Energy harvesting is becoming increasingly important in low-power applications where energy from the environment is used to power the system alone, or to supplement a battery. For example, pulse oximeter sensors inside helmets of road racing cyclists are powered by the sun. These sensors have become smaller and more practical without the limitation of a finite energy supply. Harvested energy from an energy transducer (solar, piezoelectric, etc.) must be maximized to ensure these devices can survive periods where environmental energy is scarce. The conversion process from the transducer to usable power for the device is not perfectly efficient. Specifically, the output voltage of a solar cell is a function of the light intensity, and by extension the load it powers. A small perturbation of the light source quickly diminishes the available power. The wasted power reduces the energy available for the application, and can be improved using an approach called maximum power point tracking (MPPT). This technique maximizes harvesting efficiency by dynamically impedance matching the transducer to its load. This report introduces the Maximum Efficient Solar Harvester (MESH), an MPPT algorithm tuned for a specific Wireless Sensor Network (WSN) application. MESH specifically controls the operation of the DC-DC converter in a solar power management unit (PMU). The control is done by monitoring the available light and feeding that information to choose the optimal operating point DC-DC converter. This operating point has a direct dependency on the overall efficiency of the system. For MESH to be practical, the cost and power overhead of adding this functionality must be assessed. Empirical results indicate that MESH improves the maximum efficiency of the popular Texas Instruments (TI) RF2500-SEH WSN platform by an average of 20%, which far exceeds the power overhead it incurs. The cost is also found to be minimal, as WSN platforms already include a large portion of the hardware required to implement MESH. The report was done in collaboration with Stephen Kobdish. It covers the software implementation and MESH architecture definition; Kobdish's companion report focuses on hardware components and the bench automation environment. / text

The yield from a solar photovoltaic (PV) source is dependent on factors such as light and temperature. A control system called a maximum power point tracker (MPPT) ensures that the yield from a solar PV source is maximized in spite of these factors. This thesis presents a novel implementation of a perturb and observe (PO) MPPT. The implementation uses a switched capacitor step down converter and a custom digital circuit implementation of the PO algorithm. Working in tandem, the switched capacitor step down converter and the custom digital circuit implementation were able to successfully track the maximum power point of a simulated solar PV source. This implementation is free of the overhead encountered with general purpose processor based MPPT implementations. This makes this MPPT system a valid candidate for applications where general purpose processors are undesirable. This document will begin by discussing the current state of MPPT research. Afterward, this thesis will present studies done to be able to use the chosen switched capacitor step down converter. Then the digital circuit PO implementation will be discussed in detail. Simulations of the architecture will be presented. Finally, experimental validation using a hardware prototype will be shown.

A energia fotovoltaica oferece conhecidas vantagens, entretanto, ainda deve vencer alguns desafios, principalmente a baixa eficiência de conversão dos painéis fotovoltaicos. Além do desenvolvimento de novos materiais, ainda continua muito importante aumentar a eficiência de conversão através da maximização da entrada de radiação solar e da otimização do ponto de operação do painel fotovoltaico. Este trabalho apresenta uma nova abordagem de rastreamento do ponto de máxima potência, adequada a qualquer configuração de conversores e capaz de seguir as rápidas mudanças de insolação e temperatura. É um método de perturbação e observação que mede apenas a corrente de saída do painel e que mantém a perfeita busca do ponto de máxima potência, mesmo durante as bruscas variações atmosféricas, com o simples emprego de flags. O trabalho apresenta ainda, como objetivo secundário, informações básicas a respeito de sistemas fotovoltaicos: células, painéis, conversores e suas técnicas de controle. O desempenho das simulações utilizando o software Matlab foram muito bons, confirmando a robustez, simplicidade, rápida convergência e facilidade de implementação do algoritmo. / The photovoltaic energy offers known advantages, however, it has yet to overcome some challenges, mainly the low efficiency of conversion of the photovoltaic panels. Besides the development of new materials, it still continues very important to increase the conversion efficiency through the maximization of the input solar radiation and the optimization of the photovoltaic panel operating point. This work presents a new approach for tracking the maximum power point, appropriate for any configuration of converters and capable to follow the fast changes in irradiance and temperature. It is a method of perturbation and observation that measures only the panel output current and that maintains a perfect search of the maximum power point, even during abrupt atmospheric variations, by simply using flags. The work still presents, as secondary objective, basic information regarding photovoltaic systems: cells, panels, converters and their control techniques. The performance of the simulations using the software Matlab proved to be very good, confirming the robustness, simplicity, rapid convergence and ease of implementation of the algorithm.

