ZHANG Jinkun, WANG Du, REN Xin, et al. Economic study on key parameters of gas turbine/supercritical carbon dioxide cycle based on LNG cold energy utilization[J]. Thermal power generation, 2023, 52(6): 109-118.
ZHANG Jinkun, WANG Du, REN Xin, et al. Economic study on key parameters of gas turbine/supercritical carbon dioxide cycle based on LNG cold energy utilization[J]. Thermal power generation, 2023, 52(6): 109-118. DOI: 10.19666/j.rlfd.202212298.
The supercritical carbon dioxide cycle has many advantages
such as high cycle efficiency
small equipment size
convenient transportation and installation
and easy to reach the critical point. Considering the huge cold energy of LNG
it can not only be used as coolant in the combined cycle system
but also the natural gas after heat transfer can be used as fuel input in the combined cycle
and the rest can be supplied to urban users. A gas turbine/supercritical carbon dioxide combined cycle system based on the utilization of LNG cold energy is proposed in this paper. Select the appropriate cost formula to calculate and analyze the investment cost
operating income and recovery cycle of the circulating power generation system in detail. The influence of some key parameters(such as maximum temperature
maximum pressure
minimum temperature
minimum pressure and shunt ratio) on the power generation characteristics and economy of the supercritical carbon dioxide cycle in the combined cycle system was studied. The results show that with the increase of each single parameter
the cost of equipment investment will first increase and then decrease
but the effect of power generation on income is dominant. Taking the yield as the measurement standard
the higher the maximum temperature
the better
the lower the minimum temperature
the better. Under other parameters
there are optimal values to maximize the yield.The key parameters were optimized by genetic algorithm to maximize the cumulative income. After optimization
the recovery cycle was 5.86 years
and the cumulative income(20 years) was 2.287 billion yuan.