Application of Key Cutting Algorithms for Optimal Power Flow Problems

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Published: Aug 1, 2011
DOI: https://doi.org/10.37936/ecti-eec.2012101.170482
Keywords:
Optimal Power Flow Genetic Algorithm Particle Swarm Optimization Sequential Quadratic Programming Key Cutting Algorithm

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Uthen Leeton
Power System Research Unit, School of Electrical Engineering, Institute of Engineering, Suranaree University of Technology
Thanatchai Kulworawanichpong
Power System Research Unit, School of Electrical Engineering, Institute of Engineering, Suranaree University of Technology

Abstract

This paper illustrates an application of Key Cutting Algorithm (KCA) to optimal power flow (OPF) problems in comparative with some effective mathematical and evolutionary optimization methods. The KCA is one of intelligence algorithms (AI), which was just developed since 2009. This algorithm emulates the work of locksmiths to open the lock. The best key that matches a given lock is pretended to be an optimal solution of a relevant optimization problem. The basic structure of the key cutting algorithm is as simple as that of genetic algorithms in which a string of binary numbers is employed as a key to open the lock. The proposed algorithm was tested with four mathematical test functions and three standard IEEE test power systems (6-bus, 14-bus and 30-bus test systems). The test power systems were divided into two cases. The first test case was given by applying a quadratic function to generators’ fuel-cost curve whereas a non-smooth fuel-cost function was assigned to the second. The comparisons among solutions obtained by sequential quadratic programming (SQP), genetic algorithms (GA), particle swarm optimization (PSO) and key cutting algorithm (KCA) were carried out. As revealed from the simulated results, the effectiveness of the KCA algorithm for solving OPF problems was confirmed.

Article Details

How to Cite
Leeton, U., & Kulworawanichpong, T. (2011). Application of Key Cutting Algorithms for Optimal Power Flow Problems. ECTI Transactions on Electrical Engineering, Electronics, and Communications, 10(1), 108–122. https://doi.org/10.37936/ecti-eec.2012101.170482
Issue
Vol. 10 No. 1 (2012): Special Session from ECTI-CON 2011
Section
Electrical Power Systems

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