Scientific direction Development of key enabling technologies
Transfer of knowledge to industry

PhD : selection by topics

Technological challenges >> Solar energy for energy transition
6 proposition(s).

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Diagnostic and prognostic tools for inverters and PV modules using machine-learning approaches

Département des Technologies Solaires (LITEN)

Laboratoire des Systèmes PV Appliqués

01-09-2021

SL-DRT-21-0347

sylvain.lespinats@cea.fr

Solar energy for energy transition (.pdf)

Framework: In the current context of climate change, the issue of energy is central from a societal point of view and from a political or economic point of view. Solar production, which is a renewable alternative to carbon-based energies, is growing exponentially and this rise in power will probably continue in the years to come. One of the best ways to lower the financial and environmental cost of solar power plants is automatic diagnostics, which can detect and correct plant failures and thus increase their performance. Basically, photovoltaic power plants are made up of modules connected to an inverter. The modules produce direct current which is converted into alternating current by the inverter for transport on the distribution network. The failures and aging of these devices are the main source of non-trivial failures. For example, the lifetime of a power plant is generally estimated at 20 or 30 years, to be compared to only 10 years for an inverter. It is very common for the current and voltage upstream and downstream of the inverter to be monitored. These data are generally supplemented by meteorological measurements (irradiance and temperature in particular). These data are however under-exploited. In the case of the behavior of the modules, it is mostly due to the strong correlation with various factors including daily and seasonal phenomena, weather conditions, relative position of the sun, non-linear interactions between the different modules, aging continue, break, etc. In the case of inverters, the difficulties are mainly due to the strong dependence on the operating conditions and on the noise level of the measurement largely higher than the signal (as encountered in the context of the detection of gravitational waves by the LIGO project). Objective: From these data we want to provide a close monitoring of photovoltaic plants, diagnose failures and anticipate them. In that goal, based, on the one hand, on the very large amount of data which can counter the signal-to-noise problem, and on machine-learning on the other hand, we will isolate the different explanatory components. Firstly, the modules and inverters will be considered separately. Secondly, we will consider the system as a whole. In the past, the LSPV (CEA) and LAMA UMR 5127 (Savoie Mont Blanc University) laboratories have collaborated on the development of dimensionality reduction methods. These methods (probably to be adapted) make it possible to explore the datasets in order to extract behaviors that can be linked to various modes of operation and aging. This step will allow definoing classes for regression / classification methods. The final goal is a diagnostic tools deployable onto power plant monitoring systems. Desired profile: We are looking for a student in mathematics interested in applications in the field of renewable energy and electronics or a student in engineering sciences passionate about mathematics. Experience in electronics is not necessary, but the candidate may operate measurements in laboratory under the supervision of electronics and photovoltaic engineers to produce data or confirm behavior. The tools used may include dimension reduction methods, statistics (descriptions and tests), time series analysis, SVMs, neural networks or tensor methods.

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Multiphysical design of high-voltage power semiconductor modules for renewable energy conversion

Département des Technologies Solaires (LITEN)

Laboratoire Systèmes PV

01-09-2021

SL-DRT-21-0387

jeremy.martin@cea.fr

Solar energy for energy transition (.pdf)

Research and development around silicon carbide (SiC) power semiconductors provides samples that can withstand voltages up to 15kV. These devices switch at very high speeds (e.g. 120kV / µs for a 10kV SiC MOSFET or 180kV / µs for a 15kV SiC IGBT). Overall, the performances of these semiconductors are exceptional, and drastically reduces the switching losses compared to Silicon equivalents. The implementation of these switches is on the other hand very delicate and calls upon methodologies of multiphysics design in transversal disciplinary fields. It is, from the scientific literature addressed a number of scientific and technological obstacles that we can list: -Minimization of parasitic inductors of power modules (<5nH) -Integration of EMC shielding to collect disturbing impulse currents -Cooling of SiC chips so the size is very small compared to a Si equivalent -Management of partial discharges and dielectric materials -Influence of dV / dt on the aging of materials (in DC, at 50Hz, and in pulse) -Reflection phenomena (electromagnetic wave) The proposed work consists of studying and proposing a power module architecture integrating innovations making it possible to address the implementation of SiC chips up to 10kV. The teams from the CEA in Toulouse specialists in high power 3D packaging will provide their skills in assembly technologies for the production of complex power modules. The CEA teams at INES campus (Nat. Inst. of Solar Energy)located at the Bourget du Lac (Savoy) will provide their high voltage measurement and prototyping means as well as their knowledge in power module design (finite element simulation). Researchers from G2ELAB in Grenoble in cooling of power modules and dielectric science will use their knowledge as well as their experimental platforms.

