Author : Said Fouad Mohamed Mekhemar
CoAuthors : A. Y. Abdelaziz, Mostafa Algabalawy
Source : Engineering Review
Date of Publication : 01/2018
Abstract :
Hybrid power generation system (HPGS) is an
active research area, which is in need of a
continuous improvement. It represents the best
solution for the most complex problems facing the
world in the last decades. These problems are
known as the shortage of energy, or lack of
electricity, which logically are the results of the
continuous increasing demand. Therefore, the
researchers do their best to overcome all expected
roadblocks facing the development, where the most
applicable solutions to solve these problems are
introduced. In this paper, the HPGS includes; wind
turbine (WT), photovoltaic (PV), storage battery
(SB), gas turbine (GT), and utility grid (UG). The
GT of this system is fueled directly from the natural
gas distribution network considering all
operational conditions of it, which may be affected
by fueling the natural gas for the GT. So, the
natural gas distribution network is becoming an
important component of the HPGS, and it is
included in the HPGS for the first time. Multi metaheuristic optimization techniques are applied to
obtain the components sizing of this system, where
cuckoo search algorithm (CSA), firefly algorithm
(FA), and flower pollination algorithm (FPA) have
been applied. Therefore, this paper introduces a
new contribution not only to the new configuration
of the HPGS, but also in applying the new
optimization techniques as solving tools. The
output results are compared to show the
effectiveness and the superiority of the applied
techniques as well as extract a recommendation for
the best solving technique.
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