A new approach for solution of large-scale multi-objective optimization operation modelling of cascade reservoirs: Long-term interaction between ecology and hydroelectricity

The solution for large-scale multi-objective optimization operation modelling of cascade reservoirs is always one of the difficult issues and hot topics for water resources operation and allocation. However, the multi-objective operation model has the characteristics of complex hydraulic connection, high-dimensionality, and multi-constraint, and how to efficiently and accurately solve and model is always a challenge in decision-making and management of water resources. To avoid the phenomenon and limitations of the conventional studies on the solution of the operation model used to excessively depend on intelligent optimal algorithm without taking the complex hydraulic connections of variables into consideration, in this paper, a new approach of a synergistic optimization strategy combining a decomposition optimization framework (DOF) with an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) was proposed. The new method completely avoided the curse of dimensionality by variable division, boundary condition transmission, and hydraulic connection reconstruction, and significantly improved the computational efficiency and accuracy of the global optimization (GO). The Lancang River (LCR) cascade reservoirs were selected as a case study, and the multi-objective model was constructed to apply the new approach. The results show that compared with the GO, the GO by the DOF (GO-DOF) reduces the computational time by 86.9 %, significantly decreases the degree of ecological change (DEC) by 42.6 % with power generation decreasing by only 0.6 %. It is concluded that the DOF shows excellent performance in both computational efficiency and operation outcomes, providing a new approach to an efficient solution for the operation and allocation optimization of complex water resources systems.