Reference
A. Castelletti, A. Ficchì, A. Cominola, P. Segovia, M. Giuliani, W. Wu,
S. Lucia, C. Ocampo-Martinez, B. De Schutter, and
J. M. Maestre, "Model predictive control of
water resources systems: A review and research agenda,"
Annual
Reviews in Control, vol. 55, pp. 442-465, 2023.
Abstract
Model Predictive Control (MPC) has recently gained increasing interest in the
adaptive management of water resources systems due to its capability of
incorporating disturbance forecasts into real-time optimal control problems.
Yet, related literature is scattered with heterogeneous applications,
case-specific problem settings, and results that are hardly generalized and
transferable across systems. Here, we systematically review 149 peer-reviewed
journal articles published over the last 20 years on MPC applied to water
reservoirs, open channels, and urban water networks to identify common trends
and open challenges in research and practice. The three water systems we
consider are inter-connected, multi-purpose and multi-scale dynamical systems
affected by multiple hydro-climatic uncertainties and evolving socioeconomic
factors. Our review first identifies four main challenges currently limiting
most MPC applications in the water domain: (i) lack of systematic benchmarking
of MPC with respect to other control methods; (ii) lack of assessment of the
impact of uncertainties on the model-based control; (iii) limited analysis of
the impact of diverse forecast types, resolutions, and prediction horizons;
(iv) under-consideration of the multi-objective nature of most water resources
systems. We then argue that future MPC applications in water resources systems
should focus on addressing these four challenges as key priorities for future
developments.
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BibTeX
@article{CasFic:23-013,
author = {Castelletti, Andrea and Ficch\`{\i}, Andrea and Cominola, Andrea
and Segovia, Pablo and Giuliani, Matteo and Wu, Wenyan and Lucia,
Sergio and Ocampo-Martinez, Carlos and De Schutter, Bart and
Maestre, Jos{\'{e}} Mar{\'{\i}}a},
title = {Model Predictive Control of Water Resources Systems: {A} Review
and Research Agenda},
journal = {Annual Reviews in Control},
volume = {55},
pages = {442--465},
year = {2023}
}