Increased consumption and increased use of renewable energy make overhead lines and transformers more often congested. Dynamic rating (DR) uses a time-depending maximum permissible current instead of a long-term-fixed rating; it is an effective solution to upgrade the capacity of existing grid assets to minimize this congestion. Dynamic line rating (DLR) considers how the weather affects the thermal behavior of the conductor and therewith its rating; environmental parameters as well as conductor characteristics have to be considered. Likewise, dynamic rating of transformers (DTR) relies on a thermal assessment of the hottest spot in the transformer windings. The hot-spot temperature is dependent on the ambient temperature, loading, and transformer’s cooling system.

In this thesis, a number of lesser-studied aspects of DR are studied: stochastic modeling of the rating; relations between protection, reliability and rating; risk assessment for line selection when using DLR; and increased transformer hosting capacity (HC) in the presence of solar photovoltaic (PV).

In the first part of the work, the focus is on the stochastic modeling of DLR and its relation to the protection operation. Actual line rating is considered a random variable in the protection system for a more flexible decision-making. Different sources of uncertainties are modeled using suitable probability density functions. The method allows for a transparent trade-off between the risk of failure to take measures and the risk of unnecessary measures against overload. The results depicts that deterministic DLR could result in high probabilities of overloading or would require large safety margins. While, a stochastic approach will allow for both small margins and appropriate risks.  

A generic model is introduced to consider DLR reliability from two different viewpoints: errors and failures of components that would affect the calculation of the rating; and the impact of a DLR failure on the power system. The qualitative reliability study highlights that it is important to update the protection settings on a real-time basis. 

In the second part of the work, a risk assessment framework is proposed to select the minimum set of overhead lines for DLR implementation. Results show a possible increase of permissible hosting capacity (HC) for electric-vehicle charging by up to 80% (depending on the test system and initial data) with low interruption costs and reduced risk of congestion. Furthermore, the improvement in the transformer HC by using DTR has been quantified. The results indicate that depending on the HC performance indices, the transformer can be loaded beyond the normal operational limits up to 35% to host PV and up to 100% for increased consumption.