TY - GEN A1 - van Ackooij, Wim A1 - Henrion, Rene A1 - Möller, Andris A1 - Zorgati, Riadh T1 - Joint Chance Constrained Programming for Hydro Reservoir Management N2 - In this paper, we deal with a hydraulic reservoir optimization problem with uncertainty on inflows in a joint chance constrained programming setting. In particular, we will consider inflows with a persistency effect, following a causal time series model, and examine the impact of the ”Gaussian” assumption for such inflows. We present an iterative algorithm for solving similarly structured joint chance constrained programming problems that requires a Slater point and the computation of gradients. Several alternatives to the joint chance constraint problem are presented. In particular, we present an individual chance constraint problem and a robust model. We illustrate the interest of joint chance constrained programming by comparing results obtained on a realistic hydro-valley with those obtained from the alternative models. Despite the fact that the alternative models often require less hypothesis on the law of the inflows, we show that they yield conservative and costly solutions. The simpler models, such as the individual chance constraint one, are shown to yield insufficient robustness and are therefore not useful. We therefore conclude that Joint Chance Constrained programming appears as a technique offering a good trade-off between cost and robustness and can be tractable for complex realistic models. KW - Chance-Constrained-Programming KW - Hydro-Reservoir-Management KW - Joint-Chance-Constraints KW - Stochastic-Inflows Y1 - 2012 UR - https://opus4.kobv.de/opus4-matheon/frontdoor/index/index/docId/992 UR - https://nbn-resolving.org/urn:nbn:de:0296-matheon-9929 ER -