PhD

The research developed in this report lies in the framework of the Wireless Power Transportation (WPT). The carried study aims at optimizing the collecting/rectifying part of the WPT System where recovery of the microwave energy into continue-us energy takes place. This is a complex non-linear process usually difficult to deal with, in theory and in practice, requiring - if rectenna optimization has to be obtained - a good understanding of the conceptuel, experimental and technological aspects involved in rectenna implementation. This fact has been the rationale for bringing us to implement a methodology for the synthesis of a rectenna when it is only allowed to function in a given limited operating condition space. The process exposed in this document consists in making out a simple and yet precise modelling of the various components of the rectenna, where parameters are extracted from some experimental data, so as to subsequently and efficiently optimize the complete System.

Despite the long history and the widespread application of crystallization process, the improvement of its control still remains an open field of research. The aim of this study is to optimize the crystallization process control in sugar industry. In this purpose, three observer- based control strategies are proposed. This thesis consists in five chapters. The first one presents the state of the art of the crystallization process control. In the second chapter, the observation and analyze of the industrial crystallization control lead us to propose alternative control strategies, in terms of controller, controlled and manipulated variables. Since some of these variables are not measured on-line, the third chapter deals with the design of three observers, based on the three most widespread configurations in sugar industry. Results obtained in simulation and on a pilot plant (scale of 1 to 1000) with two monovariable strategies are presented in the fourth chapter. The performances of a multivariable control strategy, in terms of setpoint tracking and disturbances rejection, are studied in the fifth chapter. The overall results obtained in this study show a significant improvement of the supervision and control of the crystallization process in sugar industry.

The research developed in this report deals with a compact 2.45 GHz rectenna design, working at low power level. The rectenna will be used to collect the ambient RF energy, to be used as a source of electrical power. The rectifcation process of the RF wave into DC electrical power is nonlinear. The compact feature of the rectenna is realized by integrating the filter function within the antenna. This integration is achieved by using a circular microstrip patch antenna. Otherwise, this compactness allows the improvement of the RF/DC conversion efficiency at low power level. Avoiding coupling between the antenna and the rectifer with a slit in the ground plane brings an additional answer to the rectenna compactness. As a result of this methodology, simulations show the synthesized rectenna to exhibit a 48% RF/DC rectifcation efficiency at 100 μW on a 10 kΩ resistor value. The experimental implementation of the corresponding structure is measured to exhibit 34% efficiency. Eventually, we propose methodological guidelines and additional techniques for further improvements in the efficiency and the compactness of the rectenna.

To increase the lifetime of wireless sensor networks, a solution is to improve the energy efficiency of the communication's protocol. The grouping of nodes in the wireless sensor network clustering is one of the best methods. This thesis proposes several improvements by changing the settings of the reference protocol LEACH. To improve the energy distribution of "cluster-heads", we propose two centralized clustering protocols LEACH and k-optimized version k-LEACH-VAR. A distributed algorithm, called e-LEACH, is proposed to reduce the periodic exchange of information between the nodes and the base station during the election of "cluster-heads". Moreover, the concept of energy balance is introduced in metric election to avoid overloading nodes. Then we presented a decentralized version of k-LEACH, which in addition to the previous objectives, integrates the overall energy consumption of the network. This protocol, called k-LEACH-C2D, also aims to promote the scalability of the network. To reinforce the autonomy and networks, both routing protocols "multi-hop" probability, denoted CB-RSM and FRSM build elementary paths between the "cluster-heads" and elected the base station. The protocol, CB-RSM, forms a hierarchy of "cluster-heads" during the training phase clusters, with an emphasis on self-scheduling and self-organization between "cluster-heads" to make the networks more scalable. These protocols are based on the basic idea that the nodes have the highest residual energy and lower variance of energy consumption become "cluster-head". We see the central role of consumption of the node in our proposals. This point will be the last part of this thesis. We propose a methodology to characterize experimentally the consumption of a node. The objectives are to better understand the consumption for different sequences of the node status. In the end, we propose a global model of the consumption of the node.

