Abstract The growing demand for electricity and the restructuring of power markets is forcing the power industry to change the way that power systems are planned and operated. Traditionally, transmission lines have been operated based on fixed deterministic thermal ratings, 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. In this paper, a probabilistic static thermal rating method based on typical weather conditions along a transmission line is described and analyzed. The results of load and energy throughput analyses show that the use of this rating approach can significantly increase line throughput compared to traditional deterministic rating methods. However, this approach can also substantially increase the risk of thermal overload. To identify the problems associated with the use of a probabilistic static thermal rating method, we performed a sensitivity study. Statistical analysis of weather parameters shows that line ratings calculated from typical weather data are inflated. Additional results confirm that values of risk tolerance and wind direction incorporated into the rating method significantly affect the resulting rating values. We suggest values for these parameters that minimize the risk of line overloading.