Harvesting indoor light to supply power to nomad embedded systems

International audienceIt is possible to design a system to supply power to low consumption systems (hundreds of µW to tens of mW) from industrial devices. To develop an autonomous system based on harvesting energy from mixed artificial and natural light, it is mandatory to know which solutions are available and suitable to the conditions of use of the system to be designed. In this paper a comparison of solar cells exposed to different indoor light sources is made. This allows to establish which technology is the most relevant to use in different light environments, in terms of power generation. In addition, the difference in behavior between the two most widely produced solar cells, crystallin and amorphous Si, is depicted. We conclude that for new efficient light sources as fluorescent tubes, CFLs and LEDs, amorphous silicon is the best solution to generate power. On the other hand, crystallin silicon is the most efficient under incandescent, halogen or sunlight exposition

Systèmes d’analyse de la récupération d’énergie lumineuse en intérieur pour l’alimentation d’objets connectés.

Energy autonomy for the connected devices around us is becoming an important issue today. Various sources of ambient energy can be used to supply them with power. However, depending on the type of environment in which they are set up, the ambient energy sources available may vary. Besides, the amount of energy from the available sources can be uneven and inconsistent. The company Bureaux A Partager (BAP), the initiator of this thesis, intends to apply this approach to smart tablet displays used for the shared areas of its offices to reduce the constraints and costs of their installation and use. Yet, the amount of energy consumed by this digital tablet is between one hundred and one thousand times greater than that of devices generally made autonomous by this method of power supply. Therefore, making the tablet autonomous is a major challenge that requires precise knowledge of the energy sources available in its environment and the amount of energy harvestable from them.This industrial thesis first explains how the light seems to be the ambient energy most likely to make a device that consumes on average more than 10 mW of power autonomous in an office environment. The necessity to know the energy available in practice in a specific environment to develop energy harvesting systems adapted to it led to developing a calculation method. It is based on measurements of a photovoltaic converter's electrical and optical characteristics and the ambient light spectrum. The calculations are validated by comparing them with the energy harvesting measurements of a prototype energy harvesting systems. A low-cost analysis system with a low spectral resolution is developed to overcome the constraints associated with the costly and complex instruments required to acquire the light spectrum. Using light source classification and spectral reconstruction methods, the system can perform recoverable energy evaluations equivalent in accuracy to those obtained with high-resolution instruments. Finally, the results of the observations obtained made it possible to establish that, to make the BAP display tablets autonomous, an energy harvesting device with a surface area of approximately 250 cm² of gallium arsenide cells would be suitable.Rendre autonomes en énergie les appareils connectés qui nous entourent devient aujourd’hui un enjeu important. Différentes sources d’énergie ambiante peuvent alors servir à les alimenter. Cependant, selon le type d’environnements dans lesquels ils sont installés, les sources d’énergie ambiante présentes peuvent varier. La quantité d’énergie des sources disponibles peut être inégale et inconstante. L’entreprise Bureaux A Partager (BAP), initiatrice de cette thèse, entend appliquer cette approche à des tablettes d’affichage connectées, utilisées dans les espaces communs de ses bureaux, afin de réduire les contraintes et coûts de leur installation et de leur utilisation. Néanmoins, la quantité d’énergie consommée par cette tablette numérique est entre cent et mille fois supérieure à celle des dispositifs généralement rendus autonomes par cette méthode d’alimentation électrique. La rendre autonome est donc un défi de taille qui nécessite de connaitre avec précision les sources d’énergie à disposition dans son environnement et la quantité d’énergie qui peut en être récupérée.Cette thèse CIFRE expose tout d’abord en quoi la lumière semble être l’énergie ambiante la plus favorable à rendre autonome un appareil qui consomme plus de 10 mW de puissance moyenne dans un environnement de bureaux. Le besoin de connaitre l’énergie récupérable en pratique dans un environnement précis afin de développer des récupérateurs d’énergie adaptés a mené à développer une méthode de calcul. Elle repose sur des mesures de caractéristiques électrique et optique d’un convertisseur photovoltaïque et du spectre lumineux ambiant. Ces performances de calculs sont validées en comparant ses calculs aux mesures de récupération d’énergie d’un prototype de récupérateur. Pour s’affranchir des contraintes liées aux instruments de mesure coûteux et complexes nécessaires à l’acquisition du spectre lumineux, un système d’analyse à faible coût et à faible résolution spectrale est développé. Grâce à l’utilisation de méthodes de classifications des sources lumineuses et de reconstruction spectrale, ce système est capable de réaliser des évaluations de l’énergie récupérable équivalentes en précision à celles obtenues avec les instruments à haute résolution. Les résultats d’observations obtenus ont permis d’établir que pour rendre autonome le dispositif d’affichage de BAP, un récupérateur d’énergie d’une surface d’environ 250 cm² de cellules en arséniure de gallium serait adapté

