en Fault Location Fault Location Research Paper Research Paper <div style="text-align: justify;"><span style="font-family:Times New Roman;"><span style="font-size:14px;"><span style="color:#000000;">To realize the self-healing concept of smart grids, an accurate and reliable fault locator is a prerequisite. This paper presents a new fault location method for active power distribution networks which is based on measured voltage sag and use of whale optimization algorithm (WOA). The fault induced voltage sag depends on the fault location and resistance. Therefore, the fault location can be found by investigation of voltage sags recorded throughout the distribution network. However, this approach requires a considerable effort to check all possible fault location and resistance values to find the correct solution. In this paper, an improved version of the WOA is proposed to find the fault location as an optimization problem. This optimization technique employs a number of agents (whales) to search for a bunch of fish in the optimal position, i.e. the fault location and its resistance. The method is applicable to different distribution network configurations. The accuracy of the method is verified by simulation tests on a distribution feeder and comparative analysis with two other deterministic methods reported in the literature. The simulation results indicate that the proposed optimized method gives more accurate and reliable results.</span></span></span></div> Fault Location, Optimization, Self-Healing, Smart Grids, Whale Optimization Algorithm. 302 312 http://ijeee.iust.ac.ir/browse.php?a_code=A-10-2071-2&slc_lang=en&sid=1 A. Bahmanyar bahmanyar@iust.ac.ir 180031947532846009304 180031947532846009304 No Center of Excellence for Power System Automation and Operation, Iran University of Science and Technology (IUST), School of Electrical Engineering, Tehran, Iran. H. Borhani-Bahabadi h_borhani@elec.iust.ac.ir 180031947532846009305 180031947532846009305 No Center of Excellence for Power System Automation and Operation, Iran University of Science and Technology (IUST), School of Electrical Engineering, Tehran, Iran. S. Jamali Sjamali@iust.ac.ir 180031947532846009306 180031947532846009306 Yes Center of Excellence for Power System Automation and Operation, Iran University of Science and Technology (IUST), School of Electrical Engineering, Tehran, Iran.