Scenario-Based Optimized Coordinated Scheduling of Transmission and Distribution Networks With Multiple Timescales Considering Renewables Correlations

The increasing integration of distributed energy resources (DERs) into distribution networks enhances operational flexibility but also introduces significant challenges, including bidirectional power flow and uncertainties in both generation and load. These challenges complicate the scheduling and secure operation of integrated transmission and distribution (T&D) systems. To address these issues, this paper presents a multi-timescale scenario-based optimal scheduling approach for an integrated transmission–distribution power system considering the correlation of DERs. First, an adaptive multivariate nonparametric kernel density estimation method is developed to construct high-dimensional joint probability distributions of DER outputs, capturing complex correlations between wind power and photovoltaics. Second, a hybrid scenario generation method combining improved rejection sampling with a continuous-time Markov chain is proposed to efficiently produce realistic and representative scenarios across multiple timescales. Third, a coordinated scheduling strategy is designed, which integrates scenario-based optimization into both day-ahead and intraday operations, balancing cost minimization with risk management. Numerical case studies verify the effectiveness of the proposed method, demonstrating enhanced coordination between transmission and distribution levels and improved reliability and DER accommodation.