up power requirements of the power management circuit‘s components. Thus enabling the power management circuit to be used for charging of devices where power cannot be drawn from the loads/batteries. The charge pump accomplishes this by storing the electric power from the solar panel into a start-up capacitor before discharging it as start-up power to the boost converter when the discharge start voltage level is reached. In addition, it has a built-in shutdown function which can be activated once the output voltage level of the connected DC/DC boost converter rises above the required value to power up the power management unit, thereby allowing for significant power savings. Once the S882Z is inactive, the power management circuit (i.e. MPPT control circuit components) draws their supply power from the output of the DC/DC boost converter, VOUT. Figure 2-25 shows the connection between the charge pump and the DC/DC boost converter. Page 52 Figure 2-25: S882Z and DC/DC boost converter connection diagram. 2.7 Battery Overcharge Protection circuit design Since there is no battery charging converter/controller existing in the solar energy harvester, the overcharge protection circuit is needed to stop the charging of the load‘s battery when it reaches the predefined voltage level. The power consumption should be in a few hundreds of µW. There are a few options to make the battery from charging continuously when the battery voltage reached the cut-off voltage as explained later. Placing the MOSFET in Figure 2-26 (a) & (b) can resolve the overcharging problem of the battery. However in both cases, it needs an isolated MOSFET driver as S1 of the MOSFET is floating. Besides the driver, it needs the zener diode to act as the load when the switch is open. Zener diode has to be selected such that breakdown voltage is slightly higher than battery cut-off voltage. The drawback of this configuration is that MOSFET driver consumes a few mA current. Besides this, Page 53 there is a conduction power loss due to MOSFET when the battery is charging. Power consumption of this configuration is not suitable for low power applications. + Vpv VB D1 G1 Zener Diode Boost Converter D1 G1 Boost Converter S1 VB Zener Diode + Vpv S1 - Vpv - Vpv (a) (b) Figure 2-26: Commonly available methods of clamping the battery voltage: (a) MOSFET needs low side driver; (b) MOSFET needs high side driver. Design of the solar energy harvesting circuit consisting of all the proposed features (MPPT, battery overcharging protection) is shown Figure 2-27. The proposed approach is to place the MOSFET parallel with the boost converter MOSFET. When the battery voltage reaches the cut-off voltage, the MOSFET 1 (M1) turns on to short the solar panel. Hence, the battery no longer gets charged as input source has been shorted. This configuration does not require the additional device such as MOSFET driver and zener diode. This configuration is suitable for the solar panel with short circuit current of less than a few amperes. This particular configuration saves a remarkable amount of harvested power to be lost in the drivers and MOSFET if it were configured as in Figure 2-26. Page 54 It can be seen from Figure 2-27 that the battery protection MOSFET (M1) is placed in parallel with PV panel and the boost converter. However, an alternative option may be to place M1 in series with the panel and the boost converter. But in the later configuration the circuit undergoes power loss across M1 while battery is charged, decreasing the efficiency as well as the later case needs the high side drive for the MOSFET. Thus, the scheme shown in Figure 2-27 is beneficial over the other well-known methodologies as discussed above. VOUT = VBATT Vpv = Vin + Sola r Pan e l D1 - G1 S1 M1 Boost Converter with MPPT and Charge Pump + Wireless Sensor Nodes Battery Protection Circuit Figure 2-27: Battery overcharge protection circuit block diagram with the proposed solar energy harvester. Desired battery cut-off voltage can be easily detected by using simple Op-Amp. Figure 2-28 shows that if the battery voltage is more than desired cut-off voltage, , G1 produces high and the MOSFET 1 (M1) shorts the panel. Hence, the solar panel is disconnected from the rest of the circuit and protects the load/battery which is connected to the converter from overcharging/over voltage. Page 55 Solar panel is connected back to the rest of the circuit if the output voltage of the boost converter falls below the predefined cut-off voltage value. The ultra-low power comparator MAX 921 is used as threshold detector. MAX 921 provides the additional features such as internal reference voltage which is used as reference voltage to compare the battery/output voltage and to supply as a reference voltage to MPPT circuit. MAX 921 also provides an external hysteresis features which is used to provide the better comparator noise margin by increasing the upper threshold and decreasing the lower threshold level. VBAT = Vout Vout RA + RB G1 Vr - Figure 2-28: Simple threshold detector for battery protection circuit. 2.8 Experimental Results The prototype of the designed solar energy harvester is developed and its performance has been tested under different operating conditions using solar light simulator as well as real outdoor environments. The experiment is carried out with Page 56 the selected polycrystalline solar panel (< 400mW) due to its suitability for low power application such as wireless sensor node, power requirements and physical size. In order to validate the maximum power point operation of the solar energy harvesting circuit, the prototype is connected to a load: - 2xAA NiMH rechargeable batteries used in wireless sensor nodes. The MPPT accuracy and efficiency of the system are analyzed and discussed in Section 2.8.1. Subsequently, the developed prototype is connected to crossbow wireless sensor node and put it under the outdoor environment together with the same type of wireless sensor node without the solar energy harvester to compare the actual performance between them. The performance result and comparison are presented in following Sections 2.8.2. Finally the experimental validation of the battery protection circuit is carried out using the load simulator. The results and discussions are presented in Section 2.8.3. 