Time-Dependent Transmission Capacity Model for Long-Term Operating Reserve Assessment

Transmission network capacity needs to be regularly reinforced either by building new transmission lines or upgrading existing circuits. Moreover, expansion planning processes always consider deterministic static thermal ratings as the basis of the N-1 security criterion to meet the growing electricity demands. This paper proposes a probabilistic framework to assess the inclusion of a time-dependent transmission capacity model in expansion planning studies, enabled by dynamic line rating (DLR) technology application. This work first exploits the multivariate requirements associated with DLR-based approaches, discussing the use of electrical, mechanical and thermal variables. Next, a probabilistic framework is built to demonstrate the effectiveness of DLR technology by assessing reliability indices through a sequential Monte Carlo simulation. To illustrate the proposed approach, the IEEE-RTS GMLC 2019 and high voltage transmission line data of the Brazilian interconnected system are utilized. Numerical results show that the proposed approach can be used to certify the inclusion of DLR-based technology in the list of possible alternatives to reinforce transmission systems.