Day-Ahead scheduling of rural integrated energy systems based on distributionally robust optimization theory

Abstract

The integration of diverse industries in rural areas is an important step in building a smart countryside and achieving rural revitalization. Aiming at the problem of high energy consumption and pollution in agricultural production parks under the traditional energy structure, a new rural comprehensive energy park distribution robust scheduling model for water containing product breeding greenhouses is proposed in this paper. Firstly, a greenhouse model for aquaculture based on the principle of thermal flow is established. Secondly, considering energy production, consumption and storage, a rural integrated energy system model is established. In response to the uncertainty of residential electricity load, solar radiation, and environmental temperature within the park, a distributed robust optimization model is established using Kullback Leibler divergence. Finally, a numerical simulation is conducted using energy data from a real rural aquaculture park. The results show that compared to agricultural production parks under traditional energy models, the new rural comprehensive energy system model proposed in this paper fully integrates rural resources, reduces daily operating costs by 74.832 %, and reduces total carbon emissions by 33.75 %, providing theoretical support for rural industrial structure adjustment and energy transformation.