This dissertation presents various systematic design techniques for photovoltaic (PV) source simulators to serve as a convenient tool for the dynamic performance evaluation of solar power conditioning systems and their maximum power point tracking algorithms. A well-designed PV source simulator should accurately emulate the static and the dynamic characteristic of actual PV generator. Four major design features should be adopted in any PV source simulator: (i) high power-stage efficiency, (ii) fast transient response-time, (iii) output impedance matching with actual PV generator, and (iv) precise reference generation technique. Throughout this research, two different PV source simulator systems are designed, modeled, and experimentally verified. The design of the first system focuses mainly on creating new reference generation techniques where the PV equivalent circuit is used to precisely generate the current-voltage reference curves. A novel technique is proposed and implemented with analog components to simplify the reference signal generator and to avoid computation time delays in digital controllers. A two-stage LC output filter is implemented with the switching power-stage to push the resonant frequency higher and thus allowing a higher control-loop bandwidth design while keeping the same switching ripple attenuation as in the conventional one-stage LC output filter. With typical control techniques, the output impedance of the proposed simulator did not  match the closed-loop output impedance of actual PV generator due to the double resonant peaks of the two-stage LC output filter. Design procedures for both control and power-stage circuits are explained. Experimental results verify the steady-state and transient performance of the proposed PV source simulator at around 2.7 kW output. The design concept of the first simulator system is enhanced with a new type of PV source simulator that incorporates the advantages of both analog and digital based simulators. This simulator is characterized with high power-stage efficiency and fast transient response-time. The proposed system includes a novel three-phase ac-dc dual boost rectifier cascaded with a three-phase dc-dc interleaved buck converter. The selected power-stage topology is highly reliable and efficient. Moreover, the multi-phase dc-dc converter helps improve system transient response-time though producing low output ripple, which makes it adequate for PV source simulators. The simulator circuitry emulates precisely the static and the dynamic characteristic of actual PV generator under different environmental conditions including different irradiance and temperature levels. Additionally, the system allows for the creation of the partial shading effect on PV characteristic. This dissertation investigates the dynamic performance of commercial and non-commercial solar power conditioning systems using the proposed simulator in steady-state and transient conditions. Closed-loop output impedance of the proposed simulator is verified at different operating conditions. The impedance profile --magnitude and phase- matches the output impedance of actual PV generator closely. Mathematical modeling and experimental validation of the proposed system is thoroughly presented based on a 2.0 kW hardware prototype. The proposed simulator efficiency including the active-front-end rectifier and the converter stages at the maximum power point is 96.4%. / Ph. D.

Indiana University-Purdue University Indianapolis (IUPUI) / With the increasing demand of economy and environmental pollutions, more and more renewable energy systems with clean sources appear and have attracted attention of systems involving solar power, wind power and hybrid new energy powers[1]. However, there are some difficulties associated with combined utilization of solar and wind, such as their intermittent behavior and their peak hours mismatch in generation and consumption[1]. For this purpose, advanced network of a variety of renewable energy systems along with controllable load and storage units have been introduced[1-3]. This thesis proposes some configurations of hybrid energy harvesting systems, including wind-wind-storage DC power system with BOOST converters, solar-solar-storage DC power system with cascade BOOST converters, wind-solar-storage DC power system with BOOST converter and cascade BOOST converter, and wind-solar DC power system with SEPIC converter and BOOST converter. The models of all kinds of systems are built in Matlab/Simulink and the mathematical state-space models of combined renewable energy systems are also established. Several MPPT control strategies are introduced and designed to maximize the simultaneous power capturing from wind and solar, such as Perturb & Observe (P&O) algorithm for solar and wind, Tip Speed Ratio (TSR) control and Power Signal Feedback (PSF) control for wind, and Sliding Mode Extremum Seeking Control (SM-ESC) for wind and solar systems[4]. The control effects of some of these MPPT methods are also compared and analyzed. The supervisory control strategies corresponding to each configurations are also discussed and implemented to maximize the simultaneous energy harvesting from both renewable sources and balance the energy between the sources, battery and the load[2]. Different contingencies are considered and categorized according to the power generation available at each renewable source and the state of charge in the battery[2]. Applying the system architectures and control methods in the proposed hybrid new energy systems is a novel and significant attempt, which can be more general in the practical applications. Simulation results demonstrate accurate operation of the supervisory controller and functionality of the maximum power point tracking algorithm in each operating condition both for solar and for wind power[3]

