Rapid battery exchange systems were built for an electric van and pedal assist electric bike as a method of eliminating the need to recharge the vehicles batteries in order to increase the feasibility of using electric propulsion as a method of efficient student transportation. After selecting proper materials it was found that the systems would need a protective coating to ensure consistent operation. 1020 cold rolled steel samples coated with multiple thicknesses of vinyl resin paint, epoxy resin paint, and powder coating were subjected to environmental wear tests in order to determine if the type and thickness of common protective coatings has an effect on the durability of the system over its lifetime. The tests consisted of a 2400 hour extended salt spray test, coating delamination testing, and modified impact testing. The extended salt spray test, delamination test, and deformation tests of the coatings all found that the type of coating and the thickness of the coating to have a significant effect on the measured outputs. The significant effect shown in the deformation test could not determine the proper material without the aid of microscopic studies of the surface geometry change due to the induced deformation. Powder coating the rapid battery exchange systems would result in proper performance if coupled with epoxy paint for repairs. Testing of the Rapid battery exchange system indicated that the use of mechanical aiming was not suitable for the application, a further adaptation of the system indicated that the system may be better suited toward personal bicycles as there was a large increase in transportation efficiency.

Plug-in Electric Vehicles (PEVs) are projected to become a viable means of transportation due to advances in technology and advocates for green and eco-friendly energy solutions. These vehicles are powered partially, or in some cases, solely by the energy stored in their battery packs. The large sizes of these battery packs require large amount of energy to charge, and as the demand for PEV increases, the increase in energy demand needed to recharge these PEV batteries could pose problems to the present electric distribution system. This study examines the potential impacts of PEV on a residential electric distribution system at various penetration levels. An existing residential distribution network is modeled up to each household service point and various sensitivity scenarios and stochastic patterns of PEV loads are simulated. Impact studies that include voltage drop, service transformers overload, energy loss, and transformer thermal loss-of-life expectancy are analyzed. Results from the study are reported and recommendations to mitigate the impacts are presented.

This thesis presents an active clamp forward converter for use in the Energy Harvesting From Exercise Machines project. Ideally, this converter will find use as the centerpiece in a process that links elliptical trainers to the California grid. This active clamp forward converter boasts a 14V-60V input voltage range and 150W power rating, which closely match the output voltage and power levels from the elliptical trainer. The isolated topology outputs 51V, higher than previous, non-isolated attempts, which allows the elliptical trainers to interact with a central grid-tied inverter instead of many small ones. The final converter operated at greater than 86% efficiency over most of the elliptical trainer’s input range, and produced very little noise, making it a solid choice for this implementation.

This thesis entails the design and fabrication of a smartphone charger that is powered by a bicycle dynamo hub. In addition to the design and validation of the charger prototype, this thesis involves the testing and characterization of the dynamo hub power source, the design and construction of specialized test equipment, and the design and prototyping of a handlebar-mounted case for the smartphone and charging electronics. With the intention of making the device a commercial product, price, aesthetics, and marketability are of importance to the design. An appropriate description of the charger circuit is a microcontroller-based energy management system, tailored to meet strict power demands of current smartphones. The system incorporates a switched-mode power supply, lithium polymer battery, microcontroller, and specialized protection circuitry. Prototype testing confirms that the circuit meets the charging requirements of the smartphone at bicycle speeds ranging from 7 miles per hour to as high as 55 miles per hour.