L’objectif de cette thèse est de contribuer au développement de la « partie réception » du projet (au niveau des nœuds de réseau), qui consiste à convertir l’énergie ambiante collectée en énergie continue. Il s’agit de concevoir un système original capable de gérer l'énergie continue recueillie de diverses sources environnementales (sachant qu’en terme de faisabilité et historiquement, le transport d’énergie sans fil a été testé comme source). Le système devrait être capable de gérer plusieurs sources en parallèle dont par exemple des sources AC (vibrations). Ce système est un dispositif intégré en technologie CMOS Si ou SOI.Le défi et l'originalité résident dans les faibles puissances générées (quelques dizaines de micro-Watts) et donc les très faibles puissances pouvant être consommées par le circuit de gestion d'énergie pour viser un très haut rendement. Le but étant comme nous l’avons mentionné d’alimenter des circuits en aval. La maîtrise de la technologie intégrée s’avère donc incontournable pour relever ce défi.En effet, bien que ce concept ait été largement utilisé en macro-échelles comme dans les systèmes solaires ou dans les générateurs hydrauliques, la conception d’un système de récupération d’énergie à micro-échelles pour des dispositifs électroniques miniaturisés présente un vrai challenge. La première contrainte dans ces microsystèmes est l’utilisation de transducteurs d’énergie produisant des tensions DC inférieures à 1V pouvant aussi varier suivant les conditions environnementales (puissance RF, distance,…). A titre d’exemple, les cellules photovoltaïques, les générateurs thermo-électriques ou les dispositifs de transfert d’énergie RF produisent généralement des tensions dans la gamme de 0.2-0.6V. Un convertisseur DC-DC est donc nécessaire pour élever les tensions récupérées à des niveaux permettant le chargement d’une batterie qui servira à l’alimentation d’un dispositif quelconque en aval. Dans ce cadre, il est proposé d’étudier la contribution des circuits de type pompe charge (CP : charge pump) qui peuvent être placés en aval d’un transducteur. Cette étude mènera à la proposition d’une solution permettant d’accumuler le maximum d’énergie et obtenir un rendement de conversion compétitif par rapport à structures de la littérature.D’un point de vu scientifique les points clés se situent : Sur le nombre d’étages de ces pompes charges La topologie des interrupteurs de transfert de charges Le dimensionnement des capacités de transfert de charges L’étude des pertes du pompe charge et le passage nécessaire à la technologie SOILes impédances d’entrée et de sortie de ces structures pour avoir le meilleur rendement de transfert d’énergie.Le dimensionnement de la structure par rapport à une quantité d’énergie continue.

Hydrogen is a candidate for the next generation fuel with a high energy density and an environment friendly behavior in the energy production phase. Micro-organism based biological production of hydrogen currently suffers low hydrogen production yields because the living cells must sustain different cellular activities other than the hydrogen production to survive. To circumvent this, a team have designed a synthetic cell-free system by combining 13 different enzymes to synthesize hydrogen from cellobiose. This assembly has better yield than microorganism-based systems. We used methods based on differential equations calculations to investigate how the initial conditions and the kinetic parameters of the enzymes influenced the productivity of a such system and, through simulations, to identify those conditions that would optimize hydrogen production starting with cellobiose as substrate. Further, if the kinetic parameters of the component enzymes of such a system are not known, we showed how, using artificial neural network, it is possible to identify alternative models that allow to have an idea of the kinetics of hydrogen production. During our study on the system using cellobiose, other cell-free assemblies were engineered to produce hydrogen from different raw materials. Interested in the reconstruction of synthetic systems, we decided to conceive various tools to help the automation of the assembly and the modelling of these new synthetic networks. This work demonstrates how modeling can help in designing and characterizing cell-free systems in synthetic biology.

Fuel Cell (FC) development is expending due to global energy transition. Power generation using FC results in water and heat as by-products, without emission of greenhouse gases. To continue developing and expanding its use as power generators, FC lifetime and reliability have to be enhanced. This thesis work is dedicated to Fault Tolerant Control System (FTCS) applied to water management in PEM Fuel Cells. An appropriate water management of FC allow to avoid irreversible degradations of FC components and performance that lead to an improvement of FC reliability and lifetime.The proposed FTCS is composed of a model-based diagnosis method applied to fault detection and isolation, and a self-tuning PID strategy for oxygen excess ratio control. This strategy is tested and validated on-line on a real FC system.

This work documents the temporal and spatial variability of surface solar radiation (SSR) over the southwest Indian Ocean (SWIO) and Reunion Island using two complementary Regional Climate Models (RCMs): RegCM4 and WRF. The first part of the work is dedicated to the analysis of the temporal variability of SSR based on RegCM4 over the SWIO at a moderate spatial resolution (50km). Because RegCM4 is the first RCM that focuses on the solar radiation research over the SWIO region, a first series of test experiments with this model to illustrate the model performance and its sensitivity to the choice of the physical parameterizations (radiation, convection), the domain size, and the spatial resolution, are performed. The default CCM radiative and the mixed convective scheme: Grell scheme over land and Emanuel scheme over ocean, give better performance over the SWIO compared to the other available options. The interannual, intraseasonal and synoptic climate variability is then examined through the climate indices and several ERA-Interim parameters (U, V, T and RH) are firstly analyzed along with the corresponding RegCM4 output data to check whether the RegCM4 model forced by ERA-Interim reanalyses is able to maintain the El-Nino Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), the Madden-Julian Oscillation (MJO) and the Tropical Temperate Trough (TTT) signals. Secondly, simulated SSR in association with the different modes of variability is examined. In the second part, SSR spatial variability over Reunion Island is analyzed based on WRF simulations at very fine resolution (750m) for seasonal, intraseasonal, and daily time scales. Clustering classification is applied to WRF simulated SSR over Reunion and the effect from the atmospheric circulation is checked together. Météo France observations and CM SAF are used to validate the results of the model. The results indicate that regional climate models have the ability to present the temporal and spatial variability of SSR over Reunion.

