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Light(Science & Applications) 2013年第1期2卷 32-37页

作者： Zachary C Holman Stefaan De Wolf christophe ballif Swiss Federal Institute of Technology Lausanne(EPFL)Institute of Microengineering(IMT)Photovoltaics and Thin-Film Electronics LaboratoryCH-2000 NeuchaˆtelSwitzerland

Imperfect internal reflectance of near-bandgap light reduces the performance of all solar cells,and becomes increasingly detrimental as absorbers become *** consider light incident on the silicon/dielectric/metal structure at the back of rear-passivated crystalline silicon solar cells with surface textures that are large enough for geometric *** calculating the absorbance in the metal as a function of the angle of incidence,we discover three results that are important for understanding and improving rear reflectors in many types of solar ***,significant parasitic absorption occurs in the metal layer in two cases:s-and p-polarized propagating modes(near-normal angles of incidence)when the dielectric thickness is adjusted to cause destructive interference of the reflected beams,and p-polarized evanescent modes(angles of incidence above the semiconductor/dielectric critical angle)that excite surface plasmon polaritons at the metal ***,the latter loss dominates;a well-designed rear dielectric passivation layer must suppress the penetration of evanescent waves to the ***,when used as an input in a simple analytical model,the average rear internal reflectance calculated by assuming a Lambertian angular distribution of light accurately predicts the total reflectance and absorbance of a solar cell.

关键词： light trapping photovoltaics plasmon silicon solar cell

Passivating contact-based tunnel junction Si solar cells using machine learning for tandem cell applications

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Energy and AI 2023年第4期14卷 550-558页

作者： HyunJung Park Audrey Morisset Munho Kim Hae-Seok Lee Aicha Hessler-Wyser Franz-Josef Haug christophe ballif Photovoltaics and Thin Film Electronics Laboratory(PV-Lab) EPFLSchool of Engineering(STI)Maladière 71bNeuchâtelCH-2000Switzerland School of Electrical and Electronic Engineering Nanyang Technological University50 Nanyang Avenue639798SingaporeSingapore Graduate School of Energy and Environment(KU-KIST Green School) Korea University145Anam-roSeongbuk-gu02841SeoulRepublic of Korea

Tandem solar cells are a key technology for exceeding the theoretical efficiency limit of single-junction *** of the most promising combinations is the silicon–perovskite tandem cells,considering their potential for high efficiency,fabrication on a large scale,and low *** most research focuses on improving each subcell,another key challenge lies in the tunnel junction that connects these subcells,significantly impacting the overall cell ***,we demonstrate the first use of tunnel junctions using a stack of p+/n+polysilicon passivating contacts deposited directly on the tunnel oxide to overcome the drawbacks of conventional metal oxide-based tunnel junctions,including low tunneling efficiency and sputter *** Random Forest analysis,we achieved high implied open circuit voltages over 700 mV and low contact resistivities of 500 mΩcm 2,suggesting fill factor losses of less than 1%abs for the operating conditions of a tandem cell.

关键词： Tunnel junction Tandem Passivating contact Solar cell Machine learning

Rule-based scheduling of air conditioning using occupancy forecasting

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能源与人工智能(英文) 2020年第2期2卷 43-53页

作者： Marina Dorokhova christophe ballif Nicolas Wyrsch Photovoltaics and Thin-Film Electronics Laboratory(PV-Lab)Ecole Polytechnique Federale de Lausanne(EPFL) Institute of Microengineering(IMT)Rue de la Maladière 71bNeuchatel 2000Switzerland

Heating,ventilation and air conditioning systems represent considerable potential for energy savings,which can be realized through intelligent occupancy-centered control *** this work,both supervised and unsupervised algorithms to forecast occupancy are proposed with the highest accuracies of 98.3%and 97.6%,*** on their output,a rule-based air conditioning scheduling technique is *** an example,a potential of 15.4%of energy savings is calculated using a dataset collected in a mid-size(4000 m 2)building in Portugal.

关键词： Automation Energy savings HVAC control Occupancy forecasting Thermal comfort

A 3D indicator for guiding AI applications in the energy sector

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能源与人工智能(英文) 2022年第3期9卷 65-77页

作者： Hugo Quest Marine Cauz Fabian Heymann Christian Rod Lionel Perret christophe ballif Alessandro Virtuani Nicolas Wyrsch École Polytechnique Fédérale de Lausanne(EPFL) Institute of Electrical and Micro Engineering(IEM)Photovoltaics and Thin-Film Electronics Laboratory(PV-LAB)NeuchâtelSwitzerland S Swiss Solar Solutions AG ThunSwitzerland Planair SA Yverdon-les-BainsSwitzerland Swiss Federal Office for Energy(SFOE) Digital Innovation OfficeIttigenSwitzerland Swiss Center for Electronics and Microtechnology(CSEM) Sustainable Energy CenterNeuchâtelSwitzerland

The utilisation of Artificial Intelligence (AI) applications in the energy sector is gaining momentum, withincreasingly intensive search for suitable, high-quality and trustworthy solutions that displayed promisingresults in research. The growing interest comes from decision makers of both the industry and policydomains, searching for applications to increase companies’ profitability, raise efficiency and facilitate theenergy transition. This paper aims to provide a novel three-dimensional (3D) indicator for AI applicationsin the energy sector, based on their respective maturity level, regulatory risks and potential benefits. Casestudies are used to exemplify the application of the 3D indicator, showcasing how the developed frameworkcan be used to filter promising AI applications eligible for governmental funding or business *** addition, the 3D indicator is used to rank AI applications considering different stakeholder preferences(risk-avoidance, profit-seeking, balanced). These results allow AI applications to be better categorised in theface of rapidly emerging national and intergovernmental AI strategies and regulations that constrain the useof AI applications in critical infrastructures.

关键词： Artificial intelligence Digitalisation AI application Big data AI policy Energy sector

Investigations on Fill-Factor Drop of Microcrystalline Silicon P-I-N Solar Cells Deposited onto Highly Surface-textured ZnO Substrates

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Investigations on Fill-Factor Drop of Microcrystalline Silic...