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An Optimized Control Method of an Energy Source Renewable with Integrated Storage Source for Smart Home

  • Alae LabriniEmail author
  • Nabila Rabbah
  • Hicham Belhaddoui
  • Mounir Rifi
Conference paper
Part of the Lecture Notes in Intelligent Transportation and Infrastructure book series (LNITI)

Abstract

The optimal control of the distribution of the electrical energy in a hybrid multi-source/multi-load system with a storage system, is an alternative method to the future smart cities, especially in areas where the deployment of a traditional electricity grid is expensive. In this article the main objective is to manage the power distribution of the hybrid power generation system for a smart home, based on the renewable source (Fuel Cell) and a storage system. In this context the contribution envisaged with this work is to contribute to the modeling and optimization of a multi-source system to power a smart home. The presence of such a multi-source system requires a modeling and management approach by a control strategy, for this an optimal control strategy to determine the energy distribution between the source and the load, by satisfying certain constraints such as the State of Charge, the storage system and the consumption of hydrogen is necessary. To ensure the optimal functioning of our system, two energy management strategies have been developed: the Equivalent Consumption Minimization Strategy (ECMS) and the state machine method. The simulation results show in MATLAB/Simulink the performance in terms of hydrogen consumption, State of Charge (SoC) of the system’s battery and simulation time.

Keywords

Hydrogen Fuel cell (FC) State of charge (SoC) Energy consumption minimization strategy (ECMS) State machine strategy (SMS) 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alae Labrini
    • 1
    Email author
  • Nabila Rabbah
    • 2
  • Hicham Belhaddoui
    • 1
  • Mounir Rifi
    • 1
  1. 1.RITM Laboratory, CED Science de l’Ingénieur ENSEMHassan II University CasablancaCasablancaMorocco
  2. 2.Laboratory of Structural Engineering, Intelligent Systems and Electrical Energy, ENSAMHassan II University CasablancaCasablancaMorocco

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