Utilizing Measurement Data from Low-voltage Grid Sensor in State Estimation to Improve Grid Monitoring

State estimation (SE) as a data processing algorithm is an integral part of the control and security analysis of a power system. SE filters redundant measurement data and other available information, thus providing high accuracy for system states. With a significant increase of distributed renewable energy in distribution networks, distribution system state estimation (DSSE) becomes essential. However, a lack of real-time measurements can cause an unobservable system that highly affects the accuracy of the DSSE. In this paper, we investigate the impact of a new measurement device, named LV-sensor, on the accuracy of the DSSE. The change point detection technique (CPD) is used to calculate the measurement variance from the collected data. The weighted least square (WLS) method is implemented for estimating the voltage magnitude and angle of a real distribution grid of a university campus. The results of the DSSE with the input variance using these LV-sensor can significantly increase the accuracy of the DSSE.