Modeling and multi-objective optimization of a stand-alone PV-hydrogen- retired EV battery hybrid energy system
Huang Zhiyu , Zhilong Xie , Caizhi Zhang , Siew Hwa Chan , Jarosław Milewski , Yi Xie , Yang Yalian , Hu Xiaosong
AbstractReusing 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 con- tributions. 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 in- dicator, 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.
|Journal series||Energy Conversion and Management, ISSN 0196-8904|
|Publication size in sheets||0.6|
|Keywords in English||Hybrid energy systemRetired EV batteryMulti-objective optimizationNSGA-IIMOEA/D|
|ASJC Classification||; ; ;|
|Score||= 200.0, 10-03-2020, ArticleFromJournal|
|Publication indicators||= 8; : 2018 = 2.151; : 2018 = 7.181 (2) - 2018=6.722 (5)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.