Dataset for Solar-Powered Submersible Pump Systems
Description
Data were collected over a year to develop AI models. The system, operating in Marsa Matrouh, Egypt, gathered two data categories: weather and inverter motor data. Weather data includes: UV index (W/m²) Air temperature (°C) Wind speed (m/s) Wind direction (° from North) Humidity (%) Gust speed (m/s) Cloud cover (%) Solar energy generation is influenced by these factors. A higher UV index generally increases power output, though prolonged exposure degrades materials. Excessive heat reduces efficiency due to electrical resistance. Wind speed cools panels, mitigating heat-related losses, but strong gusts may stress structures. Wind direction affects cooling efficiency, humidity scatters sunlight and degrades components, and cloud cover reduces direct sunlight but may occasionally enhance scattered light collection. Optimal conditions include high UV levels, moderate temperatures, steady cooling winds, and minimal humidity or clouds. Weather data was collected daily via the Stormglass.io API at a fixed location. Inverter motor data includes: Frequency reference Output frequency Output current DC bus voltage Output power Frequency fault Heatsink temperature PID output PID input The inverter motor drive manages input and output parameters for efficiency and stability. The frequency reference controls motor speed, while the PID controller adjusts performance using sensor data. Output frequency affects motor speed, and output current indicates load. The DC bus voltage stabilizes power supply, while output power reflects energy delivered. Safety features include frequency fault warnings and heatsink temperature monitoring to prevent overheating. The PID output fine-tunes motor speed and torque for optimal efficiency. For more information about the dataset or the system please read and cite our publication: