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Stochastic energy management of renewable micro-grids in the correlated environment using unscented transformation

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  • Tabatabaee, Sajad
  • Mortazavi, Seyed Saeedallah
  • Niknam, Taher

Abstract

This paper addresses the optimal stochastic scheduling of the distributed generation units in a micro-grid. In this way, it introduces a new sufficient stochastic framework to model the correlated uncertainties in the micro-grid that includes different types of RESs such as photovoltaics, wind turbines, micro-turbine, fuel cell as well as battery as the storage device. The proposed stochastic method makes use of unscented transforms to model correlated uncertain parameters. The ability of the unscented transform method to model correlated uncertain variables is particularly appealing in the context of power systems, wherein noticeable inherent correlation exists. Due to the highly complex nature of the problem, a new optimization method based on the harmony search algorithm along with an intelligent modification method is devised to solve the proposed optimization problem, efficiently. The proposed optimization algorithm is equipped with powerful search mechanisms that make it suitable for solving both discrete and continuous problems. In comparison with the original harmony search algorithm, the proposed modified optimization algorithm has few setting parameters. The new modified harmony search algorithm provides proper balance between the local and global searches. The feasibility and satisfactory performance of performance of the proposed method are examined on two typical grid-connected MGs.

Suggested Citation

  • Tabatabaee, Sajad & Mortazavi, Seyed Saeedallah & Niknam, Taher, 2016. "Stochastic energy management of renewable micro-grids in the correlated environment using unscented transformation," Energy, Elsevier, vol. 109(C), pages 365-377.
    • Handle: RePEc:eee:energy:v:109:y:2016:i:c:p:365-377
    DOI: 10.1016/j.energy.2016.04.067
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    References listed on IDEAS

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    1. Hao Liang & Weihua Zhuang, 2014. "Stochastic Modeling and Optimization in a Microgrid: A Survey," Energies, MDPI, vol. 7(4), pages 1-24, March.
    2. Moghaddam, Amjad Anvari & Seifi, Alireza & Niknam, Taher & Alizadeh Pahlavani, Mohammad Reza, 2011. "Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source," Energy, Elsevier, vol. 36(11), pages 6490-6507.
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    4. Kavousi-Fard, Abdollah & Abunasri, Alireza & Zare, Alireza & Hoseinzadeh, Rasool, 2014. "Impact of plug-in hybrid electric vehicles charging demand on the optimal energy management of renewable micro-grids," Energy, Elsevier, vol. 78(C), pages 904-915.
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    Cited by:

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    2. Elattar, Ehab E. & ElSayed, Salah K., 2020. "Probabilistic energy management with emission of renewable micro-grids including storage devices based on efficient salp swarm algorithm," Renewable Energy, Elsevier, vol. 153(C), pages 23-35.
    3. Fu, D.Z. & Zheng, Z.Y. & Shi, H.B. & Xiao, Rui & Huang, G.H. & Li, Y.P., 2017. "A multi-fuel management model for a community-level district heating system under multiple uncertainties," Energy, Elsevier, vol. 128(C), pages 337-356.
    4. Wafa Nafkha-Tayari & Seifeddine Ben Elghali & Ehsan Heydarian-Forushani & Mohamed Benbouzid, 2022. "Virtual Power Plants Optimization Issue: A Comprehensive Review on Methods, Solutions, and Prospects," Energies, MDPI, vol. 15(10), pages 1-20, May.
    5. 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.

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