<p>Solar energy is a clean and abundant renewable energy source which is currently used in many types of photovoltaic (PV) designs. In practical PV systems, solar panels are used to harvest solar energy and convert it into a usable form of electricity. Due to the intermittent nature of solar energy input however, battery storage, in combination with solar panels, must be used to provide an uninterrupted source of power.</p> <p>The process of assigning solar panel and battery configurations for a PV system is referred to as energy resource provisioning. Unfortunately, energy provisioning costs are still relatively high, and this is one of the main obstacles that inhibits the adoption of solar power for many applications. These costs however, can be substantially reduced through cost-efficient resource provisioning methods. The focus of this thesis is on the development of efficient algorithms and energy management methods that will reduce energy provisioning costs in solar powered systems.</p> <p>First, we consider resource provisioning in solar powered wireless mesh networks. In practical solar powered systems, there are usually restrictions in the way that the mesh nodes can be positioned, and this results in a time-varying and node-dependent attenuation of the available solar energy. Unfortunately, conventional resource provisioning methods cannot take this into account and therefore the deployed system may be unnecessarily expensive. In this part of the thesis, the resource provisioning problem is considered from this point of view. We first review conventional resource provisioning mechanisms and give an example which shows the value of introducing positional solar insolation awareness. A Position Aware Provisioning (PAP) algorithm is then introduced that takes known positional variations into consideration when performing the energy provisioning. Simulation results show that reductions in total network provisioning cost can be obtained using the proposed methodology compared to conventional algorithms.</p> <p>In the second part of the thesis, we consider communication infrastructure that is operated from the power grid with a solar powered addition. Resource provisioning and energy management algorithms are introduced to minimize the capital expenditure (CAPEX) and operating expenditure (OPEX) costs. We first derive lower bounds on the costs using a linear programming (LP) formulation where solar components are sized using solar insolation and projected loading data. A variety of different node configurations are considered. Three energy scheduling algorithms are then introduced to optimize online OPEX costs, namely, Grid Purchase Last (GPL), Solar Load Optimization (SLO) and Solar Load Simulation (SLS) algorithms. Simulation results show the extent to which a solar powered add-on can reduce total cost.</p> <p>Finally, we consider solar powered systems where part of their energy demands are deferrable, up to some maximum tolerable delay. The objective is to exploit the flexibility of deferrable energy demands in a way that decreases the total provisioning cost. A mixed integer linear optimization program is derived which gives a lower bound on the provisioning cost. A Delay Aware Provisioning (DAP) algorithm is then proposed to determine practical cost-efficient energy provisioning. The performance of DAP is compared to the provisioning bound and the conventional Stand-alone Node Provisioning (SNP) algorithm. Results are presented which show the significant provisioning cost savings that can be obtained.</p> / Doctor of Philosophy (PhD)

Power amplifiers (PAs) convert energy from DC to high frequencies in all radio and microwave transmitter systems be they wireless base stations, handsets, radars, heaters, and so on. PAs are the dominant consumers of energy in these systems and, therefore, the dominant sources of system cost and inefficiency. Research has focused on efficient solid-state PA circuit topologies and their optimization since the 1960s. The 2000s saw the current-mode class-D (CMCD) topology, potentially suitable for today's wireless communications systems, show promise in the UHF frequency band. This thesis describes the design and testing of a high-efficiency CMCD amplifier with an integrated driver stage. In addition, analysis of a merged PA-mixer circuit based on the CMCD is provided.

Recently, due to the increasing adoption of distributed energy resource (DER) technologies including battery energy storage (BES) and electric vehicle (EV) systems, bidirectional power converters are becoming more popular. These converters are broadly utilized as interface devices and provide a bidirectional power flow in applications where the primary power supply can both supply and receive energy. A dc capacitor, called the dc-link, is an important component of such bidirectional converters. For a wide range of applications, the converter is required to control the dc-link voltage. Commonly, a proportional-integrating (PI) controller is used by the dc capacitor voltage controller to generate a set-point for the inner current controller. This approach tightly regulates the dc-link voltage to a given value. The research presented in this dissertation shows that such an approach compromises the stability margins of the converter for reverse power flow and weak grid conditions. It is shown that by allowing a small variation of dc capacitor voltage in proportion to the amount of power flowing through the converter, the stability and robustness margins are improved. This approach also simplifies the design process and can be applied to both dc/dc and dc/ac (single-phase and three-phase) converters. Moreover, it grants an inherent power sharing capability when multiple converters share the same dc-link terminals; removing the need to a communication link between parallel converters. The proposed controller is equipped with a current limiting mechanism to protect the converter during low-voltage/over-current transients. Detailed analyses, simulations, comparisons, and experimental results are included to illustrate the effectiveness of the proposed control approach. To mathematically establish the properties of the proposed method in a single-phase dc/ac application, this dissertation also derives a new and systematic modeling approach for a grid-connected bidirectional single-phase inverter controlled in stationary frame. Implementing the control system in the stationary frame has advantages over rotating frame. However, the combination of dc and ac state variables and nonlinearities make its stability analysis challenging. In the proposed model, an imaginary subsystem is properly generated and augmented to allow a full transformation to a synchronous rotating frame. The proposed modeling strategy is modular and has a closed form which facilitates further extensions. It is successfully used to demonstrate enhanced stability margins of the proposed controller.

