A Scalable River Flow Forecast and Basin Optimization System for Hydropower Plants

Optimized operation of cascaded hydropower plants (HPPs) is critical, with important environmental and economic outcomes. These outcomes include reduced floods and waste of water, uninterrupted supply of water for drinking, irrigation and industrial use, and maximized energy generation. In this article, we present a large-scale and extensible system for river flow forecast and basin optimization. The system facilitates short-term and long-term river flow forecasts using meteorological and hydrological models, in addition to machine learning, ensemble, and hybrid learning methods. It produces optimization results for the cascaded HPPs using particle swarm optimization, based on the generated river flow forecasts and constraints of the basin. The optimization procedure can be short-term for flood prevention, and long-term for maximized energy generation. The forecast and optimization results produced, together with the automatically collected data from external systems are stored in a central database and are made accessible via a Web-based GUI application. The system is currently operational for a single basin in Turkey, but is extensible to cover other basins as well. The system is significant as it helps reduce floods and wasted water, and increases energy generation in the cascaded HPPs. Additionally, it stands as a large-scale system implementation for the domains of hydrology and hydropower.