Optimal allocation method of oxygen enriched combustion-carbon capture low-carbon integrated energy system considering uncertainty of carbon-source-load

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In the context of green grid, it is crucial to enhance the low-carbon transformation of integrated energy systems. To improve the degree of low-carbon in these systems, this paper proposes an optimal allocation method of oxygen enriched combustion-carbon capture low-carbon integrated energy system considering the uncertainty of carbon-source-load. Firstly, this paper provides an analysis of uncertainties of carbon-source-load and uses budget uncertainty sets to model the three uncertain parameters. Secondly, in the integrated energy system, the by-product O2 of hydrogen production by electrocution and the oxygen storage device are used to provide oxygen-enriched combustion conditions for the gas turbine to reduce the CO2 generated in the combustion process. At the same time, the carbon capture device is used to collect CO2, and the oxygen enriched combustion-carbon capture integrated energy system is formed. Finally, an improved multi-populations quantum-behaved particle swarm optimization algorithm is proposed to solve the proposed model. This method considers the uncertainty of carbon emission intensity, which makes the optimal allocation of integrated energy system more inclined to low-carbon rather than economic. In addition, in terms of model structure, this method integrates oxygen enriched combustion-carbon capture into the integrated energy system to form a low-carbon model, which directly improves the low-carbon performance of the system. The simulation results show that the carbon emission of the proposed method is reduced by 38.8 % compared with other methods.