The thesis project outlined in this report aims to comprehensively assess and optimize methods for long-term power production estimation of hybrid PV-wind energy systems. Through practical case studies, this approach seeks to exemplify the challenges and opportunities inherent in such systems. The research is conducted within the Wind Technical Team of Akuo Energy, an independent French renewable energy producer, leveraging their extensive expertise in technologies, industry practices, and data processing. The primary objective is to evaluate the relevance of two key parameters used in Akuo’s internal estimation methods, focusing on their impact on long-term production and revenues within the context of hybrid PV-wind energy systems. These parameters include unavailability losses, modeled on an hourly basis using Markovian transition matrices, and interannual variability of resources, statistically modeled by randomly shuffling yearly production profiles of individual wind and solar plants. Python will be employed to generate hybrid production time series, incorporating the models for unavailability losses and interannual variability. This approach facilitates the creation of multiple scenarios for sensitivity analysis, allowing for the variation of parameters to compare the productivity and profitability of different scenarios. The study sheds light on the importance of employing realistic models to account for unavailability losses, revealing that simpler models tend to overestimate revenues from hybrid power plants systematically. Moreover, the research shows the impact of interannual variability of resources on both production and revenues, emphasizing the necessity of generating multiple scenarios to anticipate best and worst-case outcomes. Ultimately, the results of this study aim to assist the company on the necessity and relevance of using such models for calculating long-term production and revenues in future hybrid PV-wind projects, as opposed to current simpler methods. / Det avhandlingsprojekt som beskrivs i denna rapport syftar till att heltäckande utvärdera och optimera metoder för långsiktig kraftproduktionsestimering av hybrid PV-vindenergisystem. Genom praktiska fallstudier söker detta tillvägagångssätt att exemplifiera de utmaningar och möjligheter som är inneboende i sådana system. Forskningen utförs inom vindtekniska teamet på Akuo Energy, en oberoende fransk producent av förnybar energi, där man dra nytta av deras omfattande expertis inom teknik, branschpraxis och datahantering. Det primära målet är att utvärdera relevansen av två viktiga parametrar som används i Akuos interna estimeringsmetoder och fokuserar på deras påverkan på långsiktig produktion och intäkter inom ramen för hybrid PV-vindenergisystem. Dessa parametrar inkluderar otillgänglighetsförluster, modellerade på timbasis med hjälp av Markovska övergångsmatriser, och årlig variabilitet av resurser, statistiskt modellerade genom att slumpmässigt ordna årliga produktionsprofiler för enskilda vind- och solanläggningar. Python kommer att användas för att generera hybridproduktionsserier och inkludera modeller för otillgänglighetsförluster och årlig variabilitet. Detta tillvägagångssätt möjliggör skapandet av flera scenarier för känslighetsanalys, vilket gör det möjligt att variera parametrar för att jämföra produktiviteten och lönsamheten för olika scenarier. Studien belyser vikten av att använda realistiska modeller för att ta hänsyn till otillgänglighetsförluster och visar att enklare modeller tenderar att systematiskt överskatta intäkter från hybridkraftverk. Dessutom visar forskningen påverkan av årlig variabilitet av resurser på både produktion och intäkter och betonar nödvändigheten av att generera flera scenarier för att förutse bästa och sämsta fall. Slutligen syftar resultaten av denna studie till att bistå företaget när det gäller nödvändigheten och relevansen av att använda sådana modeller för att beräkna långsiktig produktion och intäkter i framtida hybrid PV-vindprojekt, jämfört med nuvarande enklare metoder.

