Degradation, mitigation and forecasting approaches in thin film photovoltaics /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Deb, Dipankar
Otros Autores: Bhargava, Kshitij
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Academic Press, 2022.
Temas:
Photovoltaic cells > Materials.
Thin films.
Cellules photovolta�iques > Mat�eriaux.
Couches minces.
Photovoltaic cells > Materials
Thin films
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover
  • Degradation, Mitigation, and Forecasting Approaches in Thin Film Photovoltaics
  • Copyright
  • Contents
  • List of figures
  • List of tables
  • Biography
  • Preface
  • Acknowledgements
  • Acronyms
  • 1 Introduction to photovoltaics
  • 1.1 Introduction
  • 1.2 Scenario of global energy requirements
  • 1.3 Global warming and renewable energy
  • 1.4 Brief overview of PV manufacturing
  • 1.5 Characteristics of PV cell
  • 1.5.1 Quantum efficiency versus wavelength characteristics
  • 1.5.2 Current versus voltage characteristics
  • 1.6 Current status of PV technology
  • 1.7 Does PV pay back?
  • Bibliography
  • 2 Thin-film photovoltaics
  • 2.1 Introduction
  • 2.2 Photovoltaic effect
  • 2.3 Some popular TFPV absorber materials
  • 2.3.1 Amorphous silicon (a-Si)
  • 2.3.2 Cadmium telluride (CdTe)
  • 2.3.3 Copper indium gallium selenide (CIGS)
  • 2.3.4 Copper zinc tin sulphide (CZTS)
  • 2.3.5 Organic semiconductors
  • 2.3.6 Organic-inorganic hybrid perovskite semiconductors
  • 2.4 Conventional and emerging PV materials
  • 2.5 Photovoltaic energy conversion
  • 2.6 Thin-film photovoltaic manufacturing and recycling
  • Bibliography
  • 3 Performance-limiting issues in TFPVs
  • 3.1 Introduction
  • 3.2 Crystal defects
  • 3.2.1 Point defects
  • 3.2.2 Line defects
  • 3.2.3 Planar defects
  • 3.2.4 Volume defects
  • 3.3 Carrier generation and recombination
  • 3.4 Mobility degradation by scattering and grain boundary
  • 3.5 Environmental and other factors
  • 3.5.1 Effect of dust accumulation
  • 3.5.2 Effect of humidity
  • 3.5.3 Effect of wind
  • 3.5.4 Effect of temperature
  • 3.5.5 Effect of module orientation
  • 3.5.6 Effect of shading
  • 3.6 Leakage current and potential induced degradation
  • Bibliography
  • 4 Yield increase through soiling prevention
  • 4.1 Introduction
  • 4.2 Measuring output of PV cells, modules
  • and systems.
  • 4.3 Methods of cleaning solutions
  • 4.3.1 Forced flow from air-conditioning systems
  • 4.3.2 Rainfall, water-based and manual cleaning
  • 4.3.3 Mechanized cleaning and electrodynamic screens (EDS)
  • 4.3.4 Super hydrophobic and hydrophilic planes (SHOP and SHIP)
  • 4.4 Mechanisms behind degradation and techniques to detect degradation
  • Bibliography
  • 5 Water-free automated solar-panel cleaning
  • 5.1 Semiautomatic water-based cleaning solutions
  • 5.2 Automated panel cleaning unit
  • 5.3 Specifications of service unit
  • 5.4 Process command flow of operations in a MicroController
  • 5.5 Quantitative measurement of the effect of cleaning
  • Bibliography
  • 6 Numerical simulations of potential-induced degradation
  • 6.1 Basics of potential-induced degradation
  • 6.2 Simulation methodology
  • 6.3 Simulation-based analysis of PID effects in TFPV cells
  • 6.3.1 Effect of PID in nongraded CIGS cells
  • 6.3.2 Effect of PID in graded CIGS cells
  • 6.3.3 Effect of PID in CZTS, CZTSe and CZTSSe cells
  • Bibliography
  • 7 PID for multicrystalline soiled panels: a forecasting-based approach
  • 7.1 Introduction
  • 7.2 Experimental setup and methodology
  • 7.3 Forecasting methods
  • 7.3.1 Persistence learning algorithm (PLA)
  • 7.3.2 Auto-regressive integrated moving average (ARIMA)
  • 7.3.3 Single exponential smoothing (SES)
  • 7.3.4 Artificial neural networks (ANN)
  • 7.3.5 Support vector regression (SVR)
  • 7.3.6 Random forests
  • 7.3.7 Gradient boosting method
  • 7.4 Results and discussions
  • 7.4.1 Correlation study of parameters
  • 7.4.2 Forecasting results
  • 7.5 Conclusions
  • Bibliography
  • 8 Optimization of on-site PID detection methods
  • 8.1 Introduction
  • 8.2 Adopted methodology
  • 8.3 Existing PID detection techniques
  • 8.3.1 Electroluminescence (EL) imaging
  • 8.3.2 Thermal imaging
  • 8.3.3 Open-circuit voltage measurement.
  • 8.3.4 Operating voltage measurement
  • 8.3.5 Current voltage (IV) curve tracing
  • 8.3.6 Dark current-voltage (IV) curve tracing
  • 8.4 Application of multiple-criteria decision-making (MCDM) techniques
  • 8.4.1 Simple additive weighting (SAW)
  • 8.4.2 Technique for order of preference by similarity to ideal solution (TOPSIS)
  • 8.4.3 Elimination Et Choix Traduisant la Reali�t (ELECTRE)
  • 8.5 Results and discussions
  • Bibliography
  • 9 Next generation photovoltaics
  • 9.1 Recently developed photovoltaics
  • 9.1.1 Kesterite photovoltaics
  • 9.1.2 Dye-sensitized photovoltaics
  • 9.1.3 Organic photovoltaics
  • 9.1.4 Quantum-dot photovoltaics
  • 9.1.5 Perovskite photovoltaics
  • 9.2 Commercialization challenges for next-generation PVs
  • 9.3 Current research status and forecast for next-generation PVs
  • Bibliography
  • Index
  • Back Cover.

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