Maximizing Hydropower Generation in Flood Control Operation using Preference Based Multi-objective Evolutionary Algorithm

Reservoir flood control operation (RFCO) is a challenging optimization problem with multiple objectives which are conflicting with each other. In this work, a tri-objective optimization model which maximizes hydropower generation during flood control is investigated and a multi-objective optimizer based on decomposition technique and the decision maker's preference information is developed. Experimental studies on typical floods at Ankang reservoir indicate the effectiveness of the proposed algorithm. It successfully provides preferred scheduling plans with more hydro- power generations than those considering the safety objectives only.