Promoting deep decarbonization of energy systems is crucial for achieving China's carbon peaking and carbon neutrality goals. Plant carbon sequestration, as a key carbon sink pathway, has not yet been incorporated as a schedulable resource into existing energy optimization systems. To address this limitation, this study proposes a low-carbon optimal scheduling method that integrates precise plant carbon sequestration replenishment with energy systems. First, a five-dimensional synergistic rural energy system architecture encompassing source-grid-load-storage-carbon is established to achieve flexible resource scheduling. Second, a coupling model integrating carbon capture system, power-to-gas, and plant carbon sequestration is developed to facilitate coordinated regulation of carbon sources and sinks, establishing a full-chain carbon cycle. Finally, a bi-level collaborative optimization scheduling method is proposed to simultaneously optimize carbon flow allocation and energy dispatch. Simulations conducted on a rural energy system in Hebei Province, China, demonstrate that the proposed coupling model reduces operating costs by 12.8 %, increases the carbon-energy utilization efficiency to 20.3 %, and lowers the carbon emission intensity by 7.41 %, compared to the baseline scenario. The implementation of the bi-level optimization method further reduces the total operating cost by 13.4 % and decreases the reliance on externally procured carbon sources by 71.1 %, thereby simultaneously minimizing system operating costs and maximizing carbon trading benefits. This study provides a replicable technical solution for the low-carbon transition of rural energy systems. Future research should consider the impact of seasonal variations on the model and enhance the model's adaptability to various crops and greenhouse structures.
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Gao et al. (2025) studied this question.
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