Abstract
Deterministic static thermal ratings of overhead transmission lines are usually conservative, causing underutilization of their potential capacity. Efforts to overcome this limitation led to the development of alternative rating strategies, based on probabilistic and dynamic methods. One such strategy is the seasonal static thermal rating. It uses a probabilistic rating approach with explicit treatment of seasonal effects on conductor temperature. In this paper, we present several variants of seasonal ratings, and analyze their performance with respect to other rating approaches. Seasonal ratings use a set of predetermined probabilistic ratings that are engaged according to the season of year or time of day. By alternating among several ratings, transmission lines can be operated closer to their actual ampacity. In addition, seasonal ratings can reduce the risk of thermal overload, compared to the uniform probabilistic rating which remains constant at all times. Despite the risk reduction, and counter to the common belief, they still pose a significant risk of conductor thermal overload. Characteristics of several seasonal rating strategies are illustrated using a case study involving a power transmission line in Newfoundland, Canada. Simulation results show that seasonal ratings can provide a modest increase in transmission line throughput, compared to the basic probabilistic rating. However, they also confirm the high levels of residual risk.
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