Multi-Time Scale Optimization of Agricultural Energy Internet Considering Coupling of Electricity, Heat, and Ammonia

With the cross-integration of agriculture and energy industry, the energy integration and optimization of agricultural parks has gradually become a research hotspot. Considering the multi-energy coupling in the agricultural production process, this paper constructs an operational architecture of an agricultural energy internet (AEI) consisting of power, heat, and ammonia equipment. Due to the limitations of forecasting technology, there are deviations in the predicted values of wind power, photovoltaics, and loads within AEI during the day-ahead and intra-day stages, which will lead to energy imbalance problems. To address the issue, a multi-time scale optimization strategy is proposed in this paper, including a long-term scheduling strategy for the day-ahead stage and a short-term correction strategy for the intra-day stage. In addition, a rolling optimization method based on the model predictive control algorithm is adopted in the intra-day stage, which achieves a tracking optimization and adaptive online correction of the day-ahead scheme. The research results indicate that the proposed strategy can effectively mitigate prediction errors and has good economic viability.