Convolutional Neural Network for Microhydro Power Forecasting

The demand for electrical energy is always fluctuating, influenced by several factors such as household, industrial, commercial, and other public service electricity usage. Moreover, estimates of future electricity demand play a crucial role in the operation of the power system, ranging from power generation planning to power flow analysis and energy system operation costs. Electrical power forecasting aims to prevent sudden decreases or increases in electricity demand. Moreover, in tropical countries, the wet season and rivers offer many opportunities for micro-hydro potentials that can be harnessed in combination with solar energy. To manage the forecasting modeling, Convolutional Neural Network (CNN) is utilized CNN for short-term forecasting in Microhydro Power Plants. The anticipated outcomes aim to contribute to effective electricity demand management, facilitating the estimates of variation in microhydro power generation.