4.7 Article

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

期刊

ENERGY CONVERSION AND MANAGEMENT
卷 181, 期 -, 页码 80-92

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.enconman.2018.11.079

关键词

Hybrid energy system; Retired EV battery; Multi-objective optimization; NSGA-II; MOEA/D

资金

  1. National Key Research and Development Program [2018YFB0105402, 2018YFB0105703]
  2. National Nature Science Foundation of China [51806024]
  3. Chongqing Research Program of Foundation and Advanced Technology [cstc2017jcyjAX0276]
  4. Fundamental Research Funds for the Central Universities [106112017CDJPT280005, 106112017CDJQJ338812, 106112016CDJXZ338825, 2018CDXYTW0031]

向作者/读者索取更多资源

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 REVS 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 REVS 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.

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