Abstract
The growth of intermittent distributed energy sources (DERs) in distribution grids is raising many new operational challenges for utilities. One major problem is the back feed power flows from DERs that complicate state estimation for practical problems, such as detection of lower level fault currents, that cause the poor accuracy of fault current identification for power system protection. Existing artificial intelligence (AI)-based methods, such as support vector machine (SVM), are unable to detect lower level faults especially from inverter-based DERs that offer limited fault currents. To solve this problem, a current tracing method (CTM) has been proposed to model the single distribution feeder as several independent parallel connected virtual lines that traces the detailed contribution of different current sources to the power line current. Moreover, for the first time, the enhanced current information is used as the expanded feature space of SVM to significantly improve fault current detection on the power line. The proposed method is shown to be sensitive to very low level fault currents which is validated through simulations.
Highlights
Due to the increasing penetration rate of distributed energy sources (DERs), such as solar power injected at the distribution side of the power system, during the past decade, distribution grids have become large, complex, interconnected networks
With DERs, excess power can be generated and consumed by the customer or feed back to the distribution feeder. This raises new challenges, especially in grid modeling methods for fault current identification, where the impact of back feed power flow has to be considered for determining the fault current threshold
DERs that connect to bus 1 cannot support the AC loads attached to bus 1 so that the currents flow from bus 2 to bus 1, which is opposite from the case shown in the companion paper [20]
Summary
Due to the increasing penetration rate of distributed energy sources (DERs), such as solar power injected at the distribution side of the power system, during the past decade, distribution grids have become large, complex, interconnected networks. The infusion of DERs onto distribution grids raises some new state estimation challenges, such as fault current identification, which was less of an issue in conventional distribution grids operating without DERs. The traditional distribution grid was not affected by irregular back power feeds caused by intermittent DER activity, as it was originally designed for single direction power flow from the substation to the customers. With DERs, excess power can be generated and consumed by the customer or feed back to the distribution feeder. This raises new challenges, especially in grid modeling methods for fault current identification, where the impact of back feed power flow has to be considered for determining the fault current threshold. Failure to do so may have far reaching and costly consequences such as inadvertent tripping of circuits or overlooking faults in the system
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