Reservoir optimization with differential evolution

Abstract

Reservoir optimization, is one of recent problems, which has been researched by several methods such as Linear Programming (LP), Non-linear Programming (NLP), Genetic Algorithm (GA), and Dynamic Programming (DP). Differential Evolution (DE), a method in GA group, is recently applied in many fields, especially water management. This method is an improved variant of GA to converge and reach to the optimal solution faster than the traditional GA. It is also capable to apply for a wide range space, to a problem with complex, discontinuous, undifferential optimal function. Furthermore, this method does not requirethe gradient information of the space but easily find the global solution by asimple algorithm. In this paper, we introduce DE, compare to LP which was considered mathematically decades ago to prove DE's accuracy, then apply DE to Pleikrong, a reservoir in Vietnam, then discuss about the results.

Reservoirs optimization with dynamic programming

“…h i -water height at time period i, Q i -release at time period i, k -overall generation efficiency. The problem is created as in [1] which means calculation time is in dry season of Sesan cascade. It starts at the beginning of December and ends in the next June.…”

“…The results by DP of Pleikrong and Ialy reservoirs are shown as the charts and Tables below. These results are compared to the results by Differential Evolution which is a method in Genetic group that we presented in our previous work [1].…”