A comparative and predictive analysis of solar power output from different tilt angles of Internet-Of-Thing (IoT) based solar panels for irrigation system

The cost of solar panel installation has been decreased since a decade ago, yet it is considered as an expensive investment considering its less inefficiency in energy capture of fixed solar panels. Besides, the solar power output is highly depending on the climate. Due to this matter, the accurate forecasting of solar energy generation is very important, especially for east coast states of Malaysia that face northeast monsoon every year. Thus, in this study, few solar panels (0° horizontal flat-, 45° tilted- and auto-track-) were installed for a mini farm which equipped with Internet-of-Thing (IoT) system for data collection and the solar energy outputs were compared. From the results, the highest energy generated mostly from 12.00 until 2.00 pm with approximately 61% efficiency. The total solar power can reach up to 309W (45.6%) at ±30.9 ⁰C which enough to power on 12V 75W water pump. PV solar panel at 45° tilted generated higher average power (104.1W, 37.9%) compared to 0° horizontal flat ones (93.8W, 34.4%) with 3.5% difference and auto-tracker (125.6W, 45.9%) with 8% increment. Then, ARIMA (11, 2, 4) model was applied to forecast the data. Around 32% of Mean Absolute Percentage Error (MAPE) implies that the validity model about 68%. In conclusion, auto-track solar panel equipped with IoT system highlighted better solar capture compared to 0° horizontal flat and 45° tilted solar panels. The integrated technologies of solar-powered water pump with IoT system significantly cost-effective and easy for data collection. The forecasting of data analysis also bring potential for better farm management to ensure the availability and back-up of electricity supply, besides to avoid over and underutilization of electricity.