2017
DOI: 10.11591/ijece.v7i5.pp2365-2373
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Economic Dispatch Using Quantum Evolutionary Algorithm in Electrical Power System Involving Distributed Generators

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. T… Show more

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Cited by 3 publications
(3 citation statements)
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“…In addition, the AIS, Meta-EP and Base techniques were compared to verify the quality of the performance proposed techniques solutions. However, the Base technique based on Hadi Saadat is only shown as fundamental results for both standard IEEE 26 and 57 bus systems [15]. The NMEP for SOCEELD provided the solution to reduce the total generation cost by not only focusing on the fuel generator but also including the other maintenance cost.…”
Section: Results and Analysismentioning
confidence: 99%
“…In addition, the AIS, Meta-EP and Base techniques were compared to verify the quality of the performance proposed techniques solutions. However, the Base technique based on Hadi Saadat is only shown as fundamental results for both standard IEEE 26 and 57 bus systems [15]. The NMEP for SOCEELD provided the solution to reduce the total generation cost by not only focusing on the fuel generator but also including the other maintenance cost.…”
Section: Results and Analysismentioning
confidence: 99%
“…Metaheuristic-based methods have been widely and more successfully handling OELD problem. Differential evolution algorithm (DEA) [8], Quantum Evolutionary Algorithm (QEA) [9], Hybrid integer coded differential evolution -dynamic programming (HICDE-DP) [10], Improved differential evolution algorithm (IDEA) [11], Colonial competitive differential evolution (CCDE) [12], Stud differential evolution (SDE) [13] and Hybrid differential evolution and Lagrange theory (HDE-LH) [14]. Real-coded genetic algorithm (RCGA) and Improved RCGA (IRCGA) [17].…”
Section: Introductionmentioning
confidence: 99%
“…This method has been used to solve many actual UCTP cases. There are several GA models such as informed GA [10], parallel GA [2], NSGA II [11,9], Adaptive Real Coded GA [13], Hybrid Fuzzy and GA [6], Quantum Evolutionary Computing [1], and distributed model GA [14] that have been proposed. This research used the distributed model GA, or what is known usually as Island Model GA [14], out of all these models.…”
Section: Introductionmentioning
confidence: 99%