The past works found in the literature have focused on either PEM fuel cell or electrolyzer-PEM. Some of the papers even studied the unitised reversible regenerative fuel cell (URFC) and the solar power hydrogen system by integrating both fuel cell and electrolyzer. Unlike the URFC, our design has an individual compartment for each PEMFC and E-PEM systems and named Quasi-URFC. With this new concept, the main objective is to reduce the cost of regenerative fuel cell (RFC) by minimizing the ratio of the catalyst’s geometric surface area of the membrane electrode assembly (MEA) of both cell modes. Apart from that, we also aim to build a compact, light and portable RFC.This research work is divided into three parts: the modeling, assembly of the prototype and the experimentation work. As for the modeling part, a 2D multi-physics model has been developed in order to analyze the performance of a three chamber-regenerative fuel cell, which consists of both fuel cell and electrolyzer systems. This numerical model is based on solving conservation equations of mass, momentum, species and electric current by using a finite-element approach on 2D grids. Simulations allow the calculation of velocity, gas concentration, current density and potential's distributions in fuel cell mode and electrolysis mode, thus help us to predict the behavior of Quasi-RFC. Besides that, the assembly of the first prototype of the new concept of regenerative fuel cell has been completed and tested during the three years of PhD studies. The experimental results of the Three-Chamber RFC are promising in both fuel cell and electrolyzer modes and validate the simulation results that previously obtained by modeling.

Wireless sensor networks (WSNs) technology have been demonstrated to be a usefulmeasurement system for numerous bath indoor and outdoor applications. There is avast amount of applications that are operating with WSN technology, such asenvironmental monitoring, for forest fire detection, weather forecasting, water supplies, etc. The independence nature of WSNs from the existing infrastructure. Virtually, the WSNs can be deployed in any sort of location, and provide the sensor samples accordingly in bath time and space. On the contrast, the manual deployments can only be achievable at a high cost-effective nature and involve significant work. ln real-world applications, the operation of wireless sensor networks can only be maintained, if certain challenges are overcome. The lifetime limitation of the distributed sensor nodes is amongst these challenges, in order to achieve the energy optimization. The propositions to the solution of these challenges have been an objective of this thesis. ln summary, the contributions which have been presented in this thesis, address the system lifetime, exploitation of redundant and correlated data messages, and then the sensor node in terms of usability. The considerations have led to the simple data redundancy and correlated algorithms based on hierarchical based clustering, yet efficient to tolerate bath the spatio-temporal redundancies and their correlations. Furthermore, a multihop sensor network for the implementation of propositions with more features, bath the analytical proofs and at the software level, have been proposed.

The thesis subject dealt in this report lies in the LE²P framework on the energy sustainability of wireless sensor network. This work is dedicated to the reception and rectifying part of wireless power transfer to give energy sustainability to nodes in a sensor network. This process is not new and originate from the years 1950. The behavior of this process is since well-known in several waveguide such technology as microstrip. But the need of drill in those waveguide circuit may be inconvenient and lead to discrepancy from one circuit to another. This was the motivational keystone to the work address in this report which uses coplanar waveguide (CPW) over microstrip. The conception of such devices goes through a good conceptual and experimental understanding of the waveguide technology. The approach in this document consists of using coplanar waveguide while minimizing its drawbacks, in order to avoid drilling in the substrate and ease the realization of the rectifying part by limiting the human interaction.

Nowadays, a significant growth of connected things is observed, exceeding even the worldpopulation. Given the magnitude of this phenomenon, the energy efficiency of communicatingobjects is a crucial issue. Maximizing their lifetime is necessary to ensure a qualityof service. In this regard, the aim of this thesis is to optimize the energy consumption ofwireless communications in a wireless sensor network.The concept of wake-up radio was created a decade ago, which consists of waking up thecommunicating node by a remote radio signal. By default, the node remains in sleepingmode at a very low power consumption. If needed, the node can be woken up on demandthrough a specific radio signal. Thus, the energy consumption of the radio module is greatlyreduced by idle listening to the channel in sleeping mode. However, this wake-up radioprinciple requires the development of new hardware architectures associated with adaptedand innovative communication protocols. Despite recent proposals, the level of technologymaturity has not yet been reached on this subject.Therefore, a wake-up radio system is proposed in this thesis, including a theoreticalcharacterization of its performances. The wake-up receiver consumes 363 nW in sleepingmode and 49.8 µW in receiving mode. Moreover, two new protocols called DoRa and DC-DoRaare proposed with an evaluation of their performances by simulation. The resultsshow that these wake-up radio protocols greatly reduce the energy consumed by the radiomodule, compared to the MAC protocols currently used in wireless sensor networks. Finally,the experimental implementation of the wake-up radio system and protocols enabled thereal performance measurement of our approach in an environment with overhearing andinterference.

