Akademik Veri Yönetim Sistemi
JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, cilt.39, sa.4, ss.2289-2303, 2024 (SCI-Expanded)
In this study, a metaheuristic Particle Swarm Optimization based optimization tool has been designed to be
used in the optimization of Hybrid Renewable Energy Systems, which eliminates the negative aspects of the
most frequently used HOMER software in this field. In the comparison made in terms of processing speed,
it was seen that the designed system reached the result faster by obtaining the result in 17 seconds, which
the HOMER software obtained in 936 seconds in optimizing the same system. In the economic comparison,
as a result of the optimization made by two different tools; There is a difference of 1.737% in Energy cost,
0.85% in Total Net Present Cost and 1.895% in Initial Capital, and there is no significant difference between
the results. In the comparison of the electrical results, there is a difference of 0.031% for the fed loads and
1.071% for the unmet loads, and the reliability of the results in electrical terms has been demonstrated. The
capacity shortage parameter was used for the first time in the optimization of renewable energy sources with
the metaheuristic algorithm. Energy Cost is used as the objective function. In short, a unique and reliable
optimization tool has been designed as an alternative to the HOMER program that can achieve much faster
results and eliminates the sensitivity, cumbersomeness and difficult search space generation processes in the
HOMER program. This tool will also facilitate the generation of a large amount of data by obtaining the
necessary optimization outputs very quickly to train surrogate models, machine learning or deep learning
based optimization systems.