The purpose of the thesis is the development of an online tool for displaying long term data of photovoltaic modules. Using regular parameter checks we can quickly remedy potential defects and ensure optimal energy production of the solar power plant. Long term data is even more important for research solar power plants, because the data can provide useful information for the next generations of solar panels.
We began the development of the web tool by producing the Python library to acquire data from a SQL base and calculating data we cannot measure. With the help of the library we made a web interface for graphical and tabular representation of measured and calculated values. For the development of the web interface we used Django, a high-level Python web framework, HTML, JavaScript and CSS. The tool can graphically display data for all modules with the option to select the data type. It can also display multiple types of data for one or two modules, with the option to select the module, data type and to filter the data. The tool can in addition to graphs also display values for combined irradiation, generated energy, yield, performance ratio and temperature corrected performance ratio for the selected time frame in a tabular format.
We presented the usefulness of the tool with the comparison of three different types of solar modules. We compared a multicrystalline module, an amorphious silicon module and a heterojunction (HIT) module. Comparison includes differences in temperature behaviour, yield and performance ratio.
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