Increasing the Productivity of an Electricity System Based on Energy Generated by Hydropower with the Help of Artificial Intelligence

This research study deals with optimizing the production of renewable hydropower. For capacity planning and optimization, a randomly constrained programming model is developed that can take into account the sporadic character of renewable energy sources. In order to reduce the overall expenses of energy generation and storage, an analysis of the hydroelectric power station's potential capacity is conducted. The provided model is based on an algorithm for capacity enhancement and ideal system design. The short-term forecasting of data using both time series and particular hours of the day is a novel idea in this field.