Energy harvesting system design and optimization for wireless sensor networks

Wireless sensor networks (WSN) are becoming widely adopted for many applications including complicated tasks like building energy management. However, one major concern for WSN technologies is the short lifetime and high maintenance cost due to the limited battery energy. One of the solutions is to scavenge ambient energy, which is then rectified to power the WSN. The objective of this thesis was to investigate the feasibility of an ultra-low energy consumption power management system suitable for harvesting sub-mW photovoltaic and thermoelectric energy to power WSNs. To achieve this goal, energy harvesting system architectures have been analyzed. Detailed analysis of energy storage units (ESU) have led to an innovative ESU solution for the target applications. Battery-less, long-lifetime ESU and its associated power management circuitry, including fast-charge circuit, self-start circuit, output voltage regulation circuit and hybrid ESU, using a combination of super-capacitor and thin film battery, were developed to achieve continuous operation of energy harvester. Low start-up voltage DC/DC converters have been developed for 1mW level thermoelectric energy harvesting. The novel method of altering thermoelectric generator (TEG) configuration in order to match impedance has been verified in this work. Novel maximum power point tracking (MPPT) circuits, exploring the fractional open circuit voltage method, were particularly developed to suit the sub-1mW photovoltaic energy harvesting applications. The MPPT energy model has been developed and verified against both SPICE simulation and implemented prototypes. Both indoor light and thermoelectric energy harvesting methods proposed in this thesis have been implemented into prototype devices. The improved indoor light energy harvester prototype demonstrates 81% MPPT conversion efficiency with 0.5mW input power. This important improvement makes light energy harvesting from small energy sources (i.e. credit card size solar panel in 500lux indoor lighting conditions) a feasible approach. The 50mm × 54mm thermoelectric energy harvester prototype generates 0.95mW when placed on a 60oC heat source with 28% conversion efficiency. Both prototypes can be used to continuously power WSN for building energy management applications in typical office building environment. In addition to the hardware development, a comprehensive system energy model has been developed. This system energy model not only can be used to predict the available and consumed energy based on real-world ambient conditions, but also can be employed to optimize the system design and configuration. This energy model has been verified by indoor photovoltaic energy harvesting system prototypes in long-term deployed experiments.

Magnetisation of 2.6T in Gadolinium Thin Films

There is renewed interest in rare-earth elements and gadolinium in particular for a range of studies in coupling physics and applications. However, it is still apparent that synthesis impacts understanding of the intrinsic magnetic properties of thin gadolinium films, particularly for thicknesses of topicality. We report studies on 50nm thick nanogranular polycrystalline gadolinium thin films on SiO2 wafers that demonstrate single-crystal like behavior. The maximum in-plane saturation magnetization at 4K was found to be 4pMS4K = (2.61±0.26)T with a coercivity of HC4K = (160±5)Oe. A maximum Curie point of TC = (293±2)K was measured via zero-field-cooled - field-cooled magnetization measurements in close agreement with values reported in bulk single crystals. Our measurements revealed magnetic transitions at T1 = (12±2)K (as deposited samples) and T2 = (22±2)K (depositions on heated substrates) possibly arising from the interaction of paramagnetic fcc grains with their ferromagnetic hcp counterparts.

Three-port DC-DC Converter for Stand-Alone Photovoltaic Systems

System efficiency and cost effectiveness are of critical importance for photovoltaic (PV) systems. This paper addresses the two issues by developing a novel three-port DC-DC converter for stand-alone PV systems, based on an improved Flyback-Forward topology. It provides a compact single-unit solution with a combined feature of optimized maximum power point tracking (MPPT), high step-up ratio, galvanic isolation and multiple operating modes for domestic and aerospace applications. A theoretical analysis is conducted to analyze the operating modes followed by simulation and experimental work. The paper is focused on a comprehensive modulation strategy utilizing both PWM and phase-shifted control that satisfies the requirement of PV power systems to achieve MPPT and output voltage regulation. A 250 W converter was designed and prototyped to provide experimental verification in term of system integration and high conversion efficiency.