Changes in Surface Solar Radiation (SSR) have the potential to significantly impact diverse aspects of the climate system, and notably the socio-economic development of any nation. To identify the possible impacts of climate change on SSR at regional scales (~50 km) over Southern Africa and the South West Indian Ocean (SA-SWIO; 0-40°S ; 0- 100°E) up to the end of the 21st century, a slice downscaling experiment consisting of simulations covering three temporal windows: a) the present 1996-2005; b) the future 2046-2055 and 2090-2099 conducted with the Regional Climate Model (RCM) RegCM version 4, driven by the European Center for Medium-range Weather Forecasting (ECMWF) ERA-Interim reanalysis (ERAINT, only present) and 2 Global Climate Model (GCMs: HadGEM2-ES and GFDL-ESM2M) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under RCP8.5 scenario, are performed and evaluated. Since the slice simulation is of limited temporal coverage, number of regional and driven global models and climate change forcings, mainly because of the limit of available computational resources, the study towards a comprehensive knowledge of SSR changes in context of climate change is thus extended: an ensemble consisting of outputs from 20 regional climate downscaling realisations based on 5 RCMs that participated in the Coordinated Regional Downscaling Experiment (CORDEX) program (CORDEX-Africa) along with their 10 driving GCMs from CMIP5 covering southern Africa (0-40°S; 0- 100°E) during the period of 1990-2099 is analyzed under RCP4.5 and RCP8.5 up to 2099.The slice experiment indicates that 1) RegCM4 simulates present-day seasonal climatology, (surface air temperature, precipitation and SSR) quite well, but has a negative total cloud cover bias (about -20% in absolute percentage) when forced by the ERAINT and the two GCMs. 2) Internal variability of RegCM4-simulated annual means SSR (about 0.2 W/m2) is of one order smaller than the model bias compared with reference data. 3) RegCM4 simulates SSR changes in opposite signs when driven by the different GCMs under RCP8.5 scenario. 4) Electricity potential calculated using first-order estimation based on the RegCM simulations indicates a change less then 2% to 2099 with respect on present level.It is also found from the ensemble study that: 1) GCMs ensemble generally overestimates SSR by about 1 W/m2 in austral summer (December, January, and February, short as DJF) and 7.5 W/m2 in austral winter (June, July and August, short as JJA), while RCMs ensemble mean shows underestimations of SSR by about -32 W/m2 and -14 W/m2 in summer and winter seasons respectively when driven by GCMs. 2) Multi-model mean projections of SSR change patterns simulated by the GCMs and their embedded RCMs are fairly consistent. 3) GCMs project, in their multi-model means, a statistically significant increase of SSR of about 8 W/m2 in RCP4.5 and 12 W/m2 in RCP8.5 by 2099 over Centre Southern Africa (SA-C) and a highly confident decreasing SSR over Eastern Equatorial Africa (EA-E) of about -5 W/m2 in RCP4.5 and -10 W/m2 in RCP8.5 during the DJF season. RCMs simulate SSR change with statistical confidence over SA-C and EA-E area as well with a little spatial extension compared to GCMs. However, in the JJA season, an increase of SSR is found over EA-E of about 5 W/m2 by 2099 under RCP4.5 and 10 W/m2 under RCP8.5, of similar amplitudes in both the GCMs and RCMs simulations. 4) Significant cloudiness decrease (about -6 % to 2099) is found over continent of SA for GCMs and also shown in RCMs. 5) Larger SSR changes are found in the RCP8.5 scenario than in the RCP4.5 scenario in 2099, with about 2.5 W/m2 enhanced changes in GCMs and about 5 W/m2 in RCMs. 6) Either the biases or the changes pattern of SSR are overall correlated with the patterns of total cloud cover from RCMs in CORDEX-Africa program (for RegCM4 as well). The slice experiment indicates that : ...