Massive deployment of wireless IoT (Internet of Things) devices makes replacement or recharge of batteries expensive and impractical for some applications. Energy harvesting is a promising solution, and various designs are proposed to harvest power from ambient resources including thermal, vibrational, solar, wind, and RF sources. Among these ambient resources, AC powerlines are a stable energy source in an urban environment. Many researchers investigated methods to exploit this stable source of energy to power wireless IoT devices. The proposed circuit aims to harvest energy from AC powerlines with a wide input range of from 10 to 50 A. The proposed system includes a wake-up circuit and is capable of cold-start. A buck-boost converter operating in DCM is adopted for impedance matching, where the impedance is rather independent of the operation conditions. So, the proposed system can be applied to various types of wireless sensor nodes with different internal impedances. Experimental results show that the proposed system achieves an efficiency of 80.99% under the powerline current of 50 A. / M.S. / Nowadays, with the magnificent growth of IoT devices, a reliable, and efficient energy supply system becomes more and more important, because, for some applications, battery replacement is very expensive and sometimes even impossible. At this time, a well-designed self-contained energy harvesting system is a good solution. The energy harvesting system can extend the service life of the IoT devices and reduce the frequency of charging or checking the device. In this work, the proposed circuit aims to harvest energy from the AC power lines, and the harvested power intends to power wireless sensor nodes (WSNs). By utilizing the efficient and self-contained EH system, WSNs can be used to monitor the temperature, pressure, noise level and humidity etc. The proposed energy harvesting circuit was implemented with discrete components on a printed circuit board (PCB). Under a power line current of 50 A @ 50 Hz, the proposed energy harvesting circuit can harvest 156.6 mW, with a peak efficiency of 80.99 %.

Fossil fuel consumption throughout the world is drawing attention to the need for alternative energy sources to provide for the large demand for energy. It is becoming more apparent everyday that fossil fuels are unreliable sources of energy due to the volatile pricing of such commodities as well as the toll that these energy sources take on the environment. Fossil fuels are non-renewable sources of energy that when burned to create energy produce bi-products that are extremely harmful to the global environment. Today, renewable energy sources such as wind and solar energy are playing larger roles as sources of electricity and are providing new jobs as well as research opportunities both in academia and in industry. It is for this reason that wind turbine energy harvesting is the topic of this thesis and how the efficiency of wind turbine power conversion systems can be improved to become a more viable source of energy. Large wind turbines, along with their power conversion electronics, exist today for the sole purpose of serving a large population of consumers with "green" electricity. Unfortunately, systems designed for low power wind turbines do not utilize advanced methods of maximizing energy draw from wind turbines both from hardware and software point of views. This theses is presents a method of efficient energy extraction and conversion from low power wind turbines to charge lead ac id batteries.

Distributed generators (DGs) with integration of renewable resources (RRs) such as photovoltaic (PV) and wind turbine have been widely considered to reduce the dependency on conventional power generation systems along with enhancement of the quality and sustainability of the power system. Recently, DC microgrid has gained popularity in many real-world applications such as rural electrification due to its simplicity and low power losses. However, the power variability of renewable resources and continuous change in load demand imposes risks of power mismatch in standalone DC systems that increase the chances of stability and reliability issues. Therefore, complementary generation and/or storage systems are coupled with standalone DC microgrid to mitigate the power fluctuations and maintain a power balance in the system. This dissertation presents a power management strategy (PMS) based on model predictive control (MPC) for a standalone DC microgrid. A control scheme for a standalone DC microgrid system with RRs, storage, and load is desired to have the capability of effective power management that maximizes the extraction of energy from renewable generators, minimizes the transients in the system during disturbances, and protects the storage from over/under charging conditions. As a part of the proposed MPC, an optimization problem is formulated to meet the voltage performance in the system with respect to operating conditions and constraints. The proposed PMS uses the ARIMA prediction method to forecast the load and environmental parameters. The predicted parameters are utilized to estimate the future performance of the system by solving the dynamic model of the system, and a cost function is optimized to generate suitable control sequences. This research also presents detailed mathematical models of the considered systems. This dissertation presents an extensive simulation-based analysis of the proposed approach. With the proposed control, maximum utilization of the renewable generators has been achieved, and the DC bus voltage is regulated at nominal value with minimum transients under various load/environmental disturbances. Moreover, the research investigates the proposed MPC based on ARIMA prediction by comparing the performance of different types of prediction methods. The dissertation also measures the effectiveness of the proposed MPC by comparing its performance with a conventional PI controller.

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The study started with the requirement that a photovoltaic (PV) power source should be integrated with other supplementary power sources whether it operates in a stand-alone or grid-connected mode. First, fuel cells for a backup of varying PV power were compared in detail with batteries and were found to have more operational benefits. Next, maximizing performance of a grid-connected PV-fuel cell hybrid system by use of a two-loop controller was discussed. One loop is a neural network controller for maximum power point tracking, which extracts maximum available solar power from PV arrays under varying conditions of insolation, temperature, and system load. A real/reactive power controller (RRPC) is the other loop. The RRPC meets the system's requirement for real and reactive powers by controlling incoming fuel to fuel cell stacks as well as switching control signals to a power conditioning subsystem. The RRPC is able to achieve more versatile control of real/reactive powers than the conventional power sources since the hybrid power plant does not contain any rotating mass. Results of time-domain simulations prove not only effectiveness of the proposed computer models of the two-loop controller, but also their applicability for use in transient stability analysis of the hybrid power plant. Finally, environmental evaluation of the proposed hybrid plant was made in terms of plant's land requirement and lifetime CO2 emissions, and then compared with that of the conventional fossil-fuel power generating forms. / Ph. D.