Modeling and multi-objective optimization of a stand-alone PV-hydrogen-retired EV battery hybrid energy system

•The reclamation of retired EV batteries in hybrid energy systems.•Set up of a retired EV battery model considering capacity fade.•Design of a power management strategy for protecting system components.•Set up of a multi-objective optimization model considering energy waste.•Comparison of performanc...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Energy conversion and management 2019-02, Vol.181 (C), p.80-92
Hauptverfasser: Huang, Zhiyu, Xie, Zhilong, Zhang, Caizhi, Chan, Siew Hwa, Milewski, Jarosław, Xie, Yi, Yang, Yalian, Hu, Xiaosong
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•The reclamation of retired EV batteries in hybrid energy systems.•Set up of a retired EV battery model considering capacity fade.•Design of a power management strategy for protecting system components.•Set up of a multi-objective optimization model considering energy waste.•Comparison of performance of NSGA-Ⅱ and MOEA/D. Reusing retired electric vehicle batteries (REVBs) in renewable energy systems is a relatively new concept, and the presented PV-hydrogen-REVB hybrid energy system is a promising way to exploit REVBs’ residual capacities. This paper focuses on the design and sizing optimization of the entire system and delivers three main contributions. First, this paper proposes a REVB model based on the model of capacity fading of lithium battery cells, which could allow a more realistic result for the design. Second, a power management strategy is presented to regulate the energy flow, for protecting the REVB and other system components. Third, multiple objectives are considered in the optimization model, including minimizing loss of power supply, system cost, and a new indicator, namely, potential energy waste. Then, using the simulation results of a five-year working period to calculate the objective functions, a multi-objective evolutionary algorithm NSGA-II is applied to generate the Pareto set of a case for residential usage. In further discussions, the influences of ignoring REVB’s capacity fading and removing the objective of potential energy waste possibility are presented, as well as the comparison of performances between NSGA-II and MOEA/D. The results reveal that the reliability of the system is impaired if ignoring the REVB’s capacity loss, and the proposed indicator is crucial for the design. NSGA-II has a better performance regarding the distribution of solutions and gives better results in this study.
ISSN:0196-8904
1879-2227
DOI:10.1016/j.enconman.2018.11.079