Shaalke: Development of a MATLAB Software Tool for Advanced Statistical Outdoor Data Evaluation

This paper introduces Shaalke, a novel analytical software tool developed for the high-accuracy evaluation of long-term photovoltaic module measurement data. Addressing the critical need for robust parameter extraction from field data, Shaalke integrates advanced filtering, linear regression, and algorithmic processing to overcome limitations of traditional evaluation methods. We demonstrate Shaalke's capability to accurately determine STC parameters and both static and dynamic temperature coefficients, showing excellent agreement with manufacturer specifications and independent laboratory measurements. A key finding is Shaalke's precise mapping of the irradiance dependence of module efficiency, filling a significant gap left by typical datasheet values which often only provide data at 1000 and 200 W/m². Furthermore, the tool enables reliable power degradation analysis, identifying modules that exceed manufacturer-tolerated limits. Shaalke provides a comprehensive, data-driven platform for understanding real-world module performance, offering invaluable insights for system design, operation, and quality assurance, thereby bridging the gap between laboratory specifications and field performance.