Wireless sensor networks that are suitable for a wide range of applications, represent a promising solution that meets any requirement for continuous monitoring. The energy autonomy of sensor nodes constitutes a vulnerability factor that directly affects their longevity and the capacity of the network to ensure long coverage of the geographical area of interest. Energy consumption management is the only way to increase the lifespan of these networks and to give them a reasonable autonomy. Software solutions proposed through MAC protocols, bring significant improvements to the minimization of the energy expenditure of sensor nodes. They reduce the idle-listening periods which represents the most expensive operation in terms of energy, in the operation of the wireless sensor nodes. However, Focusing lonely on these solutions is not enough to guarantee acceptable longevity. The only way to optimize energy conservation in the WSN is to constantly put each node in low power mode and use a wakeup mechanism through wake-up signals. This involves the use of low-power wake-up circuits that provide channel monitoring, and trigger node wake-up only whenever event of interest occurs. In this context, a significant amount of work has proposed the use of an addressing mechanism (MAC addresses or other binary informations), to allow non-concerned nodes to quickly return to their sleep state. This approach is interesting, but involves a significant energy expenditure, related to address information’s reception and processing at all nodes. The most energy efficient solution would be the use of another type of address. This thesis is part of the context of minimizing the energy consumption of the WSN, using an addressing system that allows sensor nodes to receive and process the wake-up signals, without turning on their main communication module. It is to eliminate the energy expenditure related to the RF module’s activation and the reception of address packets, by exploiting wakeup signals duration. Our solution is based on the hardware characteristics of the microcontroller (IRQ, Timer/Counter) of sensor nodes. It reduces the complexities related to wakeup signals conditioning. Our solution is implemented on a small network. Its evaluations were done experimentally and its energy performance is compared to a conventional wake-up mechanism without addressing,and a conventional scheme based on duty-cycling.

Based on proton conduction of polymeric electrolyte membrane (PEM) technology, the water electrolysis (PEMWE) offers an interesting solution for efficiency hydrogen production. During the electrolysis process of water in PEMWE, the anodic side is the place where the water is splitting into oxygen, protons and electrons. The aim of this study is to recognize the link between two-phase flows (anode side) and cell performance under low pressure conditions. We have developed three approaches: the analytical approach and the numerical approach validated by the experimental data. For the numerical model, we have developed a two-dimensional stationary PEMWE model that takes into account electro-chemical reaction, mass transfer (bubbly flow), heat transfer and charges balance through the Membrane Electrodes Assembly (MEA). In order to take into account the changing electrical behavior, our model combines two scales of descriptions: at microscale within anodic active layer and MEA scale. The water management at both scales is strongly linked to the slug flow regime or the bubbly flow regime. Therefore, water content close to active surface areas depends on two-phase flow regimes. Our simulation results demonstrate that the transition from bubble to slug flow in the channel is associated with improvement in mass transport, a reduction of the ohmic resistance and an enhancement of the PEMWE efficiency. Regarding the analytical model, we have developed a one-dimensional stationary isothermal PEMWE model that takes into account electro-chemical reaction, mass transfer and charges balance through the Membrane Electrodes Assembly (MEA). The analytical approach permit to obtain mathematical solution of the activation overpotential, the ohmic losses and the bubbles overpotential respectively for the low current density, the middle current density and the high current density. This approach quantify the total overpotential of the cell, function of the operational and intrinsic numbers. In terms of perspective, the analytical model could be used for the diagnostic of the electrolyzer PEM.

Due to the heterogeneous and rapidly-changing cloudiness, tropical islands, such as Reunion Island in the South-west Indian Ocean (SWIO), have significant solar resource that is highly variable from day-to-day. In this study, we propose a new approach for deterministic prediction of daily surface solar radiation (SSR) maps based on four linear regression models: multiple linear regression (MLR), principal component regression (PCR), partial least squares regression (PLSR), and stepwise regression (SR), that we have applied on the SARAH-E@5km satellite data (CM SAF) for the period during 2007-2016. To improve the accuracy of prediction, the multifractal parameters (H,C_1 and α) are proposed to include as new predictors in the predictive model. These parameters are obtained from the analysis of SSR intermittency based on arbitrary order Hilbert spectral analysis. This analysis is the extension of Hilbert Huang Transform (HHT) and it is used to estimate the generalized scaling exponent ξ(q). It is the combination of the Empirical Mode Decomposition and Hilbert spectral analysis (EMD+HSA). In a first step, the multifractal analysis is applied onto one-second SSR measurements form a SPN1 pyranometer in Moufia in 2016. The mean sub-daily, daily and seasonal daily multifractal patterns are derived, and the scaling exponent ξ(q) is analyzed. In a second step, the intermittency study is conducted on one-minute SSR measurements from a SPN1 network with 11 stations in 2014. The spatial patterns for all the stations with the multifractal parameters H,C_1 and α are shown. The variability of singularity spectrum width is considered to study the spatial intermittency at the daily and seasonal scale. Based on this intermittency analysis from measurements at several stations, the universal multifractal parameters (H,C_1 and α) could be taken as new predictors for indicating the multifractal properties of SSR.

