Multi-timescale collaborative operation of renewable energy-based power system and Agri-product supply chain considering dynamic energy consumption-based crop growth

The rapid expansion of modern agriculture has spurred leading companies to establish smart industrial parks in rural areas, facilitating integrated agri-product supply chains leveraging abundant crops, space, and natural resources. However, operating various segments within agri-product supply chains, such as crop growth, fruit refrigeration, and fruit transportation, requires a large energy supply, and may lead to substantial operation costs. Integrating the renewable energy-based power system with the agri-product supply chain emerges as a promising solution to address the high energy consumption within the supply chain. Therefore, this study proposes a multi-timescale collaborative operation framework for a rural integrated power system and agri-product supply chain (RIPS-APSC). Key innovations include: (1) Firstly, this framework innovatively integrates an agri-product supply chain into the power system to optimize energy operations and address high energy consumption challenges. (2) Secondly, in the production link of the agri-product supply chain, a dynamic energy-consumption-based crop growth model is established that accurately estimates greenhouse energy consumption and crop yield based on environmental factors like temperature, humidity, and carbon dioxide concentration. (3) Subsequently, this study introduces an operation optimization model for the RIPS-APSC system that uniquely integrates crop growth, agri-product refrigeration, transportation, and energy consumption. (4) Finally, the hourly timestep for energy consumption and the daily timestep for crop growth are both contained in the operation optimization model, addressing the challenge of inconsistent timesteps within the proposed multi-timescale collaborative operation framework. A case study involving greenhouses, central cooling warehouses, and consumers validates the proposed framework, and some sensitivity analyses are conducted in this work. The findings reveal that daily greenhouse energy consumption rises with the crop growth cycle and stabilizes after reaching maximum leaf area. The optimal refrigerated storage temperature for the warehouse is determined to be the upper limit of its temperature range. Additionally, sensitivity analysis demonstrates that decreasing the desired indoor temperature of greenhouses and the refrigerated storage temperature of the warehouse both lead to increased total system costs.