MODERN OPTIMIZATION ALGORITHMS FOR FAULT LOCATION ESTIMATION IN POWER SYSTEMS

About the authors:

Kudryashov Ivan Sergeevich,

Undergraduate Student, the University of Tyumen,

spider-1998@mail.ru

Garkusha Nadezhda Anatolievna,

Candidate of Pedagogic Sciences, University of Tyumen, Institute of Mathematics and Computer Sciences, Foreign Languages and Intercultural Professional Communication Department, Associate Professor, n.a.garkusha@utmn.ru

Abstract:

This text presents a fault location estimation approach in two terminal transmission lines using Teaching Learning Based Optimization (TLBO) technique, and Harmony Search (HS) technique. Previous methods were discussed such as Genetic Algorithm (GA), Artificial Bee Colony (ABC), Artificial neural networks (ANN) and Cause & Effect (C&E) with discussing advantages and disadvantages of all methods. Simulation of the model was performed on SIMULINK by extracting initial inputs from SIMULINK to MATLAB, where the objective function specifies the fault location with a very high accuracy, precision and within a very short time. Future works are discussed showing the benefit when using the Differential Learning TLBO (DLTLBO)

References:

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