Thermal Performance Evaluation of an Induced Draft Evaporative Cooling System through Adaptive Neuro-Fuzzy Interference System (ANFIS) Model and Mathematical Model

Jens Baetens, Greet Van Eetvelde, Gert Lemmens, Nezmin Kayedpour, Jeroen D. M. De Kooning and Lieven Vandevelde
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Jens Baetens: Electrical Energy Laboratory (EELAB), Department of Electrical Energy, Metals, Mechanical Constructions & Systems (EEMMeCS), Ghent University, Tech Lane Ghent Science Park—Campus A, Technologiepark-Zwijnaarde 131, 9052 Ghent, Belgium
Greet Van Eetvelde: Electrical Energy Laboratory (EELAB), Department of Electrical Energy, Metals, Mechanical Constructions & Systems (EEMMeCS), Ghent University, Tech Lane Ghent Science Park—Campus A, Technologiepark-Zwijnaarde 131, 9052 Ghent, Belgium
Gert Lemmens: INEOS Group, 1180 Rolle, Switzerland
Nezmin Kayedpour: Electrical Energy Laboratory (EELAB), Department of Electrical Energy, Metals, Mechanical Constructions & Systems (EEMMeCS), Ghent University, Tech Lane Ghent Science Park—Campus A, Technologiepark-Zwijnaarde 131, 9052 Ghent, Belgium
Jeroen D. M. De Kooning: Electrical Energy Laboratory (EELAB), Department of Electrical Energy, Metals, Mechanical Constructions & Systems (EEMMeCS), Ghent University, Tech Lane Ghent Science Park—Campus A, Technologiepark-Zwijnaarde 131, 9052 Ghent, Belgium
Lieven Vandevelde: Electrical Energy Laboratory (EELAB), Department of Electrical Energy, Metals, Mechanical Constructions & Systems (EEMMeCS), Ghent University, Tech Lane Ghent Science Park—Campus A, Technologiepark-Zwijnaarde 131, 9052 Ghent, Belgium

Energies, 2019, vol. 12, issue 13, 1-17

Abstract: The shift from fossil fuel to more renewable electricity generation will require the broader implementation of Demand Side Response (DSR) into the grid. Utility processes in industry are suited for this, having a large thermal time constant or buffer, and large electricity consumption. A widespread utility system in industry is an induced draft evaporative cooling tower. Considering the safety aspect, such a process needs to maintain cooling water temperature within predefined safe boundaries. Therefore, in this paper, two modelling methods for the prediction of the basin temperature of an induced draft evaporative cooling tower are proposed. Both a white box and a black box methodology are presented, based on the physical principles of fluid dynamics and adaptive neuro-fuzzy interference system (ANFIS) modelling, respectively. By analysing the accuracy of both models with a focus to cooling tower fan state changes, i.e., DSR purposes, it is shown that the white box model performs best. Fostering the idea of using such a system for DSR purposes, the concept of design for flexibility is also touched upon, discussing the thermal mass. Pre-cooling, where the temperature of the cooling water basin is lowered before a fan switch off period, was simulated with the white box model. It was shown that beneficial pre-cooling (to lower the temperature peak) is limited in time.

Keywords: dynamic modelling; Adaptive Neuro-Fuzzy Inference System (ANFIS); evaporative cooling; electrical flexibility; industry (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: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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