Identifying PV module mismatch faults by a thermography-based temperature distribution analysis

Photovoltaic (PV) solar power generation is proven to be effective and sustainable but is currently hampered by relatively high costs and low conversion efficiency. This paper addresses both issues by presenting a low-cost and efficient temperature distribution analysis for identifying PV module mismatch faults by thermography. Mismatch faults reduce the power output and cause potential damage to PV cells. This paper first defines three fault categories in terms of fault levels, which lead to different terminal characteristics of the PV modules. The investigation of three faults is also conducted analytically and experimentally, and maintenance suggestions are also provided for different fault types. The proposed methodology is developed to combine the electrical and thermal characteristics of PV cells subjected to different fault mechanisms through simulation and experimental tests. Furthermore, the fault diagnosis method can be incorporated into the maximum power point tracking schemes to shift the operating point of the PV string. The developed technology has improved over the existing ones in locating the faulty cell by a thermal camera, providing a remedial measure, and maximizing the power output under faulty conditions.

Thermography-based virtual MPPT scheme for improving PV energy efficiency under partial shading conditions

This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array. 

An Adaptive Predictive Control Strategy for RMPPT under Partially Shaded Conditions

As one of key technologies in photovoltaic converter control, Maximum Power Point Tracking (MPPT) methods can keep the power conversion efficiency as high as nearly 99% under the uniform solar irradiance condition. However, these methods may fail when shading conditions occur and the power loss can over as much as 70% due to the multiple maxima in curve in shading conditions v.s. single maximum point in uniformly solar irradiance. In this paper, a Real Maximum Power Point Tracking (RMPPT) strategy under Partially Shaded Conditions (PSCs) is introduced to deal with this kind of problems. An optimization problem, based on a predictive model which will change adaptively with environment, is developed to tracking the global maxima and corresponding adaptive control strategy is presented. No additional circuits are required to obtain the environment uncertainties. Finally, simulations show the effectiveness of proposed method.

Increase of the delivered energy probability in DES using a fuzzy probabilistic modeling

The paper proposes a methodology to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The proposed methodology is based on statistical failure and repair data of distribution components and it uses a fuzzy-probabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A mixed integer nonlinear programming optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

Tensile behaviour of a structural adhesive at high temperatures by the extended finite element method

Component joining is typically performed by welding, fastening, or adhesive-bonding. For bonded aerospace applications, adhesives must withstand high-temperatures (200°C or above, depending on the application), which implies their mechanical characterization under identical conditions. The extended finite element method (XFEM) is an enhancement of the finite element method (FEM) that can be used for the strength prediction of bonded structures. This work proposes and validates damage laws for a thin layer of an epoxy adhesive at room temperature (RT), 100, 150, and 200°C using the XFEM. The fracture toughness (G Ic ) and maximum load ( ); in pure tensile loading were defined by testing double-cantilever beam (DCB) and bulk tensile specimens, respectively, which permitted building the damage laws for each temperature. The bulk test results revealed that decreased gradually with the temperature. On the other hand, the value of G Ic of the adhesive, extracted from the DCB data, was shown to be relatively insensitive to temperature up to the glass transition temperature (T g ), while above T g (at 200°C) a great reduction took place. The output of the DCB numerical simulations for the various temperatures showed a good agreement with the experimental results, which validated the obtained data for strength prediction of bonded joints in tension. By the obtained results, the XFEM proved to be an alternative for the accurate strength prediction of bonded structures.

