针对光伏高渗透率农村配电网中光伏出力波动与季节性农业负荷集中投运叠加引发的农村台区供电能力不足，从而导致负荷削减量大的问题，本文提出一种面向农网供电风险控制的互联储能车（Interconnected Energy Storage Vehicle, IESV）优化调度策略。构建基于 IESV 的农村配电网系统架构，并建立 IESV 数学模型；刻画农业负荷显著的时空波动特性，在此基础上并提出预布局与动态调度两阶段调度策略。预布局阶段基于农忙前典型场景，以最小化配置成本与负载率偏离惩罚为目标，确定互联台区对，为农忙期负荷高峰预留运行裕度；在此基础上，为进一步应对负荷波动，提出动态调度阶段。该阶段基于预布局形成的拓扑，以最小化负荷削减功率为目标，优化 IESV 的接入位置与放电功率；两阶段在“规划-运行”顺序优化框架下协同，实现运行成本与负荷削减的综合优化。最后，通过 IEEE33 节点系统的仿真验证表明，所提策略在控制农网供电风险的同时，显著降低农业负荷削减量与系统总运行成本。

Aiming at the problem of large load shedding caused by insufficient power supply capacity of rural distribution stations due to the superposition of photovoltaic output fluctuation and centralized operation of seasonal agricultural loads in rural distribution networks with high photovoltaic penetration, this paper proposes an optimal scheduling strategy for Interconnected Energy Storage Vehicles (IESV) oriented to power supply risk control in agricultural distribution networks. The system architecture of a rural distribution network based on IESV is constructed, and the mathematical model of IESV is established. The significant spatio-temporal fluctuation characteristics of agricultural loads are described, and on this basis, a two-stage scheduling strategy including pre-layout and dynamic dispatch is proposed. In the pre-layout stage, based on typical scenarios before the busy farming period, with the objectives of minimizing the configuration cost and load rate deviation penalty, the interconnected distribution station pairs are determined to reserve operation margin for the load peak during the busy farming period. On this basis, the dynamic dispatch stage is proposed to further cope with load fluctuations. Based on the topology formed by pre-layout, this stage optimizes the access locations and discharge power of IESV with the objective of minimizing the load shedding power. The two stages cooperate under the sequential optimization framework of "planning-operation" to realize the comprehensive optimization of operation cost and load shedding. Finally, the simulation based on the IEEE 33-node system verifies that the proposed strategy can significantly reduce the agricultural load shedding and the total system operation cost while controlling the power supply risk of agricultural distribution networks.