LAUSR

Dynamic thermal rating (DTR) is more accurate and can better utilize the transmission/distribution capacity of an electric power system compared to static thermal rating. It is beneficial to integrate DTR into power system planning problems where modeling the DTR is vital. This paper presents a new modeling method for DTR that consists of three sequential steps: A multivariate polynomial regression between the DTR and its four affecting factors, an hourly normalization, and an autoregressive integrated moving average (ARIMA). Three types of polynomial regressions were developed based on the analysis of the heat balance model for calculation of the DTR. For the purpose of comparison, several other modeling methods for the DTR were designed based on a widely used wind speed modeling method. The performance of the different modeling methods was verified using case studies from Austin, USA and Wawa, Canada. The results show that the model of the DTR obtained using the proposed method is superior in terms of both probability distribution and fitting accuracy.