Innovative Applications of O.R.Stochastic short-term hydropower planning with inflow scenario trees

•A scenario tree generation method is proposed.•A stochastic short-term unit commitment and loading problem is modeled.•Scenario tree method produces more energy than median scenario.•Computational time to generate trees and optimize is very fast.

This paper presents an optimization approach to solve the short-term hydropower unit commitment and loading problem with uncertain inflows. A scenario tree is built based on a forecasted fan of inflows, which is developed using the weather forecast and the historical weather realizations. The tree-building approach seeks to minimize the nested distance between the stochastic process of historical inflow data and the multistage stochastic process represented in the scenario tree. A two-phase multistage stochastic model is used to solve the problem. The proposed approach is tested on a 31 day rolling-horizon with daily forecasted inflows for three power plants situated in the province of Quebec, Canada, that belong to the company Rio Tinto.