MLPN based Parameter Estimation to Evaluate Overhead Power Line Dynamic Thermal Rating

A widely and massively distributed power line sensor network (PLSN) has been proposed to monitor the status of utility assets to enhance line reliability and maximize the existing power grid utilization. One of its important applications is monitoring and evaluating the short-term overload capacity of an overhead power line (OHPL) down to a 'per span' level of granularity in real-time, and to determine the real-time dynamic thermal rating (RDTR) of the line under variant ambient weather conditions. Formulation of the RDTR requires repeated calculation to predict the conductor temperature ahead of time under various ambient conditions, often complex and difficult for real-time implementation. This paper, on the other hand, proposes a MLPN based parameter estimation scheme, by which the dynamic thermal rating is evaluated directly under different weather conditions with no conductor temperature prediction required. This method requires only temperatures and line current as inputs and its simplified calculation makes it an attractive and cost effective solution to real-time implementation. Furthermore, by continuously providing accurate real-time line thermal condition information, this method can assist in utilizing the power lines more effectively.