In the South-West Indian Ocean, La Réunion Island is located in a strong solar potential. However, its complex topography and tropical climate are obstacles to the best exploitation of renewable energies. Thus, the knowledge of the local solar potential has to be deepen, both on its temporal and spatial variabilities. The research here focuses on this deepening of the local solar deposit. Thus, the use of SARAH-E satellite product (Solar surfAce RAdiation Heliosat - East) allows us to study the irradiance of Reunion Island on 89 pixels and 16 years of hourly data. In a first study, the mean solar potential is mapped by combining its two orbital components: the diurnal and seasonal cycles. Their complementarity permits the extraction of coherent zones with the local atmospheric dynamic. In the second part, the daily perturbations modulating the mean solar potential are detailed in five typical days with specific spatial structures and temporality. We then propose a first link between local solar perturbations and the larger-scale atmospheric processes, namely the Madden-Julian oscillation, the Tropical-Temperate Troughs and Tropical Cyclones. Finally, La Réunion island solar resource is decomposed into (1) an mean cyclic potential, combining seasonal and diurnal evolutions, and (2) typical daily perturbations, with links to larger-scale atmospheric dynamics.

Fuel cells (FC) are powerful systems for electricity production. They have a good efficiency and do not generate greenhouse gases. This technology involves a lot of scientific fields, which leads to the appearance of strongly inter-dependent parameters. It makes the system particularly hard to control and increase the fault’s occurrence frequency. These two issues underline the necessity to maintain the expected system performance, even in faulty condition. It is a so-called “fault tolerant control” (FTC). The present paper aims to describe the state of the art of FTC applied to the proton exchange membrane fuel cell (PEMFC). The FTC approach is composed of two parts. First, a diagnostic part allows the identification and the isolation of a fault. It requires a good a priori knowledge of all the possible faults in the system. Then, a control part, where an optimal control strategy is needed to find the best operating point or to recover the fault.

With the development of fuel cell (FC) and water electrolysis technologies, electrolytic hydrogen is becoming a pillar of the energy transition, a substitute for fossil resources and a tool for integrating intermittent renewable energy sources (RES). On the scale of isolated or islandable microgrids, this transition is based on the development of hybrid systems, coupling photovoltaic (PV) panels and electrolyzers for hydrogen production, storage systems - hydrogen (H2) tanks and batteries (Bat) - and FC for electricity production. This study presents control strategies for a PV-H2-Bat-FC system to optimize intermittent PV energy management while respecting the operating conditions of electrolyzers and FC. First, a MPPT (Maximum Power Point Tracking) control system is developed to ensure the operation of PV at maximum power, and a control strategy based on Model Predictive Control is implemented to define a current reference for the FC, the electrolyzer and the batteries. Secondly, IP controllers are used to regulate these currents. Thirdly, an optimization problem makes it possible to define a commitment plan to use the FC and the electrolyser taking into account energy supply, demand and stocks.

The proton exchange membrane fuel cell is a promising electrochemical converter for production of electricity from the decarbonated hydrogen carrier. However, some technological challenges limit its deployment, such as durability, reliability or financial cost. The active fault-tolerant control strategy is one of the solutions to mitigate any system fault according to three actions: diagnosis, decision and control. This study proposes to develop a generic controller module adaptive to health states through neural networks. Dynamic programming controller, reinforcement learning, and echo-state models are combined for the design of the adaptive controller. This controller employs three neural models with specific roles: an actor, a predictor and a critic. Flooding and membrane drying faults are considered in this study. The proposed controller was able to demonstrate interesting capabilities on a simulation fuel cell model in multi-variable regulation for oxygen stoichiometry, membrane pressure difference and temperature. The results show superior performance of the proposed controller compared to a proportional integral derivative controller. Stability analyses were conducted to prove the continuity of the adaptive controller. The controller has been validated experimentally on a single cell test-bench. The configuration of the test-bench imposed constraints specific to an on-line and real-time application. The generic nature of the controller offers the possibility to switch from one configuration to another without having to design another controller. Several tests are carried out for regulation of the zero-pressure difference at the membrane. The controller was validated on the occurrence of flooding and membrane dryness faults, including actuator and water purging disturbances. The approach and the generic controller adaptive to the states of health proposed in this thesis allow to satisfy control requirements regarding the fault-tolerant control strategy. The first interest lies in the compensation of the multilateral effects of faults that lead to unwanted dynamic changes. Another interest is to be able to modify in situ operating conditions, components or even auxiliaries while being able to ensure a stable and optimal control.

