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Mat Syai’in
Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia
Computer Science & IT Electrical & Electronics Engineering

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Economic Dispatch Using Quantum Evolutionary Algorithm in Electrical Power System Involving Distributed Generators Ni Ketut Aryani; Adi Soeprijanto; I Made Yulistya Negara; Mat Syai’in
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (804.9 KB) | DOI: 10.11591/ijece.v7i5.pp2365-2373

Abstract

Unpredictable increase in power demands will overload the supply subsystems and insufficiently powered systems will suffer from instabilities, in which voltages drop below acceptable levels. Additional power sources are needed to satisfy the demand. Small capacity distributed generators (DGs) serve for this purpose well. One advantage of DGs is that they can be installed close to loads, so as to minimise loses. Optimum placements and sizing of DGs are critical to increase system voltages and to reduce loses. This will finally increase the overall system efficiency. This work exploits Quantum Evolutionary Algorithm (QEA) for the placements and sizing. This optimisation targets the cheapest generation cost. Quantum Evolutionary Algorithm is an Evolutionary Algorithm running on quantum computing, which works based on qubits and states superposition of quantum mechanics. Evolutionary algorithm with qubit representation has a better characteristic of diversity than classical approaches, since it can represent superposition of states.
Co-Authors Adi Soeprijanto I Made Yulistya Negara Ni Ketut Aryani