TY  - EJOU
AU  - Song, Yanlou 
AU  - Xue, Gaichao 
AU  - Li, Xiangshuo 
AU  - Wu, Yuchen 
AU  - Wu, Po 
AU  - Zhang, Bo 
AU  - Wang, Xiang 

TI  - Complementary Coordinated Optimization Strategy for Power Line Overloading Based on Multiple Flexible Resources
T2  - Energy Engineering

PY  - 
VL  - 
IS  - 
SN  - 1546-0118

AB  - The fluctuations and prediction uncertainty of distributed renewable energy output and load demand make power lines in medium- and low-voltage power grids more prone to overloading. Together with time-varying line loading rates, such uncertainty makes overloading risks change dynamically. Numerous and widely distributed flexible resources can support line overloading regulation, but directly including all resources in the optimization model increases the model scale and computational burden. Existing studies have not sufficiently considered dynamic overloading risk identification and the complementary adjustment characteristics of different flexible resources. To address these challenges, this paper proposes a coordinated rolling optimization method for intra-day operational regulation and online decision support. First, a dynamic power line overloading risk coefficient is constructed by considering prediction uncertainty in distributed renewable energy output and load demand, as well as the loading rates of all power lines. This coefficient helps identify potential overloading risks in advance. Second, a pre-selection algorithm is developed for multiple-line overloading scenarios by evaluating the line-resource influence relationship, impact direction, impact magnitude, and adjustment cost of flexible resources. Effective and cost-efficient resources are preferentially selected before optimization, thereby reducing the complexity of the optimization model. Finally, based on the pre-selection results, a coordinated optimization model for multiple flexible resources is established, and rolling optimization is used to update the dispatch scheme and reduce the impact of prediction errors. Simulation results show that the proposed method can effectively mitigate overloading on multiple power lines while reducing the optimization scale and improving computational efficiency.
KW  - Multiple power line overload; multiple flexible resources; resource pre-selection; dynamic overload risk coefficient; complementary coordination; rolling optimization

DO  - 10.32604/ee.2026.086637