Probabilistic Modelling, Advanced Exergy Analysis, and Cooling Water Optimization of a Combined Cycle Power Plant /

Abstract

The Water-Energy Nexus is becoming of great interest with the growing environmental concerns, especially in developing countries like Pakistan that are now under a state of water stress from once being water abundant. Pakistan relies heavily on thermal power generation, and with thermal power plants consuming high amounts of freshwater, their water usage optimization is of immense importance. For repowering with reduced cooling water usage, a clear understanding of the effects of the condenser parameters on a power plant is needed. This study investigates a furnace oil-fired combined cycle power plant for reduced cooling water usage from a repowering perspective. The case study power plant draws freshwater for recirculation-based cooling from a canal linked with the River Indus. The power plant has been modelled using 120 hours of real-time probabilistic data at baseload by generating three study cases stemming from 24-hour parametric variations. The commercial tool Cycle-Tempo has been deployed for modelling. The modelling considers physical uncertainties and errors from sensors, making it a challenging task. The models are validated and compared with the 21 years old design case data to highlight degradations in an exergy analysis. A tri-parametric optimization is done using Cycle-Tempo to reduce the cooling water usage while retaining baseload performance, generating performance maps that relate exergy, low-pressure section steam turbine performance, and condenser performance to highlight potential repowering opportunities. The effect of reduced water usage on the observed malfunctions in the system has also been observed. The optimized cases result in the power plant using 9.5-11% less water in terms of mass flow rate while still retaining baseload performance and key heat recovery steam generator operating points.