Interior-point method for reservoir operation with stochastic inflows

A new method is proposed for long-term reservoir operation planning with st ochastic inflows. In particular, the problem is formulated as a two-stage s tochastic linear program with simple recourse. The stochastic inflows are a pproximated by multiple inflow scenarios, leading to a very large determini stic model which is hard to solve using conventional optimization methods. This paper presents an efficient interior-point optimization algorithm for solving the resulting deterministic problem. It is also shown how exploitin g the problem structure enhances the performance of the algorithm. Applicat ion to regulation of the Great Lakes system shows that the proposed approac h can handle the stochasticity of the inflows as well as the nonlinearity o f the operating conditions in a real-world reservoir system.