2.8.1 Experimental validation of the maximum power point operation and efficiency of the solar energy harvesting circuit The developed prototype is put under the solar light simulator with the load (2xAA rechargeable batteries) using the selected solar panel while maintaining the solar panel temperature at around 400C. Figure 2-29 shows the experimental waveforms of the photovoltaic (PV) panel output voltage Vpv, PV panel current Ipv, output voltage, VB and output current, Io under 1000Wm-2 insolation (the insolation is Page 57 created artificially using solar light simulator). It can be noted from Figure 2-29 that the input power coming out of the PV panel (power input to the boost converter) at 1000Wm-2 is equal to: It can also be calculated that the power output of the boost converter at 1000Wm-2 is equal to: Thus, efficiency, , of the solar energy harvesting device at 1000Wm-2 can be calculated to be It can also be observed from Figure 2-29 that the solar panel voltage is tracked at 1.79V which is the maximum power point voltage of the PV panel designed to be track at all insolation level with constant voltage of 1.79V. Page 58 Ipv (50mA/div) Vpv (0.5V/div) Ipv =218mA Vpv =1.79V io (50mA/div) Io = 119mA Vo =2.86V Vo = VB (2V/div) Figure 2-29: Experimental waveform showing PV voltage (Vpv), PV current (Ipv), Output voltage (VB) and Output current (Io) under solar insolation of 1000Wm-2. Figure 2-30 shows the same set of experimental results as Figure 2-29 with the only change in the solar insolation level. During the experimental test for Figure 2-30, the solar insolation is maintained at 400Wm-2. It can be observed from Figure 2-30 that the input power coming out of the PV panel (power input to the boost converter) at 400Wm-2 is equal to: And the power output of the boost converter at 400Wm-2 is equal to: Page 59 Thus, efficiency, , of the solar energy harvesting device at 400Wm-2 can be calculated to be: From the Figure 2-30, it can also be observed that the solar panel voltage is also tracked to 1.79V in this insolation level of 400Wm-2. Hence, MPPT circuit is maintaining the solar panel output voltage at the constant voltage of 1.79V regardless of the solar insolation level. This validates that constant voltage MPPT method is successfully implemented with high efficiency. Page 60 Vpv (0.5V/div) Ipv (50mA/div) Vpv = 1.79V Ipv = 97mA io (20mA/div) Io = 57mA Vo = 2.84V Vo = VB (2V/div) Figure 2-30: Experimental waveform showing PV voltage (Vpv), PV current (Ipv), Output voltage (VB) and Output current (Io) under solar insolation of 400Wm-2. The 60 - 65% of the total power loss is mainly due to schottky diode in the boost converter. The forward voltage drop of the schottky diode is around 220mV at 90mA and 285mV at 120mA. From Figure 2-30, it can be observed that for the total power loss is 49.12mW, 34.2mW of the total loss is due to the schottky diode, 15.28mW is switching power loss and inductor power loss and 0.4mW is due to ICs, resistors and capacitors losses. Hence, the solar energy harvester efficiency is varied from 87% (at 1000 Wm-2) to 93% (at 400 Wm-2) due to the variation of the voltage drop across the schottky diode for different battery charging currents. The Figure Page 61 2-31 shows the power distribution of the developed solar energy harvesting system at the solar insolation level of 1000Wm-2. The way to reduce the voltage drop across the schottky diode is to make use of active MOSFET, where voltage drop is around 100mV irrespective of current flowing through the MOSFET. In this case, the overall efficiency of the solar energy harvester goes up to 95% (typical charging current of the test condition is 120mA). However, when there is a discontinuous conduction mode (DCM) operation of the boost converter, the inductor current is observed to go to negative due to bi-directional channel present in the MOSFET. Because of the variation of the solar intensity, the duration of the DCM operation of the boost converter is unpredictable. Hence, MOSFET is not used as permanent solution to replace the schottky diode. Page 62 Power Distribution at solar insolation of 1000Wm-2 0.08% 3.33% 0.44% 8.72% 87.44% Load Diode MOSFET Control Circuit Others Figure 2-31: Power Distribution of the developed solar energy harvesting system at solar insolation of 1000Wm-2. 2.8.2 Field testing of the developed solar energy harvester with wireless sensor node in outdoor environments The solar energy harvester prototype is connected to crossbow wireless sensor nodes and placed in the outdoor environment together with the same type of crossbow wireless sensor node. Both wireless sensors nodes (with and without solar energy harvester) are programmed to senses the voltage of the battery, temperature and light intensity every second. The information is transmitted to the base station where data are logged for more than 880hrs for every second. The average power Page 63 consumption of each wireless sensor node is about 65mW. Figure 2-32 shows the battery voltage of the crossbow sensor nodes with and without solar energy harvester. It can be seen from Figure 2-32 that the sensor node without the solar energy harvester lasts for around 150hrs (6.25 days). The sensor node which has been integrated with a solar energy harvester has been able to maintain for at least 880hrs (36.67days), subsequently the experiment has been terminated. But it is anticipated that if the experiment could have been continued for long time, the sensor node should be able to self-sustain theoretically for infinite period of time. Figure 2-33 shows the developed prototype of the solar energy harvesting system for wireless sensor nodes. 3 2.8 Voltage (V) 2.6 2.4 2.2 2 1.8 0 100 200 300 400 500 600 700 800 900 Hours Solar & Battery Power Battery Power Figure 2-32: Real Time battery voltage data during the field testing. Page 64 Crossbow Sensor Node Solar Panel Power Management Circuit Figure 2-33: Photograph of the developed prototype. 