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Probabilistic Modeling and Equilibrium Optimizer Solving for Energy Management of Renewable Micro-Grids Incorporating Storage Devices

Author

Listed:
  • Salah K. ElSayed

    (Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Sattam Al Otaibi

    (Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Yasser Ahmed

    (Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Essam Hendawi

    (Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Nagy I. Elkalashy

    (Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Ayman Hoballah

    (Department of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

Abstract

Recently, micro-grids (MGs) have had a great impact on power system issues due to their clear environmental and economic advantages. This paper proposes an equilibrium optimizer (EO) technique for solving the energy management problem of MGs incorporating energy storage devices concerning the emissions from renewable energy sources (RES) of MGs. Because of the imprecision and uncertainties related to the RESs, market prices, and forecast load demand, the optimization problem is described in a probabilistic manner using a 2m + 1 point estimation approach. Then, the EO approach is utilized for solving the probabilistic energy management (EM) problem. The EM problem is described according to the market policy on the basis of minimizing the total operating cost and emission from RESs through optimal settings of the power generated from distributed generators (DGs) and grids connected under the condition of satisfying the operational constraints of the system. The proposed EO is evaluated based on a grid-connected MG that includes energy storage devices. Moreover, to prove the effectiveness of the EO, it is compared with other recently meta-heuristic techniques. The simulation results show acceptable robustness of the EO for solving the EM problem as compared to other techniques.

Suggested Citation

  • Salah K. ElSayed & Sattam Al Otaibi & Yasser Ahmed & Essam Hendawi & Nagy I. Elkalashy & Ayman Hoballah, 2021. "Probabilistic Modeling and Equilibrium Optimizer Solving for Energy Management of Renewable Micro-Grids Incorporating Storage Devices," Energies, MDPI, vol. 14(5), pages 1-24, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:5:p:1373-:d:509375
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    References listed on IDEAS

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