This study focuses on utilizing an energy harvesting system in which a dedicated Radio Frequency (RF) power source transmits RF power via rebar in a reinforced concrete column. The RF power is received and decoupled by a receiver, and is then rectified, boosted, and stored as electrical energy in a supercapacitor, later to be used to make measurements, process data, and communicate to the source via rebar. Two design attempts are presented in this study: (a) one uses single line conduction at 2.4 GHz for RF power transfer; (b) the other uses a more conventional two-line conduction at 8.0 kHz for RF power transfer. Both designs were unsuccessful: (a) the 2.4 GHz attempt demonstrated that no detectable RF power propagated through the concrete medium; (b) the 8.0 kHz attempt demonstrated that too much of the RF power was attenuated through the concrete medium for the energy harvesting circuitry work properly. A potential third design approach is posited in the conclusion of this study. In addition to investigating power transfer designs, a study on the energy harvesting circuitry was performed. A Two-Stage Dickson Multiplier was utilized in conjunction with a Texas Instruments BQ25504 Ultra-Low Power Energy Harvesting Circuit. For these two components to function best, it was shown that the BQ25504’s input filtering capacitor needed to be on the same order of magnitude as the charging capacitors of the Two-Stage Dickson Multiplier, otherwise, if the filtering capacitor was comparatively too large, it would short the output of the Two-Stage Dickson Multiplier. With that said, the lowest power input observed was at 7.83 dBm, but with lower input powers expected to be achievable. Nevertheless, since the second design attempt showed power losses were too significant, it was deemed that at present, unless the power transfer design were improved, then contemporary commercial off the shelf energy harvesting approaches are insufficient.

Artificial intelligence tools, which are fast, robust and adaptive can overcome the drawbacks of traditional solutions for several power systems problems. In this work, applications of AI techniques have been studied for solving two important problems in power systems. The first problem is static security evaluation (SSE). The objective of SSE is to identify the contingencies in planning and operations of power systems. Numerical conventional solutions are time-consuming, computationally expensive, and are not suitable for online applications. SSE may be considered as a binary-classification, multi-classification or regression problem. In this work, multi-support vector machine is combined with several evolutionary computation algorithms, including particle swarm optimization (PSO), differential evolution, Ant colony optimization for the continuous domain, and harmony search techniques to solve the SSE. Moreover, support vector regression is combined with modified PSO with a proposed modification on the inertia weight in order to solve the SSE. Also, the correct accuracy of classification, the speed of training, and the final cost of using power equipment heavily depend on the selected input features. In this dissertation, multi-object PSO has been used to solve this problem. Furthermore, a multi-classifier voting scheme is proposed to get the final test output. The classifiers participating in the voting scheme include multi-SVM with different types of kernels and random forests with an adaptive number of trees. In short, the development and performance of different machine learning tools combined with evolutionary computation techniques have been studied to solve the online SSE. The performance of the proposed techniques is tested on several benchmark systems, namely the IEEE 9-bus, 14-bus, 39-bus, 57-bus, 118-bus, and 300-bus power systems. The second problem is the non-convex, nonlinear, and non-differentiable economic dispatch (ED) problem. The purpose of solving the ED is to improve the cost-effectiveness of power generation. To solve ED with multi-fuel options, prohibited operating zones, valve point effect, and transmission line losses, genetic algorithm (GA) variant-based methods, such as breeder GA, fast navigating GA, twin removal GA, kite GA, and United GA are used. The IEEE systems with 6-units, 10-units, and 15-units are used to study the efficiency of the algorithms.