A bi-level optimal dispatch method for distribution networks and facility agricultural parks considering the regulation capability of power electronic devices and crop coupled growth characteristics

• Considering the dynamic demands of crops for light, heat, and carbon and their interactive coupling effects, a light-heat-carbon load model and corresponding coupled growth indicators for FAPs are established; • By jointly considering the secure and economical operation of distribution networks as well as the crop growth requirements and electricity costs of FAPs, a bi-level optimal dispatch method for distribution networks and FAPs is developed, which incorporates the regulation capability of power-electronic devices and crop coupled growth characteristics. Existing highly intelligent, large-scale, and industrialized facility agricultural parks (FAPs) often exhibit uncoordinated electricity consumption patterns, which not only lead to line overloads and voltage violations in rural distribution networks, but also increase the operating cost of FAPs. To address the insufficient characterization of crop growth characteristics in FAPs and the difficulty for flexible distribution networks to simultaneously ensure secure, economical operation and satisfy FAP crops growth requirements, this paper proposes a bi-level optimal dispatch method for distribution networks and FAPs considering the regulation capability of power electronic devices and crop coupled growth characteristics. First, the light-thermal-carbon coupled growth mechanisms of FAP crops are analyzed, and a light-thermal-carbon load balance model together with coupled crop growth indicators is established to quantitatively characterize crop growth demands. Second, a bi-level optimal dispatching model for the flexible distribution network and FAP is formulated. In the upper-level model, network losses, peak-valley difference, and line overload are minimized subject to power balance constraints and equipment regulation limits. In the lower-level model, the operating cost of the FAP and crop growth performance indicators are jointly optimized to determine the optimal electricity consumption strategy. Through iterative coordination between the upper and lower levels, collaborative optimization between the flexible distribution network and the FAP is achieved. Finally, case studies demonstrate that the proposed method can effectively reduce the operating cost of FAPs while ensuring normal crop growth, and simultaneously enhance the operational security and economic performance of the distribution network.