On-line monitoring aided evaluation of power line cable shapes

Abstract

The paper presents a novel method that by coupling of the measurement data with an advanced 3D, extensible cable model allows for the prediction of power line configuration. The method, which may be considered as an example of the predictive digital twin, is presented in two variants that were validated throughout a comparison of the predictions with an in situ geodetic surveying. It has resulted in an excellent agreement of the computed and the real power cable shapes and confirmed reliability of the proposed approaches. We use on-line measured temperature and inclinations at a certain point on a cable to enhance the non-linear mechanical model (not the simple catenary curve) of the cable sag. The proposed coupling of the real data and a computational model is done twofold, by modification of either selected parameters or equations used to model power cable configuration. In both approaches, our power cable model is combined with a rigid body model of insulator chains. The proposed predictions with quantified uncertainties may support the power line dynamic rating that in turn may significantly increase the capacity of electric transmission systems. The key component of such systems is the processing of the collected data in order to determine the maximum current that can be transmitted safely, without violating the required clearance space. Making use of the advanced 3D, extensible cable model, instead of the catenary curve, insignificantly increases computation time, however it enables taking into account out of plane loading (wind), data overload as well as effective using of measurement uncertainties.