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

Charles Gauvin (), Erick Delage () and Michel Gendreau ()
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Charles Gauvin: Polytechnique Montréal
Erick Delage: HEC Montréal
Michel Gendreau: Polytechnique Montréal

Computational Management Science, 2018, vol. 15, issue 1, No 3, 55-86

Abstract: 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 small real river system and discuss policy implications. Our results namely show that our method can decrease flood risk and increase production compared to the historical decisions, albeit at the cost of reduced final storages.

Keywords: Mathematical programming; Stochastic processes; Forecasting; Risk analysis (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10287-017-0295-4

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