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针对风电的预测距离运行点越近精度越高的特点,结合随机优化和可调节鲁棒优化方法的优点,提出一种有需求响应参与,随机和可调节鲁棒共同构成日前调度的风电消纳模型.模型通过确定最优转换时刻,将随机优化和可调节鲁棒优化有效地结合,凸显远期调度以鲁棒性见长,近期调度以经济性占优的特点,实现源荷互动.该文基于 PJM-5节点系统的算例,验证模型的有效性.该文提出的模型相较于单一使用随机优化或者可调节鲁棒优化方法,可以通过转换时间的最优化,实现调度总成本的显著降低,但失负荷价值、风电置信度概率等关键参数对于最优转换时间影响较大,需谨慎选择.“,”In view of the characteristics of wind power prediction accuracy gradually increasing with the time scale and taking advantages of stochastic optimization and adjustable robust optimization, this thesis presented a stochastic & adjustable robust hybrid scheduling model. In the model, the stochastic programming and the adjustable robust optimization were effectively integrated together and realized the coordinated optimization of the power supply side resources and demand response resources. Finally, the examples of PJM-5 bus system verified the validity of the model. Comparing with models based on only stochastic programming or adjustable robust optimization, the proposed model can decrease total dispatch costs. Besides, some parameters such as value of lost load may affect the optimal transition time.