2.8.3 Experimental validation of the Battery Overcharge Protection It can be understood that during the process of experimentation, battery overcharge phenomena occurs in the battery to show the successful overcharge protection property of the harvesting circuit. However, the battery used for the experiment is Ni-MH battery and it takes long time to reach to its overcharge state. So a real time simulation is done to imitate the overcharge phenomena of the battery. The circuit imitating the overcharge phenomena is shown in Figure 2-34. Page 65 Figure 2-34: Battery Simulator Circuit Diagram. It can be seen from the Figure 2-34 that two DC power supply are connected in series to simulate the battery overcharging phenomena. In Figure 2-34, voltage source V1 = 2.6V and V2 = 0.5V are added (opening the switch, M3) to give the overcharged condition of the battery. On the other hand, when M3 is closed, V2 is shorted (goes to current control mode) to give the normal charging condition of the battery. The battery overcharge protection circuit block diagram is shown in Figure 2-27. The experimental result showing the overcharging phenomenon is pointed in Figure 2-35. It is depicting the experimental waveform of the Gate voltage (G1), PV voltage (Vpv), Output voltage (VB) and Output current (Io) under consecutive simulated charged and overcharged condition. It can also be noticed from Figure 2-35 that during the condition when Vo is greater than 2.9V, the solar panel is shorted (Vpv = 0) by enabling the Gate signal (G1= 1). It can also be observed that when Vo is less Page 66 than 2.9V, MPPT operation is active; leading to the charging state of the battery (G1=0). Vo = VB (2V/div) G1 (2V/div) Vo >2.9V & G1 = 1 M3 is open Vo= 2.9V & G1 = 1 Vpv (1V/div) Io (50mA/div) Figure 2-35: Experimental waveform showing Gate voltage (G1), PV voltage (Vpv), Output voltage (VB) and Output current (Io) under solar insolation of 1000Wm-2. Page 67 2.9 Summary A prototype of solar energy harvesting using only one DC/DC converter with high performance analog control is implemented and experimentally validated. The developed solar energy harvesting circuit extracts the maximum power (using constant voltage MPPT) available from the PV panel to charge the battery under different insolation conditions. It provides quite high overall efficiency (up to 93%) while implementing the advanced control strategy using analog devices only. The power consumption of the control circuit is less than 300µW. The experimental results show the efficacy of the proposed solar energy harvester. Overall it can be remarked that the proposed solar energy harvester can be considered to be a viable solution for low power (5mW-400mW) energy harvesting application due to ultralow power consumption of the control and protection circuit. Page 68 Chapter 3 : Thermal Energy Harvesting System Thermoelectric generator (TEG) is a solid state device which produces electric energy when there is a thermal gradient between its surfaces. Recently, the developments in TEG have resulted in energy harvesting/ scavenging from the environmental heat to become one of the possible solutions to eliminate the need of battery or extend the battery life time of the low power devices such as the wireless sensor nodes and has attracted wide research interest [10-13]. A TEG can be modelled as a voltage source in series with internal resistance [14]. The open circuit output voltage of the TEG is proportional to the temperature gradient. As a result, the generated power is varying, not constantly available and limited which leads to the need of power management circuit (PMC). The core functions of the PMC are to provide stable power to the load and also to extract maximum power from the TEG. A mismatch between the generated and the consumed power can be resolved by an energy storage device such as a capacitor or a rechargeable battery. To extract maximum power from TEG, some DC/DC converters have been investigated [15], [19-20]. Several well-known MPPT algorithms such as perturbation and observation (P&O), incremental conductance, and approach using TEG characteristics (impedance matching) have been applied in TEG [14-15] and [16-18]. In literature [14], [16]-[18], the implementations of the MPPT algorithms require the micro-controller circuit to compute either the output power or impedance of TEG. Hence these implementations require the voltage and current feedback from Page 69 either/both TEG (input) or/and load/battery (output). The drawback of such implementation is that it makes the power consumption of the power management circuit (PMC) large (a few mW) due to digital computation, voltage sensing and current sensing. This leads to the low power (less than 10mW) harvester operating at maximum power point (MPP), very less efficient or nearly makes it impossible to operate at MPP as harvested power from TEG is lower than power consumption of the PMC. Besides, PMC leaves a larger footprint and also becomes expensive due to components such as micro-controllers and feedback sensors. The constant impedance (approach using characteristics of TEG) matching MPPT circuit for low power thermal energy harvesting system is presented in this Chapter. Unlike the traditional TEG MPPT methods implemented in [14], [16]-[18], the implementation of the proposed MPPT method does not require any microcontroller to compute either power or impedance. Hence, it also does not require the voltage or current feedbacks from either input or output side to perform the MPPT. Therefore, the proposed MPPT method significantly reduces the power consumption of the PMC to less than one mW. In order to further minimize the energy consumption in the PMC, the proposed ultra-low power (less than 250µW) MPPT circuit is realized using discrete analog components only. The details of the proposed constant impedance matching MPPT circuit for thermoelectric energy harvesting system has been shown in following sections. Figure 3-1 shows the schematic diagram of the proposed thermoelectric energy harvester for low power application. Page 70 To prove the efficacy of the proposed technique, a prototype