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Developing an Efficient Framework for Involving Degradation Model of Lithium-ion Battery in Optimization Studies of a Residential Energy Hub

Kheirkhah Rad, Ehsan | 2020

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 53616 (46)
  4. University: Sharif University of Technology
  5. Department: Energy Engineering
  6. Advisor(s): Moeini Aghtaie, Moein
  7. Abstract:
  8. Energy storage systems are expected to play an important role in future renewable-based power systems. Recently, lithium-ion batteries have been attracting considerable attention as alternative energy storage systems due to their advantages. In this study, viability of battery storage systems as large-scale energy storage systems is studied in the context of a residential energy hub. A stochastic optimization problem is proposed for energy management of the energy hub where wind generation and demand are considered uncertain. In order to account for the degradation costs of the battery storage system, a data-driven State-of-health prediction model is developed based on the relevance vector machine. Then, this model is fused with the energy management problem to assimilate the viability of the battery storage system. The results demonstrate that the proposed data-driven model is quite suitable for online applications, and the mean-absolute error is less than 1.5% for all the test batteries. Moreover, the scheduling results show that the expected savings from utilizing a battery storage system over the first year of operation approximately sum up to 16% of the capital costs where only 2.31% of capacity fades
  9. Keywords:
  10. Lithium Ion Batteries ; Energy Storage System ; Energy Hub ; Stochastic Programming ; Energy Dissipation ; Relevance Vector Machine

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