Uncertainty propagation in inverse reliability-based design of composite structures

An approach for the analysis of uncertainty propagation in reliability-based design optimization of composite laminate structures is presented. Using the Uniform Design Method (UDM), a set of design points is generated over a domain centered on the mean reference values of the random variables. A methodology based on inverse optimal design of composite structures to achieve a specified reliability level is proposed, and the corresponding maximum load is outlined as a function of ply angle. Using the generated UDM design points as input/output patterns, an Artificial Neural Network (ANN) is developed based on an evolutionary learning process. Then, a Monte Carlo simulation using ANN development is performed to simulate the behavior of the critical Tsai number, structural reliability index, and their relative sensitivities as a function of the ply angle of laminates. The results are generated for uniformly distributed random variables on a domain centered on mean values. The statistical analysis of the results enables the study of the variability of the reliability index and its sensitivity relative to the ply angle. Numerical examples showing the utility of the approach for robust design of angle-ply laminates are presented.

CMOS indoor light energy harvesting system for wireless sensing applications

This book discusses in detail the CMOS implementation of energy harvesting. The authors describe an integrated, indoor light energy harvesting system, based on a controller circuit that dynamically and automatically adjusts its operation to meet the actual light circumstances of the environment where the system is placed. The system is intended to power a sensor node, enabling an autonomous wireless sensor network (WSN). Although designed to cope with indoor light levels, the system is also able to work with higher levels, making it an all-round light energy harvesting system. The discussion includes experimental data obtained from an integrated manufactured prototype, which in conjunction with a photovoltaic (PV) cell, serves as a proof of concept of the desired energy harvesting system. © 2016 Springer International Publishing. All rights are reserved.

Modified Discrete PSO to Increase the Delivered Energy Probability in Distribution energy Systems

This paper proposes a PSO based approach to increase the probability of delivering power to any load point by identifying new investments in distribution energy systems. The statistical failure and repair data of distribution components is the main basis of the proposed methodology that uses a fuzzyprobabilistic modeling for the components outage parameters. The fuzzy membership functions of the outage parameters of each component are based on statistical records. A Modified Discrete PSO optimization model is developed in order to identify the adequate investments in distribution energy system components which allow increasing the probability of delivering power to any customer in the distribution system at the minimum possible cost for the system operator. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 180 bus distribution network.

DC Fuzzy Multicriteria Approach to Increase the Probability of Delivering Power in Distribution Networks

This paper proposes a methodology to increase the probability of delivering power to any load point through the identification of new investments. The methodology uses a fuzzy set approach to model the uncertainty of outage parameters, load and generation. A DC fuzzy multicriteria optimization model considering the Pareto front and based on mixed integer non-linear optimization programming is developed in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power to all customers in the distribution network at the minimum possible cost for the system operator, while minimizing the non supplied energy cost. To illustrate the application of the proposed methodology, the paper includes a case study which considers an 33 bus distribution network.

Increase of the Delivered Power Probability in Distribution Networks using Pareto DC Programming

A methodology to increase the probability of delivering power to any load point through the identification of new investments in distribution network components is proposed in this paper. The method minimizes the investment cost as well as the cost of energy not supplied in the network. A DC optimization model based on mixed integer non-linear programming is developed considering the Pareto front technique in order to identify the adequate investments in distribution networks components which allow increasing the probability of delivering power for any customer in the distribution system at the minimum possible cost for the system operator, while minimizing the energy not supplied cost. Thus, a multi-objective problem is formulated. To illustrate the application of the proposed methodology, the paper includes a case study which considers a 180 bus distribution network

PV inverters for module level applications

Dissertação para obtenção do Grau de Mestre em Energias Renováveis – Conversão Eléctrica e Utilização Sustentáveis