Low-Cost Sensors for Indoor PV Energy Harvesting Estimation Based on Machine Learning

With the number of communicating sensors linked to the Internet of Things (IoT) ecosystem increasing dramatically, well-designed indoor light energy harvesting solutions are needed. A first step in this direction would be to be able to accurately estimate the harvestable energy in a specific light environment. However, inside, this energy varies in spectral composition and intensity, depending on the emission source as well as the time of day. These challenging conditions mean that it has become necessary to obtain accurate information about these variations and determine their impact on energy recovery performance. In this context, this manuscript presented a method to apply an innovative energy harvesting estimation method to obtain practical and accurate insight for the design of energy harvesting systems in indoor environments. It used a very low-cost device to obtain spectral information and fed it to supervised machine learning classification methods to recognize light sources. From the recognized light source, a model developed for flexible GaAs solar cells was able to estimate the harvestable energy. To validate this method in real indoor conditions, the estimates were compared to the energy harvested by an energy harvesting prototype. The mean absolute error percentage between estimates and the experimental measurements was less than 5% after more than 2 weeks of observation. This demonstrated the potential of this low-cost estimation system to obtain reliable information to design energetically autonomous devices

Light Energy Harvesting Analysis Systems for Indoor Applications

Rendre autonomes en énergie les appareils connectés qui nous entourent devient aujourd’hui un enjeu important. Différentes sources d’énergie ambiante peuvent alors servir à les alimenter. Cependant, selon le type d’environnements dans lesquels ils sont installés, les sources d’énergie ambiante présentes peuvent varier. La quantité d’énergie des sources disponibles peut être inégale et inconstante. L’entreprise Bureaux A Partager (BAP), initiatrice de cette thèse, entend appliquer cette approche à des tablettes d’affichage connectées, utilisées dans les espaces communs de ses bureaux, afin de réduire les contraintes et coûts de leur installation et de leur utilisation. Néanmoins, la quantité d’énergie consommée par cette tablette numérique est entre cent et mille fois supérieure à celle des dispositifs généralement rendus autonomes par cette méthode d’alimentation électrique. La rendre autonome est donc un défi de taille qui nécessite de connaitre avec précision les sources d’énergie à disposition dans son environnement et la quantité d’énergie qui peut en être récupérée.Cette thèse CIFRE expose tout d’abord en quoi la lumière semble être l’énergie ambiante la plus favorable à rendre autonome un appareil qui consomme plus de 10 mW de puissance moyenne dans un environnement de bureaux. Le besoin de connaitre l’énergie récupérable en pratique dans un environnement précis afin de développer des récupérateurs d’énergie adaptés a mené à développer une méthode de calcul. Elle repose sur des mesures de caractéristiques électrique et optique d’un convertisseur photovoltaïque et du spectre lumineux ambiant. Ces performances de calculs sont validées en comparant ses calculs aux mesures de récupération d’énergie d’un prototype de récupérateur. Pour s’affranchir des contraintes liées aux instruments de mesure coûteux et complexes nécessaires à l’acquisition du spectre lumineux, un système d’analyse à faible coût et à faible résolution spectrale est développé. Grâce à l’utilisation de méthodes de classifications des sources lumineuses et de reconstruction spectrale, ce système est capable de réaliser des évaluations de l’énergie récupérable équivalentes en précision à celles obtenues avec les instruments à haute résolution. Les résultats d’observations obtenus ont permis d’établir que pour rendre autonome le dispositif d’affichage de BAP, un récupérateur d’énergie d’une surface d’environ 250 cm² de cellules en arséniure de gallium serait adapté.Energy autonomy for the connected devices around us is becoming an important issue today. Various sources of ambient energy can be used to supply them with power. However, depending on the type of environment in which they are set up, the ambient energy sources available may vary. Besides, the amount of energy from the available sources can be uneven and inconsistent. The company Bureaux A Partager (BAP), the initiator of this thesis, intends to apply this approach to smart tablet displays used for the shared areas of its offices to reduce the constraints and costs of their installation and use. Yet, the amount of energy consumed by this digital tablet is between one hundred and one thousand times greater than that of devices generally made autonomous by this method of power supply. Therefore, making the tablet autonomous is a major challenge that requires precise knowledge of the energy sources available in its environment and the amount of energy harvestable from them.This industrial thesis first explains how the light seems to be the ambient energy most likely to make a device that consumes on average more than 10 mW of power autonomous in an office environment. The necessity to know the energy available in practice in a specific environment to develop energy harvesting systems adapted to it led to developing a calculation method. It is based on measurements of a photovoltaic converter's electrical and optical characteristics and the ambient light spectrum. The calculations are validated by comparing them with the energy harvesting measurements of a prototype energy harvesting systems. A low-cost analysis system with a low spectral resolution is developed to overcome the constraints associated with the costly and complex instruments required to acquire the light spectrum. Using light source classification and spectral reconstruction methods, the system can perform recoverable energy evaluations equivalent in accuracy to those obtained with high-resolution instruments. Finally, the results of the observations obtained made it possible to establish that, to make the BAP display tablets autonomous, an energy harvesting device with a surface area of approximately 250 cm² of gallium arsenide cells would be suitable

