Day-Ahead Collaborative Optimization Approach for New Energy and Energy Storage Clusters Considering Dynamic Limits of Multi-Level Cross-Sections

New energy clusters transmit across multiple voltage levels and multi-level sections have become a typical scenario of large-scale wind-solar base new energy concentrated transmission. However, as the proportion of new energy installations continues to rise, the aggregation level is continuously increasing as well, the actual transmission capacity of each section is greatly affected by the power flow distribution, and the coupling relationship between cross-section limits is complicated. Nowadays, the optimization scheduling strategy that only considers a single, static fixed-value cross-section limit of the cooperation of the new energy and the energy storage is no longer applicable. Therefore, the constraint expression of the dynamic time-varying limit of the section is proposed by multiple linear regression and then substituted into the day-ahead optimization model. Finally, a multi-level nested cross-section example in a province is selected for analysis, and the results verify the effectiveness of the proposed model.