Improving the microbial production of biofuels through metabolic engineering

Les défis conjoints du changement climatique d'origine anthropique et la diminution des réserves de combustibles fossiles sont le moteur de recherche intense pour des sources d'énergie alternatives. Une avenue attrayante est d'utiliser un processus biologique pour produire un biocarburant. Parmi les différentes options en matière de biocarburants, le bio-hydrogène gazeux est un futur vecteur énergétique attrayant en raison de son efficacité potentiellement plus élevé de conversion de puissance utilisable, il est faible en génération inexistante de polluants et de haute densité d'énergie. Cependant, les faibles rendements et taux de production ont été les principaux obstacles à l'application pratique des technologies de bio-hydrogène. Des recherches intensives sur bio-hydrogène sont en cours, et dans les dernières années, plusieurs nouvelles approches ont été proposées et étudiées pour dépasser ces inconvénients. À cette fin, l'objectif principal de cette thèse était d'améliorer le rendement en hydrogène moléculaire avec un accent particulier sur l'ingénierie métabolique et l’utilisation de bioprocédés à variables indépendantes. Une de nos hypothèses était que la production d’hydrogène pourrait être améliorée et rendue plus économiquement viable par ingénierie métabolique de souches d’Escherichia coli producteurs d’hydrogène en utilisant le glucose ainsi que diverses autres sources de carbone, y compris les pentoses. Les effets du pH, de la température et de sources de carbone ont été étudiés. La production maximale d'hydrogène a été obtenue à partir de glucose, à un pH initial de 6.5 et une température de 35°C. Les études de cinétiques de croissance ont montré que la μmax était 0.0495 h-1 avec un Ks de 0.0274 g L-1 lorsque le glucose est la seule source de carbone en milieu minimal M9. .Parmi les nombreux sucres et les dérivés de sucres testés, les rendements les plus élevés d'hydrogène sont avec du fructose, sorbitol et D-glucose; 1.27, 1.46 et 1.51 mol H2 mol-1 de substrat, respectivement. En outre, pour obtenir les interactions entre les variables importantes et pour atteindre une production maximale d'hydrogène, un design 3K factoriel complet Box-Behnken et la méthodologie de réponse de surface (RSM) ont été employées pour la conception expérimentale et l'analyse de la souche d'Escherichia coli DJT135. Le rendement en hydrogène molaire maximale de 1.69 mol H2 mol-1 de glucose a été obtenu dans les conditions optimales de 75 mM de glucose, à 35°C et un pH de 6.5. Ainsi, la RSM avec un design Box-Behken était un outil statistique utile pour atteindre des rendements plus élevés d'hydrogène molaires par des organismes modifiés génétiquement. Ensuite, l'expression hétérologue de l’hydrogénases soluble [Ni-Fe] de Ralstonia eutropha H16 (l'hydrogénase SH) a tenté de démontrer que la mise en place d'une voie capable de dériver l'hydrogène à partir de NADH pourrait surpasser le rendement stoechiométrique en hydrogène.. L’expression a été démontrée par des tests in vitro de l'activité enzymatique. Par ailleurs, l'expression de SH a restaurée la croissance en anaérobie de souches mutantes pour adhE, normalement inhibées en raison de l'incapacité de réoxyder le NADH. La mesure de la production d'hydrogène in vivo a montré que plusieurs souches modifiées métaboliquement sont capables d'utiliser l'hydrogénase SH pour dériver deux moles d’hydrogène par mole de glucose consommé, proche du maximum théorique. Une autre stratégie a montré que le glycérol brut pourrait être converti en hydrogène par photofermentation utilisant Rhodopseudomonas palustris par photofermentation. Les effets de la source d'azote et de différentes concentrations de glycérol brut sur ce processus ont été évalués. À 20 mM de glycérol, 4 mM glutamate, 6.1 mol hydrogène / mole de glycérol brut ont été obtenus dans des conditions optimales, un rendement de 87% de la théorie, et significativement plus élevés que ce qui a été réalisé auparavant. En prolongement de cette étude, l'optimisation des paramètres a également été utilisée. Dans