Low-Cost Sensors for Indoor PV Energy Harvesting Estimation Based on Machine Learning

With the number of communicating sensors linked to the Internet of Things (IoT) ecosystem increasing dramatically, well-designed indoor light energy harvesting solutions are needed. A first step in this direction would be to be able to accurately estimate the harvestable energy in a specific light environment. However, inside, this energy varies in spectral composition and intensity, depending on the emission source as well as the time of day. These challenging conditions mean that it has become necessary to obtain accurate information about these variations and determine their impact on energy recovery performance. In this context, this manuscript presented a method to apply an innovative energy harvesting estimation method to obtain practical and accurate insight for the design of energy harvesting systems in indoor environments. It used a very low-cost device to obtain spectral information and fed it to supervised machine learning classification methods to recognize light sources. From the recognized light source, a model developed for flexible GaAs solar cells was able to estimate the harvestable energy. To validate this method in real indoor conditions, the estimates were compared to the energy harvested by an energy harvesting prototype. The mean absolute error percentage between estimates and the experimental measurements was less than 5% after more than 2 weeks of observation. This demonstrated the potential of this low-cost estimation system to obtain reliable information to design energetically autonomous devices

Redox-active ions unlock substitutional doping in halide perovskites

International audienceElectrical doping of metal halide perovskites (MPHs) is a key step towards the use of this efficient and cost-effective semiconductor class in modern electronics. In this work, we demonstrate n-type doping of methylammonium lead iodide (CH3NH3PbI3) by the postfabrication introduction of Sm2+. The ionic radius of the latter is similar to that of Pb2+ and can replace it without altering the perovskite crystal lattice. It s demonstrated that once incorporated, Sm2+ can act as a dopant by undergoing oxidation to Sm3+. This results in the release of a negative charge that n-dopes the material, resulting in an increase of conductivity of almost 3 orders of magnitude. Unlike substitution doping with heterovalent ions, furtive dopants do not require counterions to maintain charge neutrality with respect to the ions they replace and are thus more likely to be incorporated into the crystalline structure. The incorporation of the dopant throughout the material is evidenced by XPS and ToF-SIMS, while the XRD pattern shows no phase separation at low andmedium doping concentrations. A shift of the Fermi level towards a conduction energy of 0.52 eV confirms the doping to be n-type with a charge carrier density, calculated using the Mott–Schottky method, estimated to be nearly 1017 cm 3 for the most conductive samples. Variable-temperature conductivity experiments show that thedopant is only partially ionized at room temperature due to dopant freeze-out

Sources d'énergies indoor pour objets communicants énergétiquement autonomes

International audienc

Indoor energy micro-sources for energetically antonomous nomadic devices

International audienc