Cell-free systems (CFS) are emerging as a powerful platform for biomanufacturing. The optimisation of the cell-free system is important to achieve maximum yield. The experimental optimisation is time-consuming and expensive. Different kinds of modelling emerged in the last decades, helping to optimise the pathway of interest in a shorter time at a low cost. In this study, we tested two approaches: systemic through the implementation of neural networks, and analytical through the use of differential equations. In the first step, an artificial neural network model was built to predict the flux through the pathway, and in the second step, a new methodology termed GC-ANN was developed to select optimum and cost-efficient enzyme balances for higher flux. This approach showed unexpected betterment of flux estimation, up to 63%. In the third step, a kinetic model was built and estimation of kinetic parameters for selected enzymes was achieved to replicate experimental conditions. Finally, linked to one of the most demanding chemicals, malate synthesis pathway was successfully modelled in the cell-free system. Even though many studies have been performed, biomanufacturing has not yet been possible for malate. The combination of the cell-free system and modelling could help achieve the biomanufacturing of malate. Overall, this thesis explores different mathematical modelling approaches, and their limits, for optimising metabolic pathways.

Launched on September 8, 2020, the national strategy for developing carbon-free hydrogen (H2) is a priority area of investment for France. H2 is now produced mainly from fossil fuels (grey or carbonated H2; blue H2 with CO2 sequestration or carbon-free) via processes that emit high greenhouse gases (GHGs). But it can also be produced by water electrolysis from renewable electricity (green or carbon-free H2) without GHG emissions. Proton exchange membrane electrolyzers (PEMWE) are candidates for the production of green H2. This experimental thesis was carried out to provide additional knowledge on PEMWE to optimize the electrolyzer mode of the new concept of three-chamber reversible fuel cell developed at the LE2P Energy-Lab. The work carried out was based on several PEMWE technological and scientific obstacles. For example, the two-phase fluid management at the anode (gas/liquid) strongly influences the supply of reactant (water) to the catalytic sites as well as the discharge of the reaction product (oxygen) to the outside. The evolution study's of anodic oxygen bubbles on the LGDL surface's (distribution channels and diffusion layer) made it possible to identify several operating zones corresponding to different bullous regimes. The two main ones are a regime of un-coalesced bubbles and a regime of coalesced bubbles. The operation of PEMWE in zoning was validated using other data from characterization methods based on polarization curves and electrochemical impedance spectra (EIS). Thus, the correlation between different anodic bullous regimes and the polarization curves and EIS has been demonstrated. With the intention to interpret the various phenomena occurring during operation, an equivalent electrical diagram has been developed to model the PEMWE. The model made it possible to simulate the resistive behaviour, the transfer of charges and mass in the various operating areas of the PEMWE. A correlation between the CPE parameters (Constant Phase Element) of the equivalent electrical circuit and the mass and charge transfers within the PEMWE has been demonstrated. Thus, it is possible to describe a functioning PEMWE cell's state more precisely from the EIS and polarisation curves. As already announced, anode bubble regimes play a crucial role in the proper functioning of PEMWE. This work has demonstrated these regimes' impact on diffusion (mass transfer) and charges transfer phenomena. Experiments were carried out with different distribution channel topologies whose influence on the performance of PEMWE has been shown. Also, the analysis of the experiments' results made it possible to highlight the impact of the PEMWE cell's ageing on its performance. Thus, instability phenomena on the PEMWE voltage's, time function's and the cell electric current density have been identified.

Advances in microelectronics and integrated technologies have allowed the evolution and growth of the world of nomad connected objects. However, these wireless devices require power and involve notions of maintenance, access and autonomy. Thus, with the aim of contributing to making these devices totally autonomous, this thesis proposes the study of a circuit participating in the supply of these connected objects using integrated technologies and RF Energy Harvesting at 2.45 GHz. We will study and compare two integrated technologies: a more recent one, the FDSOI 28 nm and the other more known and standard, the BULK 350 nm. To achieve a power supply function, we will combine an RF to DC energy rectifier circuit with a voltage boost circuit known as a charge pump. The use of FDSOI technology will allow us to use the advantage of substrate biasing, allowing additional gain in voltage rectification performance. This will allow us to respond to the problem: do the new integrated technologies make it possible to create sufficiently high-performance circuits to participate in the supply of wireless sensors thanks to RF Energy Harvesting? Firstly, our simulation work shows that the FDSOI technology thanks to the polarization of the substrate makes it possible to obtain better threshold voltages for its transistors and thus increase the voltage produced in rectification (transistor mounted as a diode). Second, we dimensioned our circuits using a method of parametric analysis. Finally, after taking into account the parasites resulting from post-layout simulations, we produced two sets of chips in each technology. The results of the simulations and measurements show that it is quite possible to contribute to the power supply of a sensor such as the TelosB in its standby phase by using RF energy recovery and our proposed rectifier circuits. However, the assembly of the different circuits has not been approached in this thesis and constitutes a line of thought for future work as well as the possibility of coupling the RF energy used to supply information.

