Background & Objective
Due to the policy goals for sustainable energy production, renewable energy plants such as photovoltaics are increasingly in use. The energy production from solar radiation depends strongly on atmospheric conditions. As the weather mostly changes, electrical power generation fluctuates, making technical planning and control of power grids to a complex problem. Due to used materials (semiconductors e.g. silicon, gallium arsenide, cadmium telluride) the photovoltaic cells are spectrally selective. It means that only radiation of certain wavelengths converts into electrical energy. A material property called spectral response characterizes a certain degree of conversion of solar radiation into the electric current for each wavelength of solar light.
The AM 1.5 air mass is a standardized spectral composition of solar radiation widely used for testing of solar devices in the photovoltaic industry. It is enough to compare the photovoltaic modules with each other. However, real solar radiation during time does not have a constant spectral composition.
The current study is a part of the research project MetPVNet: “Satellite- and meteorology supported prediction of energy production from the photovoltaics at the distribution level: development, validation, application“ supported by the German Federal Ministry of Economics and Energy (BMWi) and coordinated by the University of Bonn-Rhein-Sieg (H-BRS). The aim of the study is to identify and quantify the influence of the variable spectral composition of solar radiation on the electrical yields of photovoltaic systems under real occurring atmospheric conditions.
A model chain connecting a spectrally resolved solar radiation transfer-model or spectrally resolved irradiance data (input) and a model for a photovoltaic module considering spectral response to calculate electric power (output) was created for this purpose. The PV-model is realised in MATLAB/Simulink and its spectral resolution takes place directly inside the electrical circuit (the photocurrent is determined with help of the incident solar radiation and the above-mentioned spectral response). The spectral- and time-resolved radiation data calculated by the radiative transfer model LibRadtran builds up the PV-model input. The model chain allows the systematic generation of scenarios about the location (latitude, overall atmospheric composition), position of PV-modules in relation to the sun (inclination, alignment) and atmospheric parameters (aerosols, clouds). The validation of the model chain is carried out with the spectral and time-resolved data from the MetPVNet measurement campaign (Allgäu, 2018).
Principal Findings and Conclusion
The main drivers for spectral variability of solar irradiance are the path length through the Earth’s selectively absorbing atmosphere and its opacity which depends on the specific atmospheric condition. In addition site latitude determines the seasonal and daily variation in the path length and the opacity is due to the local climate and weather of the site (e.g. type and concentration of trace gases, aerosols, cloud type). Thus the importance of spectral effects varies depending on the considered location, atmospheric situation and time scale considered. We will present results of a systematic investigation of the role of spectral effects on the time-fluctuating photovoltaic energy generation.
 PV abbr. for Photovoltaic