研究目的
To develop and validate a high-resolution BIPV modeling and optimization method that addresses complex geometries, non-uniform irradiance, and partial shading to maximize energy yield and minimize losses in urban environments.
研究成果
The presented method effectively optimizes BIPV systems by minimizing mismatch losses through genetic algorithms and high-resolution simulations. Longitudinal cell orientation outperforms orthogonal by up to 8%, and bypass diodes have limited benefits. The approach is validated for various conditions and applied in a case study, showing practical applicability for urban BIPV design.
研究不足
The simplified simulation for string layout optimization could be improved to include more loss types. Genetic optimization does not guarantee global optimum. Building-scale validation has not been performed yet. System cost and economics are not addressed. Mounting type influence on temperature is omitted. Inverter efficiency is assumed constant, which is a simplification.
1:Experimental Design and Method Selection:
The methodology involves a parametric 3D modeling tool (Rhino/Grasshopper) coupled with high-resolution ray-tracing irradiance simulation (Daysim) and an electrical model based on the single diode model on a subcell level. A genetic algorithm is used for optimizing electrical interconnections.
2:Sample Selection and Data Sources:
Validation is conducted using thin-film CIGS modules (MiaSolé Flex01 70N and Flex-03N) under various shading and curvature conditions. Weather data is sourced from EPW files and MeteoSwiss.
3:List of Experimental Equipment and Materials:
Equipment includes pyranometers for irradiance measurement, IV-curve measurement setups, and computational tools like Rhino/Grasshopper, Daysim, Python, and PV Lib toolbox. Materials include CIGS modules with specific parameters.
4:Experimental Procedures and Operational Workflow:
The workflow includes geometry definition, irradiance simulation, string layout optimization using genetic algorithms, and high-resolution electrical simulation. Validation involves measuring IV-curves and comparing with simulations.
5:Data Analysis Methods:
Data is analyzed using root mean square error (RMSE) for validation, performance ratio calculations, and disaggregated loss analysis (e.g., angle of incidence losses, temperature losses, mismatch losses).
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Rhino
McNeel
Parametric 3D modeling tool for geometry definition and module placement.
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Grasshopper
McNeel
Visual programming language integrated with Rhino for parametric design.
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Daysim
NING
Radiance-based ray-tracing tool for high-resolution irradiance simulation.
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Python
Python Software Foundation
Programming language used for process interconnection, optimization, and data analysis.
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PV Lib toolbox
GitHub
Python module for photovoltaic performance modeling, including parameter transformation and IV-curve calculation.
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DEAP module
DEAP
Evolutionary algorithms framework used for genetic optimization in Python.
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System Advisor Model
SAM
National Renewable Energy Laboratory (NREL)
Software for photovoltaic system performance modeling and database access for module parameters.
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MiaSolé Flex01 70N
Flex01 70N
MiaSolé
Thin-film CIGS photovoltaic module used for experimental validation under partial shading and curvature conditions.
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MiaSolé Flex-03N
Flex-03N
MiaSolé
Thin-film CIGS photovoltaic module used in case study for performance analysis.
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Sunny Boy 240
Sunny Boy 240
SMA
Microinverter used for DC to AC conversion in module-level MPPT configurations.
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Sunny Tripower 6000TL
Sunny Tripower 6000TL
SMA
String inverter used for DC to AC conversion.
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Sunny Tripower 9000TL
Sunny Tripower 9000TL
SMA
Central inverter used for DC to AC conversion in series-parallel configurations.
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Pyranometer
Instrument for measuring solar irradiance during experimental validation.
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