Fault location identification in smart distribution networks with distributed generation

Power lines in distribution networks are subject to several subjects such as bad weather conditions, contact with animals, equipment malfunction, etc. These conditions may cause a fault in the power lines that may damage the devices in the network if it is not self-cleared by the protection devices present. A fault location identification method is proposed that can accurately identify the fault location within seconds so that utilities companies have a better understanding of where to mitigate the fault. The algorithm collects data from the measurements available from the smart grid devices such as Advanced Metering Infrastructure (AMI), Reclosers, Power Quality Meters, and other smart meters present in the grid. The algorithm is suitable for distribution networks with Distributed Generation (DG) and smart measurement infrastructure that can transmit event-driven data such as pre and post-fault voltages or currents. To overcome the problem presented by the lack of metering points to know every operating condition in the system, the technique is based on State Estimation to locate the fault. The research work presents a MATLAB-based state estimation (SE) technique applied to identify the fault location in Real-Time. The validation of the method was assessed by simulating the IEEE 37 nodes test feeder as an operating distribution grid with DG with Opal-RT technology. Fault-on voltage and current from virtual smart meters measurements are gathered in Real-Time. The Real-time data from the smart meters is fed to the State Estimation algorithm to determine the fault location which is then presented in a Graphic User Interface (GUI) for the easy understanding of a utility company operator. The method was tested for different transformers configuration, a multisource distribution grid with DG presence, symmetrical and asymmetrical fault types giving the accurate location in 90% of the cases.