RETRACTED: Supply–Demand Dynamics Quantification and Distributionally Robust Scheduling for Renewable-Integrated Power Systems with Flexibility Constraints

作者：Jiaji Liang, Jinniu Miao, Lei Sun, Liqian Zhao, J.‐C. Wu, Peng Du, Wei Zhao · 发表于：Energies · 年份：2025 · DOI：10.3390/en18051181 · 被引用次数：4 · 研究领域：Smart Grid Energy Management、Electric Power System Optimization、Integrated Energy Systems Optimization

The growing penetration of renewable energy sources (RES) has exacerbated operational flexibility deficiencies in modern power systems under time-varying conditions. To address the limitations of existing flexibility management approaches, which often exhibit excessive conservatism or risk exposure in managing supply–demand uncertainties, this study introduces a data-driven distributionally robust optimization (DRO) framework for power system scheduling. The methodology comprises three key phases: First, a meteorologically aware uncertainty characterization model is developed using Copula theory, explicitly capturing spatiotemporal correlations in wind and PV power outputs. System flexibility requirements are quantified through integrated scenario-interval analysis, augmented by flexibility adjustment factors (FAFs) that mathematically describe heterogeneous resource participation in multi-scale flexibility provision. These innovations facilitate the formulation of physics-informed flexibility equilibrium constraints. Second, a two-stage DRO model is established, incorporating demand-side resources such as electric vehicle fleets as flexibility providers. The optimization objective aims to minimize total operational costs, encompassing resource activation expenses and flexibility deficit penalties. To strike a balance between robustness and reduced conservatism, polyhedral ambiguity sets bounded by generalized moment constraints are employed, leveraging Wasserstein metric-bas...