of an economical low power thermoelectric energy harvesting system has been built and tested. In the following sections, the TEG‘s characteristics, characterization of the selected TEG, MPPT circuit design, component descriptions and principle of operation of the thermal energy harvesting system are discussed comprehensively. Besides these, the experimental results of the developed prototype are presented in this Chapter too. Idiode Ii DC/DC Converter + Vi TEG IL L Vo Load s D RL(or)Ri G MPPT Circuit Figure 3-1: Schematic diagram of the proposed thermoelectric energy harvester for low power application. Page 71 3.1 TEG characteristics Thermoelectric generator (TEG) is a device that converts thermal energy (heat) directly into electricity by Seebeck effect. Seebeck is a method of generating electrical power by converting heat into direct current electricity using Seebeck based devices which used bimetallic junctions which are bulky while more recent devices use specially designed bismuth telluride (Bi2Te3) p-n junctions that exhibit the Seebeck effect [46]. Hence, thermoelectric generators are made by connecting many of such thermocouples (p-n junctions) electrically in series and thermally in parallel as shown in Figure 3-2 [47]. Figure 3-2: Schematic of a thermoelectric generator. Page 72 TEGs are solid state devices, consist of no mechanical parts, and require little regular maintenance. Its long term stability and reliability even allows it to be employed in deep-space research, where it has been used in Radioisotope Thermoelectric Generators for long term power generation. However, TEGs are limited by their low efficiency and specific power density, lowering its performance in already inefficient low ∆T energy harvesting applications. Still, the stability and reliability of TEGs favour it for mobile low power applications. To understand the electronic behavior of a TEG, it is useful to create a model which is electrically equivalent, and is based on discrete electrical components whose behavior is well known. An ideal TEG may be modeled by a voltage source with a series resistance, RTEG of the TEG [14], [48-49]. The resulting equivalent circuit of a TEG with the load is shown in Figure 3-3. RTEG ITEG + VG = S × ∆TTEG VTEG RL - Figure 3-3: Equivalent electric diagram of a TEG. Page 73 The TEG‘s electric characteristics under ∆T (temperature different between the two surfaces of the TEG) can be represented by the equation below [49]: VG = S × ∆TTEG = n × α (THJ − TCJ ) (3.1) where VG is the open circuit voltage of the TEG, S is the Seebeck coefficient of the TEG, n is the number of electrically connected thermocouples in series, α is the Seebeck coefficient of the thermocouples, THJ is the junction temperature of the hot side of TEG and TCJ is the junction temperature of the cold side of the TEG. (3.2) where ITEG is the output current of the TEG, RTEG is the internal resistance of the TEG and RL is the electrical load resistance. The output power, PL, delivered by the TEG to the load, RL, can be expressed as: (3.3) From the above equation, it can be easily seen that the output power, PL, is dependent on both the TEG internal resistance, RTEG and the resistance of the load, RL. According to maximum power transfer theorem, the maximum power can be obtained when the load resistance RL matches the internal impedance of the TEG, RTEG. Hence, maximum output power, PMPP, of the TEG can be expressed as: Page 74 (3.4) Due to the ohmic voltage drop across its internal resistance, RTEG, during the operation of the TEG, the output voltage of the TEG is reduced. Therefore, the output voltage of the TEG at its maximum power point, VMPP, is always half of the TEG‘s open circuit voltage, VG (VG = 2 VMPP) and the maximum power changes with temperature difference as . 3.2 Characterization of the selected TEGs TEGs (6mm x 24mm x 2.6mm) from Thermonamic Electronics (Jiangxi) Corp. Ltd. is selected to use in the experimental setup. Open circuit voltage of each TEG is 0.25V at ∆T of 20oC. Since output voltage of TEG is low, three TEGs have been connected in series to provide the higher open circuit voltage in the experimental setup. It is important to find the characteristics of the TEG for designing the energy harvesting scheme using impedance matching method [17] and [18]. In order to characterize the series connected three TEGs, a generic setup has been fabricated in the lab environment as shown in Figure 3-4. The internal impedance of the series connected three TEGs is found to be 35Ω and open circuit voltage is 0.75V at ∆T of 20oC. Page 75 Heat Sink TEG 1 TEG 2 TEG 3 Hot Plate Figure 3-4: Schematic diagram of the series connected thermoelectric generators for low power application. In this Section, the series connected TEGs are tested in order to see the actual performance of it, the output power of the series connected TEGs has been recorded under the different ∆T conditions with different load conditions. An experiment with an experimental set up as shown in the Figure 3-5 was carried out to obtain the I-V characteristic of the TEGs by varying the resistive load while maintaining the same temperature difference between the two surfaces and further calculations were made to obtain their respective P-R characteristics. Page 76 A TEG1 TEG2 V RL TEG3 Figure 3-5: TEGs characteristics and performance testing circuit. The experiment was conducted with the use of a hotplate and the characteristics of the TEGs were studied at 4 different ∆T conditions, 14oC, 20oC, 26oC and 31oC. Figure 3-6 shows the plots of the power (mW) vs. load resistance (Ω) graphs for the series connected 3 TEGs under varying ∆T conditions. From Figure 3-6, it can be seen that the output power of the TEG varies under different loading conditions as well as different temperature gradient (∆T) between the two surfaces. From Figure 3-6, it can also be seen that for the different ∆T conditions, the maximum power points occurs at about the same load resistance. Page 77 Characteratics of TEGs (3 connected in series) at Different ∆T 18 31oC 16 14 Power (mW) 12 10 26oC 8 6 21oC 4 2 14oC 0 0 50 100 150 200 Load Resistance (Ω) Figure 3-6: Series connected 3 TEGs output power curves under the different ∆T conditions. 