针对光伏光热互补发电机组内部出力不均衡导致的运行不稳、效率低下问题，提出一种基于Kmeans聚类算法的风电光伏光热互补发电机组调度方法。考虑到光伏光热发电机组具有间歇性、波动性和随机性等特点，采用Kmeans聚类算法预先对需要调度的数据归类分析，建立光能和风能可能出现的四种组合情况的目标函数，求解函数值，将该值作为下一步调度约束的初始条件值。调度方法结合了功率平衡、蓄能平衡、光伏光热上爬坡及下爬坡事件，计算实时出力值及最佳调度出力值，求解二者差值实现高效调度。试验结果证明，所提方法有效完成了发电机组的电力负荷及功率调度，运行波动和低效问题均得到明显改善，对电站的稳定运行起到了重要作用。

Aiming at the problems of unstable operation and low efficiency caused by the imbalance of internal output of photovoltaic photothermal complementary generator set, a scheduling method of wind power photovoltaic photothermal complementary generator set based on Kmeans clustering algorithm is proposed. Considering the intermittence, fluctuation and randomness of photovoltaic photothermal generation set, K-means clustering algorithm is used to classify and analyze the scheduled data in advance. The objective functions of four possible combinations of light and wind power are established, and the function value is calculated as the initial condition value of the next scheduling constraint. The scheduling method combines power balance, energy storage balance, photovoltaic photothermal uphill and downhill events, calculates the realtime output value and the optimal scheduling output value, and solves the difference between the two to achieve efficient scheduling. The experimental results show that the proposed method can effectively accomplish the load and power schedule of the generator set, and the problems of operation fluctuation and low efficiency are significantly improved, which plays an important role in the stable operation of power plants.

国网总部科技项目——分布式资源主动支撑的新型配电网多状态智能管控技术研究及示范应用（5400-202219152A-1-1-ZN）