Enhancements to explicit stochastic reservoir operation optimization method

The Fletcher-Ponnambalam (FP) method is an explicit stochastic optimization method for design and operations management of real-world storage systems including surface water reservoir and groundwater management problems. The FP method faces no curse of dimensionality and no need for scenario generation. The paper introduces a novel implementation for the FP method, named FP-2022 here for clarity, by removing the need for nonlinear constraints and by decreasing the number of decision variables to just one third of its original value, significantly reducing solving time (similar to 27 times faster than the original formulation). Additionally, new expressions derived for the first and second moments of both reservoir release deficit and surplus variables and the already-derived expression for the second moments of reservoir storages are incorporated into the FP-2022 formulation enabling the method to reach an improved optimality for a nonlinear objective function. The enhanced procedure is applied to solving a reservoir operation optimization problem for a major dam in Brazil. The result comparisons made with other methods along with a thorough analysis of release operation policies prove the optimality of this highly numerically efficient and convenient-to-use FP-2022 method. Finally, a multi-reservoir application of the model is also tested with corrective simulations for improved estimates of some additional variables of interest. A specific constraint-handling approach regarding reservoir release lower and upper bounds is also presented. Satisfactory results are obtained for solving the Parambikulam-Aliyar reservoir system, a real world five-reservoir operation optimization problem from India.

Automated summary

The paper introduces a new implementation method named FP-2022, which significantly reduces solving time by simplifying constraints and decreasing decision variables. It incorporates new expressions to improve optimality for a nonlinear objective function. The method is proven to be highly efficient and optimal through the optimization problem of a dam in Brazil and a five-reservoir system in India.