A successive linear programming algorithm with non-linear time series for the reservoir management problem

Charles Gauvin (charles.gauvinpolymtl.ca)
Erick Delage (erick.delagehec.ca)
Michel Gendreau (michel.gendreaucirrelt.net)

Abstract: This paper proposes a multi-stage stochastic programming formulation based on affine decision rules for the reservoir management problem. Our approach seeks to find a release schedule that balances flood control and power generation objectives while considering realistic operating conditions as well as variable water head. To deal with the non-convexity introduced by the variable water head, we implement a simple, yet effective, successive linear programming algorithm. We also introduce a novel non-linear inflow representation that captures serial correlation of arbitrary order. We test our method on a real river system and discuss policy implications. Our results namely show that our method can decrease flood risk compared to historical decisions, albeit at the cost of reduced final storages.

Keywords: Mathematical programming, Stochastic processes, Forecasting, Risk analysis

Category 1: Stochastic Programming

Category 2: Robust Optimization

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Entry Submitted: 03/01/2017
Entry Accepted: 03/01/2017
Entry Last Modified: 07/20/2017

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