Volume 40: Energy Transitions toward Carbon Neutrality: Part III

Optimization and Analysis of an LNG Cold Energy Power Generation Model with Different Multi-energy Complementary Systems Chenchen Li, Xinli Lu, Wei Zhang, Hao Yu, Jiali Liu, Shuhui Li

https://doi.org/10.46855/energy-proceedings-10944

Abstract

In this paper, based on analyzing the existing LNG cold energy utilization power generation system and aiming at the existing problems, and also combined with using geothermal resources, seawater and seawater-source heat pump systems, a multi-energy complementary LNG cold energy power generation model is established. In the process of LNG gasification, the proposed system uses seawater as the high-temperature heat source, and LNG as the low-temperature heat source to generate electricity first, and then combines with green energy heating, such as using geothermal or seawater-source heat pump, to meet the heat load requirement in the LNG gasification process. Several kinds of organic working fluids were selected to maximize the net power output and the cycle thermal efficiency, so as to achieve the best operating effect. The system parameters are optimized and the influences of the parameters, such as the inlet and outlet pressures of the turbine, on the system performance have been analyzed. It is found that, using propane as the working fluid, the power generation system can generate 2.47MW electricity in winter and 4.25MW in summer. The optimal evaporation and condensing pressures are 7.3 bar and 0.85 bar respectively, corresponding to a power cycle thermal efficiency of 13.34%. The results show that the proposed system can meet the heat load required for LNG heating and achieve the goal of energy saving, as well as reducing the emission of C02, which is of great significance for promoting the realization of carbon neutrality Future investment needs to be carried out to further analyze the techno-economics of the proposed system.

Keywords LNG cold energy power cycle, Multi-energy systems, Thermal performance, Optimization

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