Multi-objective optimization of micro-energy network considering exergy efficiency

Compared with energy networks that only distribute a single kind of energy, the unique feature of micro-energy networks lies in the efficient and coordinated utilization of heterogeneous energy. To measure the quality of energy and to compare the capability of different energy sources or systems, ex...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of renewable and sustainable energy 2022-05, Vol.14 (3)
Hauptverfasser: Cheng, Jiawei, Mu, Longhua, Liang, Ziwen
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Compared with energy networks that only distribute a single kind of energy, the unique feature of micro-energy networks lies in the efficient and coordinated utilization of heterogeneous energy. To measure the quality of energy and to compare the capability of different energy sources or systems, exergy is a generally accepted tool in thermodynamics. Therefore, it is of great significance to introduce exergy to analyze energy utilization in quality. First, based on exergy analysis of a micro-energy network, a multi-objective optimal scheduling strategy considering exergy efficiency and economic costs is proposed, and a multi-objective optimal scheduling model is established. Second, the specified weights cannot be adjusted flexibly during the scheduling process; the optimal model can update the weights hourly and find the multi-objective optimal solution. The hunting algorithm is used to solve the optimization problem of this scheduling model, which has multiple constraints and variables. Finally, the simulation results show that the operating cost of the multi-objective scheduling model is reduced by 3.93% in summer, 7.87% in winter, and the overall exergy efficiency of the proposed model is increased by 1.92% in summer, 2.46% in winter, compared to single-objective optimization models. The results prove that the proposed multi-objective optimal scheduling strategy is effective and feasible.
ISSN:1941-7012
1941-7012
DOI:10.1063/5.0088883