THERMODYNAMIC & THERMOECNOMIC OPTIMIZATION ANALYSIS OF NOVEL DIRECT OXY-COMBUSTION SUPERCRITICAL CO2 POWER CYCLES INTEGRATED WITH DRY AND WET PRECOOLER USING GENETIC ALGORITHM

Abstract

As part of worldwide efforts to reduce the negative effects of global warming through the carbon neutrality plan by 2050 and implementation of the sustainability strategy set by Qatar National Vision 2030, three novel direct oxy combusted sCO2 power cycles are investigated. This thesis is intended to perform thermodynamic and thermoeconomic optimization analysis for the three cycles integrated with wet and dry precoolers. The first cycle (M1) is the basic sCO2 power cycle which consists of Gas turbine (GT), oxygen compressor (OC), fuel compressor (FC), gas compressor (GC), high-temperature recuperators (HTR), low-temperature recuperators (LTR), oxy-combustor, water separator (WS) and air separation unit (ASU). The second cycle (M2) and third cycle (M3) have similar components to M1 but with an additional preheater which is integrated in parallel with LTR for M2 and in parallel with LTR and HTR for M3. Each cycle configuration is studied in two conditions: a wet cooling condition where the exhaust fluid is cooled by wet pre-cooler (water) and a dry cooling condition where the working fluid is cooled by dry pre-cooler (Air) resulting in six different configurations. Using Engineering Equation Solver (EES) software, all of these configurations are thermodynamically modeled and optimized. Two optimization techniques: single and multi-objectives are performed in this study using a genetic algorithm (GA). These analyses are conducted to identify the most feasible configurations and compare their performance from the energy, exergy, and economic perspective in their optimal conditions. In wet-cooling condition, the single objective optimization results showed that M3 cycle configuration has a promising potential as it has the highest optimal thermal efficiency compared with M2 (by 7.6%) and M1 (by 8 %) and the lowest levelized cost of energy (LCOE) relatively with M2 (by 3.8%) and M1 (by 4.3%). However, M1 obtained the highest optimal exergy efficiency by prevailing in minor differences compared to other configurations. On the other hand, in dry-cooling conditions, M3 has the highest thermal efficiency, the highest exergy efficiency with a minimal difference, and the lowest levelized cost of energy (LCOE). The reason lies in preheater integration which improves the cycle's thermal efficiency and minimizes LCOE by enhancing the functionality of the combustor and reduce the fuel consumption. It also increases the exergy destruction which affects the exergy efficiency negatively. In multi-objectives optimization where both the thermal efficiency and the exergy efficiency are maximized and LCOE is minimized simultaneously using weighting factors, M3 is considered as an optimal cycle configuration in both wet and dry cooling conditions. Based on these outcomes, the decision-maker is given a framework to choose the best optimal configuration that meets their energy and economic goals considering cooling conditions. In addition, sensitivity analysis is performed on the weighted factors of the multi-objective optimization to study the influence of varying weights on the objective functions and obtain the desired optimal configuration based on the decision-maker preference.