3.3 Selection of MPPT control algorithm As can be seen from literature [10], [11], [17]-[18] as well as from Figure 3-6, the output power of the TEG varies under different loading conditions as well as different temperature gradient (∆T) between the two surfaces. In order to achieve the maximum output power from the TEG at a given temperature gradient across its surfaces, the TEG has to be correctly loaded or operated at MPP. Page 78 There are three commonly used maximum power point tracking (MPPT) algorithms, namely Perturb & Observe (P&O) method, Incremental Conductance (INC) method and approaches using TEG characteristics such as impedance matching and half open circuit voltage tracking. The detailed working principles of P&O and INC have been presented in Section 2.5.1. P&O and INC are widely adopted methods with applications in renewable energy and energy scavenging applications [10], [11], [17]-[18] and [50]. P&O and INC need voltage and current information to recursively compute and compare the power and conductance respectively. Hence, their design relies on feedback sensors and digital computation adding to the power loss, rendering them unsuitable for low power harvesters. As a consequence, P&O and INC MPPT algorithms are not considered for implementation in low power thermoelectric energy harvesting system. As seem from Figure 3-6, under the same temperature difference between the two surfaces, the output power of the TEG can be varied by changing the load resistance terminated at the TEG. It can also be observed from Figure 3-6 that the output power at the maximum power point increases with increase in ∆T as it is marked by the black line in Figure 3-6. In order to accurately attain the maximum power points shown in Figure 3-6 for different temperature differences (∆T conditions), a digital controller should be used Page 79 along with feedback sensors. Therefore, it would need additional power consumption due to the complexity and hence it should be avoided. It can be noted from Figure 3-6 that the load resistance of the TEG at maximum power point with different ∆T conditions is very close to each other. While at ∆T = 20oC, the resistance required to extract maximum power is 35Ω, an increase in ∆T by 11oC results in a meager increase in required resistance by 1Ω. If the TEGs are loaded with 35Ω at ∆T = 31oC, the power loss due to maximum power point mismatch is less than 150µW (1% of the output power at that ∆T level). Hence, it is not efficient (in terms of power and cost) to track ∆T as the typical power consumption of the ultra-low power microcontroller is around (1mW) and power losses due to the feedback sensors are around (1mW). It is proposed that constant impedance matching is to be implemented in MPPT of TEG despite the loss in accuracy, owing to an increase in net power harvested. In this paper, the load impedance is kept fixed at 35Ω which by maximum power transfer theorem implies that the TEG can be modeled as source with an internal impedance of 35Ω. The following Section details the implementation of the constant impedance matching method which matches the TEG internal input impedance with the load impedance (RL) which is the input impedance (Ri) of the DC/DC converter. Page 80 3.4 Controller design to implement Constant Impedance Matching MPPT method The constant impedance matching MPPT method intends to maintain the load impedance (RL or Ri) to be the same as TEG internal impedance. The impedance value would be chosen to ensure that even at varying ∆T, the TEG is operating close to the maximum power point. Therefore, this proposed controller functions as TEGs load impedance (RL or Ri of Figure 3-7) regulator. Idiode Ii DC/DC Converter + RTEG Vi VG IL L Vo Load - TEG s D RL(or)Ri G MPPT Circuit Figure 3-7: Schematic diagram of the buck-boost converter as load impedance regulator in the proposed thermal energy harvester. DC/DC converters are used to track the MPP by varying the load impedance (RL or Ri) seen by the source through imposing changes to the duty ratio of the MOSFET. In other words, DC/DC converter matches load impedance (RL or Ri) to be equal to that of the source. Amongst DC/DC converters, buck, boost and buck-boost Page 81 converters are the most attractive choices to track the maximum power point of the TEG [15], [17]-[20]. 3.4.1 Selection of DC/DC converter In this TEGs application, the internal impedance is considered as constant; however this does not mean that a constant duty cycle in buck and boost DC/DC converter can ensure MPPT. Conventional method of matching impedance relies on sensing voltage and current. MPPT can be achieved with a constant duty ratio only in the case of buck-boost DC/DC converter in discontinuous conduction mode (DCM) as discussed below. In continuous conduction mode of buck, boost and buck-boost converters, it cannot achieve arbitrary input impedance (Ri) matching of the converter with TEG source impedance (RTEG) with constant duty cycle owing to static relation of input and output voltage. In DCM, both buck and boost have a static relationship among input and output voltages along with output current and duty cycle. Thus input impedance matching is also not possible under these operating conditions. In the next Section, it is mathematically shown that buck-boost converter, if operated in DCM, provides the characteristics of arbitrary input impedance (Ri) matching with internal input impedance (RTEG) of TEG by only controlling the duty cycle at the specific switching frequency. Page 82 However, operation of buck-boost converter in DCM offers some other additional advantages over the other topologies and configurations of the DC/DC converters for this specific application on low power thermoelectric energy harvesting system. For specific low power thermoelectric energy harvesting application, the operating current at maximum power point is in the range of few mA. Hence, operating in DCM, enables to select the lower value of inductance resulting in lesser space, lesser loss in inductor. The