Data-driven control of water reservoirs using an emulator of the climate system. Issue 2 (2020)

• Record Type: Journal Article
• Authors: Giuliani, Matteo; Zaniolo, Marta; Block, Paul; Castelletti, Andrea
• Is Part Of: IFAC-PapersOnLine. Volume 53:Issue 2(2020)
• Page Start: 16531
• Page End: 16536
• Publication Date: 2020
• Subjects: Optimal control of water resources systems -- Data-driven control -- Model reduction -- Machine Learning -- Direct Policy Search -- Multi-objective optimal control; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2020.12.771
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This study presents a novel approach to combine a data-driven control strategy with an emulator model of the climate system in order to make the optimal control of water systems more flexible and adaptive to the increasing frequency and intensity of extreme events. These latter are often associated with global climate anomalies, which are difficult to model and incorporate into optimal control algorithms. In this paper, we compare a traditional control policy conditioned only on the reservoir storage with an informed controller that enlarges the state space to include the emulated dynamics of global Sea Surface Temperature anomalies. The multi-purpose operations of Lake Como in Italy, accounting for flood control and water supply, is used as a case study. Numerical results show that the proposed approach provides a 59% improvement in system performance with respect to traditional solutions. This gain further increases during extreme drought episodes, which are influenced by global climate oscillations.