Adaptive robust control-based energy management of hybrid PV-Battery systems with improved transient performance

Hadi Taghavifar, Hamid Taghavifar

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


Energy management of hybrid photovoltaic (PV)-battery systems still serve as a challenging task owing to their complex and nonlinear characteristics, multicomponent structures, and the extensive range of environmental factors disturbing their nominal performance. The hybrid energy system developed in this study encompasses PV arrays, a battery component, one boost converter, and one bidirectional boost converter. In this paper, we propose a novel adaptive robust control framework for the optimal energy management of the PV-battery systems under many operating conditions and subject to unmodelled dynamics. An improved exponential-like adaptive integral sliding mode (EISM) control coupled to neural network approximator is introduced using a multi-rate convergence tweaking mechanism for the sliding surface to improve the transient performance of the closed-loop system. Furthermore, the entire dynamics of the hybrid energy system is considered unknown, unlike the previous studies that only assumed the parametric uncertainties. The global asymptotic stability of the system is guaranteed, and the effectiveness of this novel framework is compared to benchmark studies.

Original languageEnglish
Pages (from-to)7442-7453
Number of pages12
JournalInternational Journal of Hydrogen Energy
Issue number10
Early online date30 Dec 2020
Publication statusPublished - 8 Feb 2021

Bibliographical note

Publisher Copyright:
© 2020 Hydrogen Energy Publications LLC

Copyright 2021 Elsevier B.V., All rights reserved.


  • Energy management
  • Hybrid power systems
  • Photovoltaic systems

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Condensed Matter Physics
  • Energy Engineering and Power Technology


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