Off-grid electrical systems are a promising solution to power remote areas, where the lack of electricity access represents a barrier to development. This thesis focuses on isolated microgrids, which are small electrical systems designed to power regions that lack a connection to the main electricity grid. These microgrids, comprising photovoltaic arrays, diesel generators and storage systems are more fragile, and users can experience frequent interruptions if the system is not designed properly. Reliability is thus a critical criterion to ensure viable microgrid projects with a real impact on living conditions for the concerned populations. A multi-objective optimisation method is therefore proposed to design these microgrids considering three objectives: economical, environmental and reliability. The method uses a genetic algorithm to make the configuration of the microgrid evolve towards and optimum and enables visualising trade-offs between all design objectives. All microgrid components including generators, power converters, storage systems and control units are modelled on an energetic scale. The results have shown that reliability can be optimised with a high level of renewable integration with little extra cost. The consideration for component failure has been seen to be beneficial as they impact overall reliability. Reliability is often evaluated in the literature solely regarding power adequacy. The method was then adapted to enable evolutive sizing of microgrids, which has been observed to improve the overall performance. By enabling smaller initial sizing with progressive repowering, the overall long-term cost can be reduced while optimising solicitation on system components. A sensibility analysis has enabled identifying the parameters with high impact on optimisation results. Load consumption evolution is a main uncertainty, whose impact can be reduced with the proposed evolutive sizing.

The present thesis focuses on the control and diagnosis of the fuel cell system in order to increase its reliability. The control of the fuel cell parameters is an important element to ensure its proper operation. Firstly, model-free control is used to control the air stoichiometry and the inlet pressure difference between the electrodes in simulation. Secondly, a validation step on two different fuel cell technologies is performed for the control of the inlet pressure difference and the temperature. The model-free controller has shown an excellent ability to reject disturbances and even to tolerate a fault impacting the back pressure actuator. A diagnostic method derived from model-free controller is presented in this manuscript. This method is based on the reconstruction of the measured output from the ultra-local model used for controlling the systems. The detection of actuator, sensor and even disturbance faults is achieved through a residual that is generated by comparing the measured and estimated output. First, the proposed method is tested in simulation on linear and nonlinear systems to detect actuator, sensor and system faults. Then, a validation step is performedon two different types of fuel cells to detect an actuator fault that affects the back pressure valve, a flooding fault and a temperature sensor fault that leads to either membrane dryout or flooding.

The changing global energy context and the search for mitigation and adaptation solutions to offset the effects of global change are driving the use of renewable resources. These energy sources are characterised by high variability due to their dependence on weather and climate conditions. In order to achieve the French objectives, and more specifically those of Reunion Island, of reducing greenhouse gas emissions, improving energy efficiency and increasing the share of renewable energy in the energy mix, improving knowledge of this variability is a key challenge. In the case of photovoltaic (PV) conversion on the scale of Reunion Island, the control of production variability requires the development and implementation of methods to forecast production over a planning horizon and over the whole territory. These forecasts help to improve the level of penetration of PV electricity thanks to better management of installed and future PV power plants, thus optimising the integration of this resource into the energy mix. The objective of this research is to contribute to the improvement of short and medium term forecasting of PV production. The study is based on a statistical analysis and a forecasting model of PV production, using meteorological parameters. Given the complex and marked topography of Reunion Island, a large number of sites, hosting meteorological sensors, judiciously placed on the island would be essential to carry out this research. However, as the cost of such an installation would be too high, the approach adopted is to generate meteorological data over the whole island at a high resolution, of the order of one square kilometre, and over several years using the regional climate model WRF (Weather Research Forecasting). A variable selection strategy, using Granger causality, is developed in order to select the meteorological variables (predictors) that are useful and relevant for improving the forecast of PV production. A statistical forecasting model, based on the Johansen cointegration method, is proposed using the correlation between previously selected meteorological predictors and PV production. This model allows to estimate the PV production on the whole territory of Reunion. A spatio-temporal model using recurrent neural networks with persistent short-term memory (LSTM) and bi-directional LSTM (Bi-LSTM) is developed in order to produce efficient forecasts over the whole island at three time horizons likely to be of interest to a network manager: M+1, d+1 and h+1. The neural models are compared with the persistence model and the SARIMA statistical model. The methodologies developed could eventually offer an opportunity to provide additional guarantees to the network operator. If efficient forecasting solutions become widespread in the future, this opportunity could open up the market beyond the regulatory threshold of 35% of renewable energy currently imposed.