Modeling of an HPS for the electric power demand of the cattle farm using genetic algorithm

Today, as the demand for energy increases based on the increasing population and improving technology, resorting to new energy sources has become a necessity. Due to the rapid consumption of fossil fuels and the responsibility of humanity for the environment, Renewable Energy Sources (RES) are of a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Heliyon 2023-06, Vol.9 (6), p.e17237-e17237, Article e17237
Hauptverfasser: Oz, Osman, Sahin, Mustafa, Akar, Onur
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Today, as the demand for energy increases based on the increasing population and improving technology, resorting to new energy sources has become a necessity. Due to the rapid consumption of fossil fuels and the responsibility of humanity for the environment, Renewable Energy Sources (RES) are of a quality that may respond to this necessity. But the RES such as sun and wind vary depending on the weather conditions. Considering such variance, Hybrid Power Systems (HPS) are suggested in order to assure reliability and continuity in energy generation. For the sake of strengthening the HPS that are dependent on weather conditions, it is considered to increase the system's reliability and continuity through the inclusion in the HPS of cattle biomass reserves in the area. In this paper, it was studied on modeling of HPS based on sun, wind and biogas that will meet the electric power demand of the cattle farm located at Afyonkarahisar, Turkey. The two decades' animal population and load value changes were estimated through Genetic Algorithm (GA), and the HPS model was investigated under different scenarios considering sustainable energy and environment objectives, and the analyses were performed considering the changes in economic parameters.
ISSN:2405-8440
2405-8440
DOI:10.1016/j.heliyon.2023.e17237