Low-carbon economic scheduling for AIES considering flexible load coordination and multiple uncertainties

Hongjun Gao, Wenqin Wang, Shuaijia He, Zhiyuan Tang and Junyong Liu

Renewable Energy, 2024, vol. 228, issue C

Abstract: The disordered energy use in traditional agricultural production has resulted in high energy purchase costs and carbon emissions. The coupling of integrated energy systems with agriculture offers the potential for flexible coordination of agricultural loads while agricultural loads are highly influenced by changes in the natural environment. In this context, this paper proposes a low-carbon and economic scheduling optimization method for agricultural integrated energy system (AIES), which comprehensively takes temperature, light intensity, and the coordination of agricultural loads into consideration. Firstly, solar and biomass resources are integrated through energy conversion equipment to support energy supply from both the electrical distribution network (EDN) and the gas network. At the same time, the modelling process of agricultural load is refined, which is divided into crop irrigation, greenhouse temperature control and residential consumption. The models of agricultural multi-energy complementary and energy storage equipment are established to achieve flexible conversion between different energy sources. In addition, the distributionally robust optimization (DRO) method based on multiple discrete scenarios is adopted to deal with the uncertainties arising from environmental condition fluctuations during the optimization process. Finally, the proposed model is tested on 4 various regions and 2 different seasons. Numerical results show that the proposed model can effectively enhance the economic and environmental performance of the AIES.

Keywords: Agricultural integrated energy system; Low carbon; Agricultural load; Uncertainty (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:228:y:2024:i:c:s0960148124007110

DOI: 10.1016/j.renene.2024.120643

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