为解决可再生能源并入配电网对系统引起的电压波动，基于模型预测控制（model predictive control, MPC）提出电压协调控制方法保证安全运行。针对风电光伏出力不确定性提出AP-K-Medoids聚类算法对出力场景进行生成与削减，以系统网损最小为优化目标建立模型。采用接入有载调压变压器、电容器组、静止无功补偿器、风-光无功出力及储能充、放电协调多时间尺度电压控制。长时间尺度优化控制通过多时步滚动优化求解系统各装置出力，以风-光出力及负荷需求预测为前提；而短时间以长时间为基础滚动优化求解出力的增量。优化控制模型是非凸、非线性的模型，利用二阶锥规划模型处理非线性问题实现求解。采用改进的IEEE33节点配电网系统进行算例分析，研究结果证明所提电压优化控制策略的可行性。

To address the voltage fluctuations caused by the integration of renewable energy into the distribution network, a voltage coordinated control method based on MPC (model predictive control) was proposed to ensure safe operation. Aiming at the uncertainty of wind and photovoltaic output, the AP-K-Medoids clustering algorithm was proposed to generate and reduce output scenarios, and a model was established with the optimization objective of minimizing system network loss. Adopting multi time scale voltage control through the integration of on load voltage regulating transformers, capacitor banks, static reactive power compensators, wind solar reactive power output, and energy storage charging and discharging coordination. Long term scale optimization control solves the output of each device in the system through multi-step rolling optimization, with wind solar output and load demand prediction as the premise. On the basis of short-term and long-term rolling optimization, the increment of output is solved. The optimization control model is a non convex and nonlinear model, which utilizes a second-order cone programming model to solve nonlinear problems. Using an improved IEEE33 node distribution network system for case analysis, the research results demonstrate the feasibility of the proposed voltage optimization control strategy.