计及惯量和风电双重不确定性的两阶段分布鲁棒机组组合OA

[Objective]To address the insufficient system frequency response capability caused by the diversification and uncertainty of grid inertia under high renewable energy penetration,this paper proposes a method for unit commitment that considers diverse inertia sources as well as the uncertainties associated with inertia and wind power.[Methods]First,an inertia uncertainty model is established by integrating various inertia sources,including synchronous generator inertia controlled by the dispatch center,inertia from small-scale synchronous generators not directly controlled by the dispatch center,virtual inertia,and demand-side inertia.Second,a data-driven two-stage distributionally robust optimization(DRO)model is formulated to characterize the dual uncertainties of inertia and wind power.The 1-norm and ∞-norm are utilized to constrain the confidence set of uncertain probability distributions.Meanwhile,dynamic frequency constraints are incorporated into the second-stage model.Finally,the absolute value terms within the model are linearized,and the Column-and-Constraint Generation(C&CG)algorithm is employed to solve the two-stage model.[Results]Compared with the unit commitment model considering only the inertia of large synchronous generators,the proposed two-stage DRO model,which accounts for the dual uncertainties of inertia and wind power,demonstrates superior frequency response capability and reduces the total generation cost by 3.3%.[Conclusions]Compared with other uncertainty-handling methods,the constructed model achieves better economic efficiency than robust optimization models and enhanced robustness compared to stochastic optimization models.It effectively balances the relationship between economic efficiency and robustness,thereby ensuring the power system′s dynamic adaptability under high renewable energy penetration scenarios.