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Stochastic differential dynamic programming for multi-reservoir system control.

El-Awar, Faraj A., Labadie, John W. et Ouarda, Taha B. M. J. (1998). Stochastic differential dynamic programming for multi-reservoir system control. Stochastic Hydrology and Hydraulics , vol. 12 , nº 4. p. 247-266. DOI: 10.1007/s004770050020.

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Résumé

: As with all dynamic programming formulations, differential dynamic programming (DDP) successfully exploits the sequential decision structure of multi-reservoir optimization problems, overcomes difficulties with the nonconvexity of energy production functions for hydropower systems, and provides optimal feedback release policies. DDP is particularly well suited to optimizing large-scale multi-reservoir systems due to its relative insensitivity to state-space dimensionality. This advantage of DDP encourages expansion of the state vector to include additional multi-lag hydrologic information and/or future inflow forecasts in developing optimal reservoir release policies. Unfortunately, attempts at extending DDP to the stochastic case have not been entirely successful. A modified stochastic DDP algorithm is presented which overcomes difficulties in previous formulations. Application of the algorithm to a four-reservoir hydropower system demonstrates its capabilities as an efficient approach to solving stochastic multi-reservoir optimization problems. The algorithm is also applied to a single reservoir problem with inclusion of multi-lag hydrologic information in the state vector. Results provide evidence of significant benefits in direct inclusion of expanded hydrologic state information in optimal feedback release policies.

Type de document: Article
Mots-clés libres: stochastic control; dynamic programming; reservoir systems; hydrologic forecasting; hydropower; feedback control; autoregressive models
Centre: Centre Eau Terre Environnement
Date de dépôt: 03 févr. 2021 20:51
Dernière modification: 03 févr. 2021 20:51
URI: https://espace.inrs.ca/id/eprint/11152

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