Springer

Optimization of a multiple reservoir system operation using a combination of genetic algorithm and discrete differential dynamic programming: a case study in Mae Klong system, Thailand

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A combination of genetic algorithm and discrete differential dynamic programming approach (called GA-DDDP) is proposed and developed to optimize the operation of the multiple reservoir system. The demonstration is carried out through application to the Mae Klong system in Thailand. The objective of optimization is to obtain the optimal operating policies by minimizing the total irrigation deficits during a critical drought year. The performance of the proposed algorithm is compared with the modified genetic algorithm. The results show that the proposed GA-DDDP provides optimal solutions, converging into the same fitness values within a short time. The GA is able to produce satisfactory results that are very close to those obtained from GA-DDDP but required alot more computation time to obtain the precise results. The difficulties in selecting optimal parameters of GA as well as finding a feasible initial trial trajectory of DDDP are significant problems and time-consuming. The significant advantage obtained from GA-DDDP is saving of computational resource as GA-DDDP requires no need for optimizing parameters and deriving feasible initial trial trajectories. Because DDDP is a part of GA-DDDP, the good performance of GA-DDDP is obtained when applied to a small system where numbers of discretizations and variables have no influence to the dimensionality problem of DDDP

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