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- Modeling and Optimization of Power Plant Cooling Tower Systems Using Physics-Based and Neural-Network-Based Models
- Salomon, Basile Clément Paul
Condensers and cooling towers are commonly used in steam power plants to condense the steam exiting the turbine and to recycle the condensed...
Show moreCondensers and cooling towers are commonly used in steam power plants to condense the steam exiting the turbine and to recycle the condensed-water into the boiler in a closed-loop system. These condensers typically use cooling water drawn from a water body (lake, river etc) to condense the steam. Cooling towers are used to lower the temperature of the warm water exiting the condenser. Since the steam condensation temperature plays an important role in the power plant efficiency, cool- ing tower performance which is limited by the wet-bulb temperature of the ambient air has been extensively studied. This work investigates the modeling of an enhanced cooling tower technology using a new pre-cooling and dehumidifying system (PDHS). This new system, based on a reversed Brayton cycle, is made out of a compressor, an air-cooled heat exchanger (HX), a heat and mass exchanger (HMX) and an expander. The goal of this PDHS concept is to pre-cool the air entering the cooling tower in order to improve its performance. In this work, a systems model has been developed. Thermodynamic models have been used for the compressor, the air-cooled heat exchanger and the expander. For the remaining components, i.e. the heat and mass exchanger, the cooling tower and the condenser, physics-based models have been developed and tested. Once tested and validated, each model can be integrated into the integrated PDHS-cooling tower-condenser system. Two different configurations of the PDHS have been considered in this thesis. In the open water loop configuration, the water in the HMX is obtained from the municipal water supply (or an alternate water source) and is released back to the source after exiting the HMX. In the closed water loop configuration, the water used to cool down the air in the HMX is being recirculated and cooled in the power plant cooling tower. The physics-based model of the PDHS developed in this work has been validated using results from an empirical model of the PDHS by GTI Energy. This first case study also shows how the PDHS can be used to save water in the cooling tower (CT). Indeed, when using the PDHS, a 37% reduction in the cooling tower evaporation rate can be observed when comparing to the baseline. This decrease in the CT evaporation rate is the main source of make-up water savings. Moreover, the water harvested by condensation in the PDHS can be redirected towards the CT, bringing another source of water savings. These two combined lead to an overall 46% decrease of the make-up water usage in the cooling tower. Another case study has been conducted on a 500 MW condenser unit. It shows that, under summer ambient conditions i.e. Ta,db = 35°C and φ = 47%, the PDHS can help the condenser restore its designed cooling load of 453 MW. Finally, using the physics-based model to create a dataset, an artificial neural network model of the PDHS has been developed to constitute a black box for the PDHS that would be able to predict with sufficient accuracy the condenser and HMX loads, the air conditions at the inlet of the CT and water temperature at both ends of the condenser and CT given the ambient air condition, the compressor pressure ratio and the water split between the condenser and the heat and mass exchanger.