Title of article :
Fault Location in Active Distribution Networks Using Improved Whale Optimization Algorithm
Author/Authors :
Bahmanyar, A Center of Excellence for Power System Automation and Operation - Iran University of Science and Technology (IUST) - School of Electrical Engineering, Tehran, Iran , Borhani-Bahabadi, H Center of Excellence for Power System Automation and Operation - Iran University of Science and Technology (IUST) - School of Electrical Engineering, Tehran, Iran , Jamali, S Center of Excellence for Power System Automation and Operation - Iran University of Science and Technology (IUST) - School of Electrical Engineering, Tehran, Iran
Pages :
11
From page :
302
To page :
312
Abstract :
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.
Keywords :
Fault Location , Optimization , Self-Healing , Smart Grids , Whale Optimization Algorithm
Journal title :
Iranian Journal of Electrical and Electronic Engineering(IJEEE)
Serial Year :
2020
Record number :
2504858
Link To Document :
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