The rapid expansion of variable wind and solar power intensifies supply-demand mismatches and increases the need for long-duration, cross-sector energy storage. Liquefied natural gas (LNG) offers a comparatively favorable balance among volumetric energy density, gravimetric energy density and infrastructure compatibility. Against this background, renewable power-to-LNG (PtLNG) integrates renewable H 2 production, captured-CO 2 methanation and cryogenic liquefaction to convert surplus renewable electricity into a transportable methane-based fuel compatible with established LNG infrastructure. Unlike gaseous power-to-gas (PtG) and power-to-methane (PtM) systems, PtLNG extends the system boundary to gas conditioning, liquefaction feed-quality control, boil-off gas (BOG) management and LNG storage. Existing studies largely examine electrolysis, CO 2 methanation, renewable methane and LNG liquefaction separately, leaving cross-process interactions insufficiently synthesized. This review first examines the key process units and operating constraints associated with renewable H 2 production, CO 2 supply and purification, methanation, gas conditioning and liquefaction. It then evaluates material flow and gas composition management, thermal management and heat recovery, and cryogenic liquefaction and cold energy management, with emphasis on gas recycle and purge, impurity control, heat-source and heat-sink matching, liquefaction specific energy consumption (SEC), BOG recovery and LNG storage. Finally, it reviews system integration and optimization through system-boundary definition, performance indicators, process simulation, multi-objective optimization and multi-timescale buffering. The review shows that overall PtLNG performance depends on coordinated matching of material flows, heat recovery, gas composition, liquefaction demand and buffering requirements rather than isolated optimization of individual process units. Future work should prioritize dynamic validation, liquefaction-grade e-methane specifications and modular integration under realistic operating conditions.
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Liu et al. (2026) studied this question.
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