HT-TPP: A Hybrid Twin Architecture for Thermal Power Plant Collaborative Condition Monitoring

Mezzour Ghita, Benhadou Siham, Medromi Hicham and Mounaam Amine
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Mezzour Ghita: National and High School of Electricity and Mechanic (ENSEM), HASSAN II University, Casablanca 8118, Morocco
Benhadou Siham: National and High School of Electricity and Mechanic (ENSEM), HASSAN II University, Casablanca 8118, Morocco
Medromi Hicham: National and High School of Electricity and Mechanic (ENSEM), HASSAN II University, Casablanca 8118, Morocco
Mounaam Amine: Innovation Lab for Operations (ILO), Mohammed VI Polytechnic University (UM6P), Benguerir 43150, Morocco

Energies, 2022, vol. 15, issue 15, 1-38

Abstract: Thermal power plants, TPP, are one of the main players in the phosphoric acid and fertilizer production value chain. The control of power plant assets involves considerable complexity and is subject to several constraints, affecting the asset’s reliability and, most importantly, plant operators’ safety. The main focus of this paper is to investigate the potential of an agent-based digital twin architecture for collaborative prognostic of power plants. Based on the ISO 13374:2015 scheme for smart condition monitoring, the proposed architecture consists of a collaborative prognostics system governed by several smart DT agents connected to both physical and virtual environments. In order to apprehend the potential of the developed agent-based architecture, experiments on the architecture are conducted in a real industrial environment. We show throughout the paper that our proposed architecture is robust and reproduces TPP static and dynamic behavior and can contribute to the smart monitoring of the plant in case of critical conditions.

Keywords: digital twin; agent-based engineering; collaborative prognostics (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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