부산대학교 도서관

With the growing proportion of renewable energy and increased load demand, the transmission network requires the use of dynamic thermal rating (DTR) to augment the capacity of transmission lines. However, DTR fluctuates dynamically due to environmental factors, which can cause congestion in the transmission system in real-time power markets. This paper proposes a framework for real-time congestion management, which is based on measurement data cleaning technology. Firstly, the paper applies data cleaning technology to cleanse the measured data and then accurately evaluates the state of transmission network nodes and lines through state estimation. Secondly, the transmission congestion is eliminated by utilizing a source-load collaboration method, with the aim of minimizing the adjustment amount. Finally, the validity and feasibility of the proposed framework are verified through an IEEE-39 node transmission network with real network data from Liaoning Province, China.