Karim Allahdadi

  • Thesis Title: A fault detection algorithm for low voltage inverter-based islanded microgrids
  • Grade: Master of Science
  • Final: Sept. 2019
  • Supervisor: Dr. Iman Sadeghkhani
  • Advisor: Dr. Bahador Fani
  • Abstract

    Today, with the appearance of the distributed energy resource (DER) and increase of their penetration in the distribution network, the microgrid concept has been proposed to alleviate the technical challenges of these resources. The microgrid is a subset of the main grid, consisting of a set of loads and small energy resources preferably renewable ones. In the case of a grid fault, the microgrid is disconnected from the main grid and provides the energy required by the consumers in their area through its DER units. This will prevent widespread blackouts and increase network reliability. But, the specific features of the microgrid have made their protection challenging. Due to the absence of synchronous generators in the microgrids and also limited output current of the converters, overcurrent protection on these types of networks is not particularly effective in islanded mode and other schemes need to be applied. Also, bidirectional fault current due to the presence of DER units makes it difficult to find the faulty zone. In this thesis, a microgrid protection scheme is proposed for inverter based microgrids in the islanded mode of operation. In this scheme, by obtaining the correlation coefficient between the current signal and the voltage reference signal, fault occurrence, faulty zone, and fault type are quickly and accurately diagnosed. Some features of this scheme include the ability to differentiate fault condition from the load and capacitive bank switchings, proper performance in the presence of nonlinear loads and measurement noises, and ability to distinguish forward and reverse fault. Results obtained from the simulation of various case studies performed in MATLAB/Simulink environment indicate the effectiveness of the proposed scheme in protecting inverter-based microgrids.