Neural Network-Based Active Cooling System With IoT Monitoring and Control for LCPV Silicon Solar Cells

• Main Authors: Dosymbetova G., Mekhilef S., Orynbassar S., Kapparova A., Saymbetov A., Nurgaliyev M., Zholamanov B., Kuttybay N., Manakov S., Svanbayev Y., Koshkarbay N.
• Other Authors: 57202334195
• Format: Article
• Published: Institute of Electrical and Electronics Engineers Inc. 2024
• Subjects: active cooling system; Bi-LSTM; IoT monitoring and control; LCPV silicon solar cells; neural networks; XGBoost; Computer control systems; Computing power; Cooling systems; Energy efficiency; Green computing; Internet of things; Maximum power point trackers; Photoelectrochemical cells; Pumps; Silicon solar cells; Solar energy; Solar panels; Solar power generation; Thermoelectric equipment; Active cooling; Active cooling system; Concentrating photovoltaic; Internet of thing monitoring and control; Low concentrating photovoltaic silicon solar cell; Monitoring and control; Neural-networks; Xgboost; Computer architecture

One of the methods of increasing output power of solar cells is increasing the concentration ratio using lenses and mirrors. Due to the temperature increase of silicon solar cells with concentrating lenses the system must be provided with an active cooling system. PV systems cooled with active or pa...