additional advantage of the DCM operation of buck-boost is that the transient of the circuit (MPPT) only persists in the first switching cycle leading to fast dynamic. In the present application, the need of the high side driver for the N-channel MOSFET is eliminated by using the P-channel MOSFET placing at the bottom as shown in Figure 3-7. Page 83 3.4.2 Simulating TEG load impedance using buck-boost converter to ensure MPPT iL Ip t Ts ii Ip t DTs idiode Ip (1-D)Ts t Figure 3-8: Inductor current, iL, input current, ii, diode current, idiode, of buckboost converter at DCM. Considering the terminologies of input and output currents and voltages as shown in Figure 3-7, typical DCM electrical conduction waveforms can be illustrated as shown in Figure 3-8. Figure 3-8 shows inductor current, iL, input current, ii, diode Page 84 current, idiode under DCM operation. If input current, ii is considered, the maximum input current, Ip can be expressed as: (3.5) where L is the inductor, Vo is the output voltage, D is the duty ratio, Vi is the input voltage and Ts is the switching period of the DC/DC converter. From equation (3.5), average input current, Ii , can be expressed as: (3.6) It can be seen from equation (3.6) that input impedance offered by the DC/DC converter for the TEG can be expressed as: (3.7) Ri is the simulated impedance designed to track the maximum power from the TEG. From the experimental data given, the source impedance of the TEG is found to be 35Ω. Now duty ratio, D, inductance L, and the switching time period Ts are adjusted in such a way that the simulated value of Ri matches with the source impedance, RTEG, of TEG to ensure the maximum power output from TEG (using maximum power transfer theorem). Page 85 3.4.3 Designing the circuit parameters to ensure MPP From (3.7), selection of D and L are critical to ensure the DCM operation of the buck-boost convert as well as input impedance matching. An average input current, Ii of the buck-boost converter in terms of output voltage, Vo (because in this specific application the output voltage is kept constant by the battery) can be expressed as: (3.8) (3.9) In order to ensure DCM operation at all the time, , where Iib is the input boundary current and Ip is the maximum possible input current of the buck-boost converter at the peak operation of TEG. Solving the (3.9) provides the duty ratio, D, range. By setting the D and Ts in (3.7) provides the inductance values as input impedance of the converter, Ri is equal to the source internal impedance. Hence, designing the gating/PWM circuit with the calculated value of L, D and Ts provide the maximum power extraction. For the selected TEGs, the internal impedance, RTEG = 35Ω and the output voltage, Vo=2.8V (maintain by a battery to be charge) and maximum input current, o Iimax = 50mA at ∆T = 50 C. Hence, Ri = 35Ω and input boundary current, , must be greater than or equal to 50mA. By using the (3.9), D must be less than 61%. Hence, selecting the Ts = 100µs and D = 35%, and solving the equation (3.7) gives, L = Page 86 214µH. Hence, the actual duty ratio, D = 65% as the MOSFET which is used in the buck-boost converter is P-channel. 3.4.4 Design of square wave generator with adjustable duty ratio and frequency (adjusting Ts and D in the analog circuit) Figure 3-9: Tunable frequency square wave generator with adjustable duty ratio. Figure 3-9 shows the square wave generator with tunable frequency and duty ratio. The frequency of square wave output of this circuit is controlled by C1, R5 and R7. In other words, varying the C1, R5 and R7 tunes the frequency of the square wave. The duty ratio is defined by R2. The high frequency ultra-low power comparator, Page 87 Max919, is used to realize the constant gating signal with desired switching frequency with constant duty ratio. For this implementation, different parameters of the circuit shown in Figure 3-9 are taken as R1 = R3 = 10kΩ, R4 = R6 = 1kΩ, R2 = 1MΩ, R5 = up to 1MΩ, R7 = up to 1MΩ, C1 = 0.1µF and VBAT = 2.8V (Battery Voltage). The circuit is tuned in such a way that the switching frequency, fs is set to about 10kHz. 3.5 Experimental Results and Analysis The prototype of the designed thermal energy harvester is developed and its performance has been tested under different operating conditions using hotplate. The experiment is carried out with the selected TEGs (series connected 3 TEGs) due to its suitability for low power application such as wireless sensor node, power requirements and physical size. In order to validate the maximum power point operation of the thermal energy harvesting circuit, the prototype is connected to load, - 2xAA NiMH rechargeable batteries which is used in wireless sensor nodes and detailed experimental results are shown in Section 3.5.1. Subsequently, the efficiency of the system is analyzed and discussed in this Section 3.5.2. Figure 3-10 shows the developed thermal energy harvesting system. Page 88 TEGs Power Management Circuit Figure 3-10: Photograph of the developed thermal energy harvesting system. 3.5.1 Experimental validation of the maximum power point operation of the thermal energy harvesting circuit Figure 3-11 and Figure 3-12 show the experimental waveforms of the TEGs output voltage vi, TEGs output current, ii, the output voltage of the buck-boost o converter, vo and the gating signal of the buck-boost converter, vG under ∆T = 24 C o and 28 C respectively (the heat is generated artificially using a hotplate). Page 89 vi = 0.5V (0.5V/div) vo = 2.83V (2V/div) ii (50mA/div) Ii = 14.1mA vG (2V/div) Figure 3-11: Experimental waveforms showing TEGs output voltage (vi), buckboost converter output voltage (vo), TEGs output current (ii) and Gating signal o (vG) under ∆T = 24 C. From Figure 3-11 and Figure 3-12, it can be noted that the duty cycle of the buck-boost converter is maintained at 65% at the switching frequency of 10kHz regardless of ∆T conditions. It can also be noted from both Figure 3-11 and Figure 3-12 that the input impedance of the buck-boost converter is maintained at o (∆T = 24 C) and o (∆T = 28 C). Page 90 Figure 3-13 and Figure 3-14 show the TEGs output