A Power Quality Monitoring Method for Active Distribution Networks with Low Data Volume Dependence

With a high proportion of new energy sources and a high proportion of power electronic equipment, the power quality problems of active distribution networks (ADNs) are complex, diverse, and prominent, bringing severe challenges to the reliable and high-quality operation of the power system. In order to ensure the safe and efficient operation of the distribution networks, it is necessary to conduct real-time monitoring of the power quality of the distribution networks. However, the traditional monitoring method usually requires a large number of sensors to collect massive grid data throughout the distribution networks for power quality analysis. As a result, the installation process of sensors and communication devices is complicated, the data transmission is huge, and the cost is very high, which is not conducive to the large-scale promotion and application of the monitoring system. This paper fully considers the operation characteristics of the ADNs and uses the impedance modeling method to study the distribution law of power quality worst points in the distribution networks after large-scale new energy access. Based on the distribution characteristics of the worst points, a low-cost and low-data-dependence power quality monitoring method for ADNs is proposed. The simulation results based on actual engineering are in agreement with the theoretical analysis, which verifies the effectiveness of the proposed method.