AUTHOR=Ma Xiaowei , Ke Xianbo , Ren Chong , Wang Jili TITLE=Data-Driven Optimization of Transmission Section Limits and Their Adaptability for New Power Systems With High Penetration of Renewable Energy JOURNAL=Frontiers in Energy Research VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.948595 DOI=10.3389/fenrg.2022.948595 ISSN=2296-598X ABSTRACT=

In traditional power systems, the transmission section limits are often set to predetermined values according to the typical peak-to-valley demand modes, which may be difficult to adapt to the complex and diverse operation modes of the new power systems with high penetration of renewable energy, and it cannot consider the coupling characteristics of AC and DC transmission sections also. In order to make better use of the efficiency of the transmission sections, a mathematical model for optimizing the adaptability of the transmission section limit is firstly proposed, in which a data-driven typical demand mode extraction method based on K-means clustering is proposed according to the load forecast, renewable energy forecast and market transaction data. Then, the adaptability assessment of the section limit and the transmission requirements are carried out. Finally, the power perturbation method is used to calculate the influence factor matrix of associated transmission section limit and stability margin of its dominant fault. And the influence factors are optimized according to section limit adaptability and stability margin influence, and the best adaptable limit of the associated transmission sections are obtained. The calculation and optimization results of the actual case of the interconnection corridor between Xinjiang and the northwest main power system of China verify the effectiveness and practicability of the proposed limit optimization model, which is able to improve the flexibility and adaptability of the actual power system operation.