voltage vi, the output voltage of the buck-boost converter, vo and the gating signal of the buck-boost o o converter, vG and the inductor current, iL at ∆T = 24 C and 28 C respectively. From Figure 3-13 and Figure 3-14 it can be observed that buck-boost converter is operating at discontinuous conduction mode. vi = 0.6V (0.5V/div) vo = 2.83V (2V/div) ii (50mA/div) Ii = 16.8mA vG (2V/div) Figure 3-12: Experimental waveforms showing TEGs output voltage (vi), buckboost converter output voltage (vo), TEGs output current (ii) and Gating signal o (vG) under ∆T = 28 C. Thus the experimental results show that constant impedance matching maximum power point tracking method is achieved by DCM operation of buck-boost Page 91 converter with fix duty ratio with constant switching frequency regardless of the thermal conditions (∆T conditions). vi = 0.5V (0.5V/div) vo = 2.83V (2V/div) iL (50mA/div) IL =16.1mA vG (2V/div) Figure 3-13: Experimental waveforms showing TEGs output voltage (vi), buckboost converter output voltage (vo), inductor current (iL) and Gating signal (vG) o under ∆T = 24 C. Page 92 vi = 0.6V (0.5V/div) vo = 2.83V (2V/div) iL (50mA/div) IL = 19.7mA vG (2V/div) Figure 3-14: Experimental waveforms showing TEGs output voltage (vi), buckboost converter output voltage (vo), inductor current (iL) and Gating signal (vG) o under ∆T = 28 C. 3.5.2 Efficiency of the thermal energy harvesting circuit It can be noted from Figure 3-11 that the input power coming out of the TEGs (power input to the buck-boost converter) is equal to: (@ ∆T = 24oC) Page 93 From Figure 3-13, it is noticed that the power output of the buck-boost converter is equal to: (@ ∆T = 24oC) Thus, efficiency, η, of the thermoelectric energy harvester can be calculated as: (@ ∆T = 24oC) It should be mentioned here that the efficiency calculation here takes care of not only the energy conversion efficiency of the buck-boost converter but also keeps the records of energy requirement of the control circuit. The total power loss of 20% from the input harvested power is investigated to reside in different components of the buck-boost converter. Rigorous calculations show that about 10% power loss is aggregated across the schottky diode of the buckboost converter. The rest 10% power loss occurs across the MOSFET (switching and conduction losses) of the buck-boost converter because of the DCM operation of the circuit. The Figure 3-15 shows the power distribution of the developed thermal energy harvesting system at the ∆T=24oC. Page 94 Power Distribution at ∆T 24oC 5.40% 4.46% 1.42% 8.72% Load Diode MOSFET 80.00% Control Circuit Others Figure 3-15: Power Distribution of the developed thermal energy harvester at ∆T = 24oC. 3.6 Summary This Chapter proposed and implemented a low cost, more efficient, compact thermal energy harvester for low power applications. A novel method of tracking the maximum power point of TEG using the maximum power transfer theorem is proposed. The proposed constant impedance matching scheme with buck-boost converter operating at DCM simplifies the circuitry thereby eliminating the need for micro-controller and feedback sensors to calculate the impedance. It also helps to reduce the power loss due to micro-controller and its associated peripherals. The proposed MPPT circuit consumes less than 250 µW for control and driver circuit leading to the high power transfer efficiency (up to 82%). Experimental results are Page 95 provided to test thermoelectric energy harvester under different operating conditions leading to the success of the proposed method. Overall it can be remarked that the proposed thermal energy harvester can be considered to be a viable solution for low power (0.5mW-20mW) energy harvesting application due to ultra-low power consumption of the control circuit. Page 96 Chapter 4 : Conclusions and Future Works This thesis is directed towards design, analysis and implementation of energy harvesting system for low power application. The present thesis focuses on mainly two different renewable energy sources, namely solar and thermal energy. In the first part of the thesis, a detailed method of selection of the solar panel, a DC/DC converter topology and control algorithm is provided. A novel method of tracking maximum power point of the solar panel is investigated and a low cost analog integrated circuit implementation is provided. The proposed method is validated under different operating conditions and experimental results are provided to validate the idea. A novel start up start-up circuit and battery protection circuit are designed to effectively interface the solar panel, power converter and load under different environmental transients. A prototype validation over a certain period of field test is provided to ascertain the commercial viability of the product. In the second part of the thesis, powering up the wireless sensor node using thermal energy harvester is studied. The feasibility of the proposed system is verified with the rigorous experimental results under different operating conditions. A new method of open loop maximum power point tracking of the TEG system is proposed. The proposed system is shown to be quite accurate even implemented in open loop with analog devices. The proposed system is also low cost because of the absence of current and voltage sensors as well as digital micro-controller. The proposed method is also described to be a smallest possible TEG system in terms of device foot print as Page 97 well as components counts. The implementation method also ensures lowest possible overall power loss in the power conversion path as well as decision making circuit. A prototype development of the proposed system is executed and the proposed idea is ready for market commercialized application. Although a thorough analysis and implementation are discussed on the solar and thermal energy harvesting devices for low power applications, a lot of future research possibilities can be investigated as discussed below. It can be seen from the analysis and implementation provided so far, each of the solar and thermal energy harvesting needs different type of DC/DC converters as well as control strategy because of the obvious difference in the MPP characteristics. However, it is very hard to put separate system to power the same sensor node to facilitate the both solar and thermal energy harvesting. A method can be investigated so that a single converter and associated control strategy can work on both system to harvest the electrical energy with the highest possible device utilization and efficiency. Page 98 List of Publications 1. Ko Ko Win, S. Dasgupta, S. K. Panda, “An Optimized MPPT Circuit for Thermoelectric Energy Harvester for Low Power Applications’,” in proc. Of IEEE International Conference on Power Electronics (ICPE), Korea, May 30-June 3, 2011. 