SOLVING OPTIMAL RESERVOIR OPERATION PROBLEMS FOR WATER INFRASTRUCTURE USING GENETIC ALGORITHM AND KEPLER OPTIMIZATION ALGORITHM

Abstract

Rule curves of reservoirs are necessary guides to operate reservoir in long term operation. This paper proposed an alternative approach of Genetic Algorithm (GA) and Kepler Optimization Algorithm (KOA) to connect with the simulation model for searching optimal reservoir rule curves as the flood control area. The proposed models were applied to determine the optimal flood rule curves of the Nam Oon Reservoir in the Northeast region of Thailand. Minimum average excess water and minimum frequency excess water were used as the objective functions for the searching procedure. The historic inflow, synthetic inflow data of 1,000 events and future inflow were used to evaluate efficiency of the flood control rule curves in showing situations of water shortage and excess water in term of frequency, magnitude and duration. The results showed that obtained rule curves were used to simulate the Nam Oon Reservoir system for reducing flood in long term operation. The results indicated that situations of excess water using the obtained rule curves from the proposed model were smaller than using the current rule curves both for the present and future situations. The new obtained rule curves from the proposed GA and KOA models were better than the existing rule curves in decreasing flood situation.