
Online First:10 October 2026,
Published:2026
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潘杰, 于竞雯, 李咏格, et al. 太阳能与LNG冷能驱动的冷-电-轻烃多联产系统设计与分析[J]. 2026, 47(9): 608-619.
潘杰, 于竞雯, 李咏格, et al. 太阳能与LNG冷能驱动的冷-电-轻烃多联产系统设计与分析[J]. 2026, 47(9): 608-619. DOI: 10.19912/j.0254-0096.tynxb.2025-0797.
结合液化天然气(LNG)稳定、连续、低冷值和太阳能清洁、环保、可再生的互补优势
构建一种集成超临界CO2再压缩布雷顿循环(SCRBC)、双级有机朗肯循环(ORC)、轻烃分离(LHS)及数据中心冷却(DCC)的多联产系统
通过双罐储热(TES)平抑太阳能波动
耦合LNG冷能梯级回收技术实现冷-电-轻烃多能联供。采用NSGA-Ⅱ与MOPSO算法
以热效率、㶲效率及净现值为目标进行多目标优化
结合优劣解距离法(TOPSIS)决策确定帕累托最优解。结果表明:系统冷能利用率达69.73%
脱重烃塔㶲损占比为57.03%;净现值(NPV)对年利率的敏感性显著高于电价。相较于传统系统
该方案在热力学性能与经济性方面更具优势。
This study combines the complementary advantages of LNG’s stability
continuity
low cooling value
and solar energy’s cleanliness
environmental friendliness
and renewability to construct polygeneration system integrating supercritical CO re-compression Brayton cycle (SCRBC)
a two-stage organic Rankine cycle (ORC)
light hydrocarbon separation (LHS)
and data center cooling (DCC). The system utilizes dual-tank thermal energy storage (TES) to mitigate solar energy fluctuations and couples LNG cold energy cascade recovery technology to achieve combined cooling
power
and light hydrocarbon production. Multi-objective optimization is performed using NSGA-Ⅱ and MOPSO algorithms
targeting thermal efficiency
exergy efficiency
and net present value (NPV)
with the Pareto optimal solution determined via the technique for order preference by similarity to ideal solution (TOPSIS) decision-making. Results indicate that the system achieves a cold energy utilization rate of 69.73%
with the de-heavy hydrocarbon tower accounting for 57.03% of the exergy destruction. The NPV demonstrates significantly higher sensitivity to the annual interest rate than to electricity prices. Compared with conventional systems
this solution exhibits superior thermodynamic performance and greater economic viability.
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