2. Ko Ko Win, X. H. Wu, S. Dasgupta, Jun Wen Wong, R. Kumar and S. K. Panda, “Efficient Solar Energy Harvester for Wireless Sensor Nodes,” at IEEE International Conference on Communication Systems (ICCS), Singapore, pp. 289-294, Nov. 17-19, 2010. Page 99 Bibliography [1] S. Roundy, “Energy scavenging for wireless sensor nodes with a focus on vibration to electricity conversion”. Ph. D. Dissertation, Dept. of EECS, UC Berkeley, May 2003. [2] T. Voigt, H. Ritter, J. Schiller, "Utilizing solar power in wireless sensor networks," 28th Annual IEEE International Conference on Local Computer Networks, 2003. LCN '03. Proceedings., pp. 416- 422, 20-24 Oct. 2003. 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Page 107 [...]... to develop energy efficient solar and thermal energy harvesters for low power wireless sensor applications In case of solar energy harvester, a one stage constant MPPT voltage method based energy harvester is proposed The whole circuit is implemented with low cost and low power consumption analog integrated circuit (IC) to minimize the power loss Page 6 of the overall energy harvesting system The proposed... brief evaluation of the different types of energy scavenging system such as energy extraction from solar and thermal energy sources for wireless sensor nodes used for condition monitoring applications are investigated In this chapter, a brief survey on the present state of art technology in energy scavenging system for wireless sensor nodes is discussed and the motivation of the work is presented The... popular topologies 45 utilizing the power electronic converter for maximum power point tracking (MPPT) in the field of low power application Brunelli et al and Dondi et al in [6] and [7] emphasize the usage of two-stage power management circuits for harvesting solar energy for wireless sensor nodes as shown in Figure 1-1 It consists of two stages namely buck converter and external DC/DC converter The... design properly Power control circuit described in [3-5] relies on digital microcontroller based MPPT system However, use of microcontroller for the control circuit calls for extra Page 4 power loss in the controller, analog to digital converter (ADC) and voltage as well as current sensors Hence, the overall efficiency of the scavenging system for low power application is comparatively lower due to digital... the computational power of the digital signal processor Hence, available battery energy has become a critical resource for such systems The real challenge for such low power portable electronic devices is to reduce or even eliminate the dependency on batteries and to be truly autonomous and self-sufficient with regards to energy generation and utilization Recently, energy harvesting /scavenging from the... comparatively lower due to digital control system in power conversion unit The proposition in [6- 9] shows an analog circuit based power management 8 circuit for solar energy harvesting The cited papers present the solar energy harvester with very attractive power management features but the power consumed in the power management control circuitry is neglected The thermoelectric energy harvesters are also playing... challenge, energy harvesting technology has become an emerging research field that strives to reduce battery dependency for low power sensor applications Reducing battery dependency can be achieved through improved energy conversion from previously untapped renewable energy as well as unwanted available energy sources such as solar, thermal, vibration etc in the environment and also through improved and efficient... thesis The thesis is organized as follow: Chapter 2 involves classification of different solar energy harvesting components based on the solar panel characteristics, DC/DC converter properties as well as different energy storage elements for the low power application such as wireless sensor nodes The chapter deals with selection of solar panel, energy storage devices, power converters as well as control... current-voltage (I-V) and power- voltage (P-V) characteristic of a PV module for different level of solar radiation and temperature [22] Figure 2-5: Solar panel characteristics with solar intensity Page 15 Figure 2-6: Solar panel characteristics with solar panel temperature Figure 2-5 and Figure 2-6 distinctly show that short circuit current is proportional to the solar radiation Hence, great solar radiation... electrical energy 1.2 Literature review Various types of renewal energy sources such as solar, thermal, etc can be investigated for powering the portable systems [1-13] The research work on the energy harvesting of the portable system is drawn the prime importance among the researchers in the recent past Figure 1-1: Conventional two-stage DC/DC converter MPPT circuit [6] Page 3 The solar energy harvester ... different types of solar and thermal energy harvesting systems The main focus of this report is to develop energy efficient solar and thermal energy harvesters for low power wireless sensor applications... converter (ADC) and voltage as well as current sensors Hence, the overall efficiency of the scavenging system for low power application is comparatively lower due to digital control system in power conversion... different types of energy scavenging system such as energy extraction from solar and thermal energy sources for wireless sensor nodes used for condition monitoring applications are investigated