SOFTHARD TOOL FOR SOLAR PANELS PERFORMANCE ESTIMATION FOR EFFECTIVE FUNCTION IN MICROGRID - АСТІСТОВА, Т. І.; КРАВЧЕНКО, М. С.; ПОСТОРОНКА, В. М.; КРАВЧЕНКО, О. П. (Technologies and Engineering, 2025)
Purpose. Design of a soft-hardware tool that is able to store and process data received from a local meteoservice device and from a global weather data network in order to estimate the solar panel performance, predict electricity generation profiles, and train appropriate expert systems, machine learning tools, or neural networks aimed at achieving maximum efficiency of the electrical system. Methodology. Using renewable energy sources in MicroGrid, particularly solar panels (SPs), is characterized by the stochastic nature of power generation due to the dependence of power generation capacity in MicroGrid with distributed SPs on the weather condition. A decisive role in assessing the efficiency of the SP operation is played by both the technical characteristics of the SP, which is provided by the manufacturer, and the performance of the SP, which is calculated on the basis of data obtained over a long period of time, during the operation of the SP installed in the selected area with appropriate weather condition. Findings. A hardware and software tool has been developed that get ability in collecting, storing and processing data to calculate the performance of the SP. Input data is obtained both from a local meteoservice point and from a global meteodata using an API (Application Programming Interface), while data storing and processing is implemented with the server. Originality. All data both stored and processed is used to make prognostics in forming power generation profile as concerned to the MicroGrid. Moreover, the data can be applied in training whether an expert system, or in machine and neural networks learning to maximize the efficiency of the electrical system. Practical value. Evaluating the solar panel’s performance factor allows to determine how efficiently the solar panel converts solar energy into electrical energy: the higher the performance factor, the more energy can be obtained from such a solar panel, which helps to establish realistic expected electricity costs and optimize the solar panel system for maximum electricity production. In addition, the performance factor assessment allows during real-time monitoring of the solar panel’s performance to identify possible issues related to contamination or damage to the panels.