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Perovskite materials: influence of nanocrystallization processes on the performances of PK cells for tandem integration

Département des Technologies Solaires (LITEN)

Laboratoire des Cellules Tandem

01-10-2021

SL-DRT-21-0526

noella.lemaitre@cea.fr

Solar energy for energy transition (.pdf)

After several decades of intense development, silicon-based PV is a well-established and mature technology that now nears its practical efficiency limit. One strategy to overcome this limit is to use multi-junctions solar cells coupling a silicon subcell with a topcell based on a higher band gap absorber (1,6 - 1,7 eV vs 1.12 eV for silicon) exhibiting high efficiency. Lead halide perovskites (with ABX3 structure) can fulfill these requirements. Such materials can be integrated via solution processing at low temperature and yield theoretical efficiencies well beyond 30% when combined in a tandem device with a silicon subcell. To this end, controlling perovskite crystallization from precursors solution is obviously of prime importance. Also, the development of upscalable techniques to process the perovskite is one of the main practical challenge still to be met to ensure a practical deployment of the technology. The strategy currently developed within CEA relies on a gas-quenching of the precursors wet film to trigger perovskite crystallization. The main goal of this PhD will be to study in-depth the perovskite crystallization when processed in such conditions, to pave the way towards successful integration in tandem devices.

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Improvement and understanding of the performance of silicon cell-based solar generators in harsh environments

Département des Technologies Solaires (LITEN)

Laboratoire des applications modules

01-10-2021

SL-DRT-21-0879

romain.cariou@cea.fr

Solar energy for energy transition (.pdf)

The thesis will be carried out at the interface of several laboratories of the Department of Solar Technologies (DTS) of the CEA located in Le Bourget du Lac on the campus of the National Institute for Solar Energy (INES). The objective of this thesis is to improve the resistance to environmental conditions (radiation, e/H+, UV, thermal cycling) of space solar generators based on silicon solar cells, and to better understand the degradation mechanisms of cells/materials associated. By finely controlling the manufacturing of cells (doping, impurity, architecture, etc.) and modules (materials, thickness, architecture, optical trapping, etc.), it is possible to improve the performance of silicon modules at the end of their lifetime while maintaining a competitive price (?/W), 1 to 3 orders of magnitude lower than space III-V modules.

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Reliability improvement of photovoltaic modules with coupled modelling / experimental approaches

Département des Technologies Solaires (LITEN)

Laboratoire des applications modules

01-09-2021

SL-DRT-21-0913

bertrand.chambion@cea.fr

Solar energy for energy transition (.pdf)

The performance and lifespan of photovoltaic (PV) modules depend on their ability to withstand various environmental constraints, including those related to thermomechanical phenomena. While this observation is true for ?classic? modules packaging installed in PV power plants, it is amplified for installation in specific climates areas, and becomes dimensioning and critical for the development of innovative modules for applications in severe environments. . The objective of the PhD work is to improve the reliability and lifespan of photovoltaic modules through thermomechanical simulation, by anticipating the behaviour of internal stress levels during the life of the PV modules. For a given application, this understanding will allow adjustments of the initial thermomechanical state within a module after assembly, in order to optimize its lifespan. The work is planned to be devided into the following steps: - First, state of the art on PV technologies, module assembly processes and understanding the existing works within the teams, particularly on the thermomechanical numerical models linked to the PV modules assembly (initial at t0). Also, specific ageing protocols will be developed on key materials (focus on polymers), associated to material characterization tools, to determine the thermomechanical material characteristics variations during aging. - Secondly, a thermomechanical model will be built, verified by experimental tests and will allow to integrate the variation of material properties during the life of the PV module. - Finally, the scientific perspective on these two first phases will result in a predictive numerical tool able to set the optimal thermomechanical state of a module after assembly (t0), to optimize the module lifespan for a given application.

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Interconnection reducing or removing the use of non sustainable material to reduce photovoltaic footprint

Département des Technologies Solaires (LITEN)

Laboratoire des applications modules

01-10-2021

SL-DRT-21-0966

vincent.barth@cea.fr

Solar energy for energy transition (.pdf)

Photovoltaic (PV) industry consumes nearly 10% of the world's silver production (2019 data) and its constant growth is likely to create a short-term problem. Silver is mainly used in the interconnection of photovoltaic cells, specifically for the metallization. Today heterojunction cells provide the highest efficiency and a low temperature coefficient. These characteristics allow to obtain an excellent LCOE (Levellized Cost Of Energy). However, mandatory use of low temperature silver paste which are less conductive and cannot be easily soldered requires to deposit more silver and the problem of silver consumption is further amplified. Different approaches can be explored to solve this problem. Increasing wires number, cutting the cells or using low temperature soldering methods are the first solutions. Replacement of silver by other conductive particles are another way. The thesis proposes to explore the different approaches and after an LCA analysis to develop the most interesting one for a sustainable development of PV.

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