Modeling and thermodynamic analysis of gas-supercritical carbon dioxide combined cycle system.

Autor: Zhou, Jiayin, Huang, Diangui, Qi, Yinke
Předmět:
Zdroj: Energy Sources Part A: Recovery, Utilization & Environmental Effects; 2022, Vol. 44 Issue 4, p9043-9063, 21p
Abstrakt: Gas turbine power generation has the advantages of flexibility, efficiency, and lower carbon emissions compared with coal-fired power generation. Under the situation of energy structure transformation and upgrading, gas turbine power generation will have bright prospects. In this paper, the modeling and thermodynamic analysis of various gas-supercritical carbon dioxide(sCO2) combined cycle systems are carried out based on the calculation method of total physical properties, and six typical combined cycle layouts are selected for detailed research. In order to obtain the optimal state of the combined cycle system, the parameters of the sCO2 bottom cycle are optimized within a certain range of the gas turbine pressure ratio. It is found that the combined cycle system has high thermal efficiency when the top cycle adopts the air preheating cycle, and a higher top cycle regenerative degree does not represent a better performance. In fact, the optimal regenerative degree is related to the bottom cycle performance. The study also found that the air preheating-dual heated cascade combined cycle system has the highest thermal efficiency of the layouts studied, reaching 65.3%, but it comes at the cost of a complex operating system. The heat recovery performance of the sCO2 partial heating bottom cycle is relatively poor, and its mass flow rate is the highest, so it is not suitable for the bottom cycle of the combined cycle. The sCO2 dual heated cascade cycle has the highest output work and the smallest CO2 flow, so this paper considers this bottom cycle as the most suitable bottom cycle for the combined cycle system. This research can provide a certain basis for the design of gas turbine combined cycle system. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index