Distribution line capacity optimization using dynamic line rating and the internet of things technology

Abstract

Global energy demand is currently at an all-time high and is expected to rise even further in the years ahead. As a result, the demands on power system infrastructure are increasing to meet the ever-growing energy requirements. The investment requirement on the power system infrastructure is also increasing greatly to reliably power the loads on the system. However, the capital required for such projects is not readily available, especially in developing countries like Uganda which mostly rely on loans and donations to finance such projects. Although the power handling capacity of some of the existing power distribution lines has almost reached the operational limit, most of these power lines exhibit a capacity reserve because they were rated using conservative worst-case values of ambient temperature, wind speed and solar insolation yet these parameters vary at different times. This research implemented dynamic line rating (DLR) on the highly loaded Wabigalo - Bombo_2 33 kV power distribution line through real-time monitoring of the temperature in the proximity of the line using Internet of Things (IoT) enabled transmitters. The real-time rating of the power distribution line was then computed using the measured values of the ambient temperature. It was found that the power distribution line studied in this research was suitable for being uprated using DLR. Over a monitoring period of one month, it was observed that the average ambient temperature was 24 oC which is much lower than the conservative fixed value of 40 oC used in the design of these power lines. An average capacity gain of 27% (7 MVA) of the static line rating (SLR) of the power distribution line was earned in this monitoring period of one month through the use of DLR. The use of IoT transducers also significantly shortened the deployment time of the DLR system and cost compared with the widely used SCADA technology. In this research, only the ambient temperature in the proximity of the power line was monitored because the ambient temperature has a much higher impact on the rating of the line than other parameters. However, recommendations have been made for future studies to carry out DLR whilst measuring all the relevant weather parameters for higher capacity gains. The adoption of the DLR technology by the utility operators is also recommended so that they can optimally use the existing infrastructure and also lower the investment costs which in turn will lead to lower tariffs, high reliability and attract more connections.