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Article

Reservoir Advanced Process Control for Hydroelectric Power Production

1
Dipartimento di Ingegneria dell’Informazione, Università Politecnica delle Marche, Via Brecce Bianche 12, 60131 Ancona, Italy
2
Alperia Green Future, 60015 Falconara Marittima, Italy
*
Author to whom correspondence should be addressed.
Processes 2023, 11(2), 300; https://doi.org/10.3390/pr11020300
Submission received: 29 November 2022 / Revised: 5 January 2023 / Accepted: 12 January 2023 / Published: 17 January 2023
(This article belongs to the Special Issue Automation Control Systems & Process Control for Industry 4.0)

Abstract

The present work is in the framework of water resource control and optimization. Specifically, an advanced process control system was designed and implemented in a hydroelectric power plant for water management. Two reservoirs (connected through a regulation gate) and a set of turbines for energy production constitute the main elements of the process. In-depth data analysis was carried out to determine the control variables and the major issues related to the previous conduction of the plant. A tailored modelization process was conducted, and satisfactory fitting performances were obtained with linear models. In particular, first-principles equations were combined with data-based techniques. The achievement of a reliable model of the plant and the availability of reliable forecasts of the measured disturbance variables—e.g., the hydroelectric power production plan—motivated the choice of a control approach based on model predictive control techniques. A tailored methodology was proposed to account for model uncertainties, and an ad hoc model mismatch compensation strategy was designed. Virtual environment simulations based on meaningful scenarios confirmed the validity of the proposed approach for reducing water waste while meeting the water demand for electric energy production. The control system was commissioned for the real plant, obtaining significant performance and a remarkable service factor.
Keywords: model predictive control; reservoir; hydroelectric power plant; modelization; forecast; advanced process control; regulation gate manipulation; water resources management; process control; process optimization model predictive control; reservoir; hydroelectric power plant; modelization; forecast; advanced process control; regulation gate manipulation; water resources management; process control; process optimization

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MDPI and ACS Style

Zanoli, S.M.; Pepe, C.; Astolfi, G.; Luzi, F. Reservoir Advanced Process Control for Hydroelectric Power Production. Processes 2023, 11, 300. https://doi.org/10.3390/pr11020300

AMA Style

Zanoli SM, Pepe C, Astolfi G, Luzi F. Reservoir Advanced Process Control for Hydroelectric Power Production. Processes. 2023; 11(2):300. https://doi.org/10.3390/pr11020300

Chicago/Turabian Style

Zanoli, Silvia Maria, Crescenzo Pepe, Giacomo Astolfi, and Francesco Luzi. 2023. "Reservoir Advanced Process Control for Hydroelectric Power Production" Processes 11, no. 2: 300. https://doi.org/10.3390/pr11020300

APA Style

Zanoli, S. M., Pepe, C., Astolfi, G., & Luzi, F. (2023). Reservoir Advanced Process Control for Hydroelectric Power Production. Processes, 11(2), 300. https://doi.org/10.3390/pr11020300

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