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Research Article | Open Access |

Study of Hybrid Autonomous Power System Modelling Via Multi-Agents Strategy

Author 1: NASRI Sihem Author 2: BEN SLAMA Sami Author 3: ZAFAR Bassam Author 4: CHERIF Adnan
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 8, No. 5 · Published 2017

DOI: https://doi.org/10.14569/IJACSA.2017.080542

Abstract

In this paper, a design of a Hybrid autonomous Power System is proposed and detailed. The studied system integrates several components as solar energy source, Energy Recovery system based on a proton membrane exchange fuel cell system and two energy storage components, namely, (1) Energy Storage based on H2 gas production, and (2) an Ultra-capacitor storage device. The system is controlled through an energy management Unit which aims to ensure the smooth operation system to be against any unexpected fluctuation. The modelling of the system relies on the application of a multi-agent strategy whose good effects on the performance of the system is evaluated and demonstrated by the obtained simulation results. The improvement of the system performance is proved through a comparison with the conventional strategies. The system that relies on multi-agents control approach seems to be more reliable and promising in term of effectiveness and fast response.

Keywords

How to Cite this Article

Sihem, N., Sami, B. S., Bassam, Z., & Adnan, C. (2017). Study of Hybrid Autonomous Power System Modelling Via Multi-Agents Strategy. International Journal of Advanced Computer Science and Applications, 8(5). https://doi.org/10.14569/IJACSA.2017.080542

Sihem, NASRI, et al.. "Study of Hybrid Autonomous Power System Modelling Via Multi-Agents Strategy." International Journal of Advanced Computer Science and Applications, vol. 8, no. 5, 2017, https://doi.org/10.14569/IJACSA.2017.080542.

@article{Sihem2017,
  title     = {Study of Hybrid Autonomous Power System Modelling Via Multi-Agents Strategy},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {5},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {NASRI Sihem and BEN SLAMA Sami and ZAFAR Bassam and CHERIF Adnan},
  doi       = {10.14569/IJACSA.2017.080542},
  url       = {https://doi.org/10.14569/IJACSA.2017.080542}
}

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