energies Article A Method of Multi-Stage Reservoir Water Level Forecasting Systems: A Case Study of Techi Hydropower in Taiwan Hao-Han Tsao 1 , Yih-Guang Leu 1,*, Li-Fen Chou 2 and Chao-Yang Tsao 2 1 Department of Electrical Engineering, National Taiwan Normal University, Taipei 106, Taiwan;
[email protected] 2 Taiwan Power Company, Taipei 100, Taiwan;
[email protected] (L.-F.C.);
[email protected] (C.-Y.T.) * Correspondence:
[email protected] Abstract: Reservoirs in Taiwan often provide hydroelectric power, irrigation water, municipal water, and flood control for the whole year. Taiwan has the climatic characteristics of concentrated rainy seasons, instantaneous heavy rains due to typhoons and rainy seasons. In addition, steep rivers in mountainous areas flow fast and furiously. Under such circumstances, reservoirs have to face sudden heavy rainfall and surges in water levels within a short period of time, which often causes the water level to continue to rise to the full level even though hydroelectric units are operating at full capacity, and as reservoirs can only drain the flood water, this results in the waste of hydropower resources. In recent years, the impact of climate change has caused extreme weather events to occur more frequently, increasing the need for flood control, and the reservoir operation has faced severe challenges in order to fulfil its multipurpose requirements. Therefore, in order to avoid the waste of hydropower resources and improve the effectiveness of the reservoir operation, this paper proposes a real-time 48-h ahead water level forecasting system, based on fuzzy neural networks with multi-stage Citation: Tsao, H.-H.; Leu, Y.-G.; Chou, L.-F.; Tsao, C.-Y.