des conditions optimales, une intensité lumineuse de 175 W/m2, 30 mM glycérol et 4.5 mM de glutamate, 6.69 mol hydrogène / mole de glycérol brut ont été obtenus, soit un rendement de 96% de la valeur théorique. La détermination de l'activité de la nitrogénase et ses niveaux d'expression ont montré qu'il y avait relativement peu de variation de la quantité de nitrogénase avec le changement des variables alors que l'activité de la nitrogénase variait considérablement, avec une activité maximale (228 nmol de C2H4/ml/min) au point central optimal. Dans la dernière section, la production d'hydrogène à partir du glucose via la photofermentation en une seule étape a été examinée avec la bactérie photosynthétique Rhodobacter capsulatus JP91 (hup-). La méthodologie de surface de réponse avec Box-Behnken a été utilisée pour optimiser les variables expérimentales de façon indépendante, soit la concentration de glucose, la concentration du glutamate et l'intensité lumineuse, ainsi que d'examiner leurs effets interactifs pour la maximisation du rendement en hydrogène moléculaire. Dans des conditions optimales, avec une intensité lumineuse de 175 W/m2, 35 mM de glucose, et 4.5 mM de glutamate,, un rendement maximal d'hydrogène de 5.5 (± 0.15) mol hydrogène /mol glucose, et un maximum d'activité de la nitrogénase de 246 (± 3.5) nmol C2H4/ml/min ont été obtenus. L'analyse densitométrique de l'expression de la protéine-Fe nitrogenase dans les différentes conditions a montré une variation significative de l'expression protéique avec un maximum au point central optimisé. Même dans des conditions optimales pour la production d'hydrogène, une fraction significative de la protéine Fe a été trouvée dans l'état ADP-ribosylée, suggérant que d'autres améliorations des rendements pourraient être possibles. À cette fin, un mutant amtB dérivé de Rhodobacter capsulatus JP91 (hup-) a été créé en utilisant le vecteur de suicide pSUP202. Les résultats expérimentaux préliminaires montrent que la souche nouvellement conçue métaboliquement, R. capsulatus DG9, produit 8.2 (± 0.06) mol hydrogène / mole de glucose dans des conditions optimales de cultures discontinues (intensité lumineuse, 175 W/m2, 35 mM de glucose et 4.5 mM glutamate). Le statut d'ADP-ribosylation de la nitrogénase-protéine Fe a été obtenu par Western Blot pour la souche R. capsulatus DG9. En bref, la production d'hydrogène est limitée par une barrière métabolique. La principale barrière métabolique est due au manque d'outils moléculaires possibles pour atteindre ou dépasser le rendement stochiométrique en bio-hydrogène depuis les dernières décennies en utilisant les microbes. À cette fin, une nouvelle approche d’ingénierie métabolique semble très prometteuse pour surmonter cette contrainte vers l'industrialisation et s'assurer de la faisabilité de la technologie de la production d'hydrogène. Dans la présente étude, il a été démontré que l’ingénierie métabolique de bactéries anaérobiques facultatives (Escherichia coli) et de bactéries anaérobiques photosynthétiques (Rhodobacter capsulatus et Rhodopseudomonas palustris) peuvent produire de l'hydrogène en tant que produit majeur à travers le mode de fermentation par redirection métabolique vers la production d'énergie potentielle. D'autre part, la méthodologie de surface de réponse utilisée dans cette étude représente un outil potentiel pour optimiser la production d'hydrogène en générant des informations appropriées concernant la corrélation entre les variables et des producteurs de bio-de hydrogène modifiés par ingénierie métabolique. Ainsi, un outil d'optimisation des paramètres représente une nouvelle avenue pour faire un pont entre le laboratoire et la production d'hydrogène à l'échelle industrielle en fournissant un modèle mathématique potentiel pour intensifier la production de bio-hydrogène. Par conséquent, il a été clairement mis en évidence dans ce projet que l'effort combiné de l'ingénierie métabolique et la méthodologie de surface de réponse peut rendre la technologie de production de bio-hydrogène potentiellement possible vers sa commercialisation dans un avenir rapproché.