Using Pyomo and IPOPT for Optimization of Reservoir Flood Control Operation

Abstract

Optimizing reservoir flood control operation is one of important non-structure measures for reducing flood damage. However, reservoir flood control operation is a typical, complex, and nonlinear optimization problem. It is very difficult to directly solve this problem. Linear programming and dynamic programming are usually used to solve it, which can bring big error or curse of dimensionality. IPOPT is a full space, interior point (or barrier) solver, which can solver large-scale nonlinear programming problems very efficiently. So in this paper we used IPOPT to solve reservoir flood control optimization problem. First, the optimization model of reservoir flood control operation was presented for minimizing the downstream flood peak, while the constraints were considered such as water balance, flood pool capacity, and outflow capacity et al. Second, an optimization modeling tool, Pyomo, was used to describe this flood control optimization model, which improved modeling efficiency. In the end, IPOPT was called to solve the model. The case study showed that the approach of solving reservoir flood control optimization problem based on Pyomo and IPOPT was operable and effective. The optimization result was also reasonable.