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 %.

The growing need and desire for the harvesting of energy from everyday mechanical interactions impose a challenge on the current design of such systems. Often their nature indicates slow response times and unsteady AC voltages. The objective of this work is to present a new method of designing and controlling an oscillating energy harvesting system using a cutting-edge algorithm for fast determination of the optimal operating condition. In this thesis, an energy harvesting backpack, which captures energy from the interaction between the user and the spring decoupled load, is being introduced. The new control strategy, Maximum Energy Harvesting Control (MEHC), is developed and applied to the aforementioned system to evaluate its improvement over the basic Maximum Power Point Tracking (MPPT) algorithm. MEHC algorithm can also be used in many different applications, ranging from ocean wave to sports shoes energy harvesting.

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.

This thesis deals with quantifying the merits of Distributed Maximum Power Point Tracking (DMPPT), as well as providing solutions to achieve DMPPT in PV systems. A general method based on 3D modeling is developed to determine the energy yield of PV installations exploiting different levels of DMPPT granularity. Sub-string-level DMPPT is shown to have up to 30% more annual energy yield than panel-level DMPPT. A Multi-Input-Single-Output (MISO) dc-dc converter is proposed to achieve DMPPT in parallel-connected applications. A digital current-mode controller is used to operate the MISO converter in pseudo-CCM mode. For series-connected applications, the virtualparallel concept is introduced to utilize the robustness of the parallel connection. This concept is demonstrated on a three-phase boost converter. The topology offers reduced output voltage ripple under shading which increases the life-time of the output capacitor. The prototypes yield output power benefits of up to 46% and 20% for the tested shading conditions.

This master work was focused on modelling and investigation of a photovoltaic module which operates in non-uniform solar irradiance and temperature changes which is typical to Lithuanian climate. 60 polycrystalline silicon cells were used to model photovoltaic module. Matlab®/Simulink® was used for modelling and calculating the whole system. To generate solar insolation curve, the latitude, longitude of the geographic place and a number of days in a year have to be selected. Buck-boost DC-DC converter and hill-climbing maximum power point tracking algorithm was used to produce maximum power point of the photovoltaic module. Modeled system has reached 93.95 % of maximum power from the photovoltaic module. Structure: introduction, review of maximum power point algorithms, system modelling, research results, conclusions, references. The thesis consists of: 60 pages, 41 figures, 16 tables, 37 references. Appendixes included. / Šiame magistro darbe buvo sumodeliuotas ir ištirtas fotovoltinio modulio veikimas, veikiant Lietuvoje būdingiems saulės apšvietos ir temperatūros pokyčiams. Fotovoltinį modulį sudaro 60 polikristalinių silicio celių sujungtų nuosekliai sistema. Modeliavimui ir skaičiavimas atlikti buvo naudojamas Matlab®/Simulink® programinės įrangos paketas. Įvedus vietos ilgumą, platumą ir pasirinkus metų dieną sugeneruojama saulės apšvietos kreivė paros bėgyje. Išgauti maksimalią galią iš fotovoltinio elemento buvo pasirinkta „buck-boost“ tipo įtampos keitiklis ir „Kalno-kilimo“ didžiausios galios taško algoritmas. Naudojant pasirinkto tipo įtampos keitiklį ir algoritmą galima pasiekti iki 93,95 % maksimalios galios. Darbą sudaro 7 dalys: įvadas, maksimalios galios algoritmų literatūros apžvalga, sistemos modeliavimas, maksimalios galios algoritmo sudarymas, rezultatai, išvados, literatūros sąrašas. Darbo apimtis 60 puslapiai, 2 priedai, 41 iliustracijų 16 lentelių, 37 bibliografiniai šaltiniai.

M. Tech. (Department of Electronic Engineering, Faculty of Engineering and Technology) --Vaal University of Technology| / Global warming is of increasing concern due to several greenhouse gases. The combustion of fossil fuels is the major contributor to the greenhouse effect. To minimalise this effect, alternative energy sources have to be considered. Alternative energy sources should not only be environmentally friendly, but also renewable and/or sustainable. Two such alternative energy sources are hydrogen and solar energy. The regenerative fuel cell, commonly known as a hydrogen generator, is used to produce hydrogen. The current solar/hydrogen system at the Vaal University of Technology’s Telkom Centre of Excellence makes use of PV array to supply power to an inverter and the inverter is connected to the hydrogen generator. The inverter provides the hydrogen generator with 220VAC. The hydrogen generator has its own power supply unit to convert the AC power back to DC power. This reduces the efficiency of the system because there will be power loss when converting DC power to AC power and back to DC power. The hydrogen generator, however, could be powered directly from a PV array. However, the hydrogen generator needs specific input parameters in order to operate. Three different input voltages with their own current rating are required by the hydrogen generator to operate properly. Thus, a DC-DC power supply unit needs to be designed to be able to output these parameters to the hydrogen generator. It is also important to note that current PV panel efficiency is very low; therefore, the DC-DC power supply unit also needs to extract the maximum available power from the PV array. In order for the DC-DC power supply unit to be able to extract this maximum power, a maximum power point tracking algorithm needs to be implemented into the design. The DC-DC power supply is designed as a switch mode power supply unit. The reason for this is that the efficiency of a switch mode power supply is higher than that of a linear power supply. To reach the objective the following methodology was followed. The first part of the research provided an introduction to PV energy, charge controllers and hydrogen generators. The problem statement is included as well as the purpose of this research and how this research was to be carried out. The second part is the literature review. This includes the background study of algorithms implemented in MPPT’s; it also explains in detail how to design the MPPT DC-DC SMPS. The third part was divided into two sections. The first section is the design, programming and manufacturing of the MPPT DC-DC SMPS. The second section is the simulation of the system as a whole which is the simulation of the PV array connected to the MPPT DC-DC SMPS and the hydrogen generator. The fourth part in the research compared the results obtained in the simulation and practical setup. The last part of the research provided a conclusion along with recommendation made for further research. The simulation results showed that the system works with an efficiency of 40,84%. This is lower than expected but the design can be optimised to increase efficiency. The practical results showed the efficiency to be 38%. The reason for the lower efficiency is the simulation used ideal components and parameters, whereas the practical design has power losses due to the components not being ideal. The design of the DC-DC switch mode power supply, however, indicated that the hydrogen generator could be powered from a PV array without using an inverter, with great success.

Microgrids containing photovoltaic (PV) cells and wind power gain more and more interest. These microgrids may work in stand-alone mode ("islanding") or be conncted to the main grid. In both modes of operation, power quality must be monitored and controlled. This report focuses on microgrids and aims to implement a monitoring system based on FPGA. In the monitoring system, two applications can be achieved, firstly a PAS-MPPT algorithm in a DC-DC boost converter to improve the maximun power point tracking of a PV unit, and secondly a detection and switching system of the grid mode - stand-alone or connected to the main grid. Simulation results prove the Verilog programs in FPGA are suitable to be used in microgrids.