A hybrid nonlinear optimization method for operation of large-scale cascaded hydropower plants

Abstract

This paper develops a hybrid nonlinear optimization method for solving long-term optimal operation of large-scale cascaded hydropower plants with complex spatial coupling constraints. This method proposes conversion factors relevant to generation and discharge in order to cope with complex nonlinear total generation limitation considered in the optimization problem. Thus, the original nonlinear optimization problem can be broken down into a sequence of standard quadratic programming sub-problems. A combination of progressive optimality algorithm (POA) and quadratic programming (QP) method is employed to optimize the operation of hydropower systems. The results obtained from POA are first chosen as the initial solution of QP, which also decide the feasible decision space. During the solution process, the previous conversion factors are dynamically updated depending on the destroying range of total generation limitation. The boundary values of these constraints are accordingly modified in the new QP model. Solving the QP problem and updating the convention factors are performed alternately until the optimal solution or satisfactory solution for original problem is obtained. The proposed hybrid nonlinear method is applied to scheduling Hongshui River cascaded hydropower plants. The simulation results show that our method can enhance the total power generation in dry season and produce more energy than POA.