Adaptive stochastic management of the storage function for a large, open reservoir using learned fuzzy models

Title:

Adaptive stochastic management of the storage function for a large, open reservoir using learned fuzzy models

Creator:

Kozel, Tomas and Stary, Milos

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:f429babf-f361-4c8b-b3f3-d229b09b9087
uuid:f429babf-f361-4c8b-b3f3-d229b09b9087
doi:10.2478/johh-2022-0010

Subject:

stochastic, artificial intelligence, storage function, and optimisation

Type:

model:article and TEXT

Format:

počítač and online zdroj

Description:

The design and evaluation of algorithms for adaptive stochastic control of the reservoir function of a water reservoir using an artificial intelligence method (learned fuzzy model) are described in this article. This procedure was tested on the Vranov reservoir (Czech Republic). Stochastic model results were compared with the results of deterministic management obtained using the method of classical optimisation (differential evolution). The models used for controlling of reservoir outflow used single quantile from flow duration curve values or combinations of quantile values from flow duration curve for determination of controlled outflow. Both methods were also tested on forecast data from real series (100% forecast). Finally, the results of the dispatcher graph, adaptive deterministic control and adaptive stochastic control were compared. Achieved results of adaptive stochastic management were better than results provided by dispatcher graph and provide inspiration for continuing research in the field.

Language:

Slovak

Rights:

http://creativecommons.org/licenses/by-nc-sa/4.0/
policy:public

Coverage:

213-221

Source:

Journal of hydrology and hydromechanics | 2022 Volume:70 | Number:2

Harvested from:

CDK

Metadata only:

false