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Pré-Publication, Document De Travail Année : 2023

Quasi-Dynamic Line Rating spatial and temporal analysis for network planning


Electric transmission networks are limited by their ampacity, the maximum current a conductor can carry whilst meeting safety criteria. Ampacity depends on a conductor's ability to dissipate Joule heat and fluctuates with weather conditions. Standard practice sets a single conservative currentcarrying limit for each season ('Static' Rating). As a result, transmission networks are performing substantially below their maximum capacity during the majority of their operation. This study proposes a methodology to design a Quasi-Dynamic Line Rating (quasi-DLR), based on ampacity simulations using historical weather reanalysis. As opposed to the static rating, this rating varies the current-carrying limit every hour of every month, allowing a higher percentage of a transmission line's capacity to be utilized. The methodology proposed can be applied to an existing transmission line to improve its performance or to a geographical region to aid in network design. Application of the quasi-DLR methodology on an example transmission line shows significant potential gains in transmission capacity, notably due to ampacity increases in the absence of solar radiation. The example also demonstrates better accommodation of low ampacity events during hot weather, potentially improving the safety of transmission networks. Meanwhile, application of quasi-DLR on a region to evaluate its transmission capacity shows a capacity to reveal potential ampacity bottleneck locations. All-in-all, the proposed methodology can potentially improve existing and future aerial transmission networks by increasing current capacity and security without adding additional infrastructure.
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Dates et versions

hal-03766110 , version 1 (07-09-2022)
hal-03766110 , version 2 (23-01-2023)


  • HAL Id : hal-03766110 , version 2


Stella Hadiwidjaja, Sergio Daniel Montana Salas, Andrea Michiorri. Quasi-Dynamic Line Rating spatial and temporal analysis for network planning. 2023. ⟨hal-03766110v2⟩
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