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Probabilistic energy management with emission of renewable micro-grids including storage devices based on efficient salp swarm algorithm

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  • Elattar, Ehab E.
  • ElSayed, Salah K.

Abstract

In this paper, the efficient salp swarm algorithm (ESSA) is proposed to solve the energy management (EM) with emission problem of renewable micro-grid (MG) including storage devices. Because of the uncertainties in the renewable energy sources (RESs), load demand and market prices, the probabilistic approach based on (2m + 1) point estimate method and ESSA is employed to solve the probabilistic EM problem. The proposed ESSA can be derived by introducing two modifications on the conventional salp swarm algorithm (SSA) to improve the balance between exploration and exploitation, speed up the convergence and avoiding the stuck in local optima of the SSA. The ESSA is employed to solve the deterministic and probabilistic EM with emission problem. Where the multi-objective optimization problem of cost and emission functions is transferred into a single objective function to minimize the total operating cost of the MG. The proposed ESSA is evaluated using a typical grid-connected MG with energy storage devices and compared with other methods. The results verify the superiority of the ESSA to solve the EM problem of the MG over other methods.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:renene:v:153:y:2020:i:c:p:23-35
    DOI: 10.1016/j.renene.2020.01.144
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    1. Hossain, Md Alamgir & Pota, Hemanshu Roy & Squartini, Stefano & Abdou, Ahmed Fathi, 2019. "Modified PSO algorithm for real-time energy management in grid-connected microgrids," Renewable Energy, Elsevier, vol. 136(C), pages 746-757.
    2. Moradi, Hadis & Esfahanian, Mahdi & Abtahi, Amir & Zilouchian, Ali, 2018. "Optimization and energy management of a standalone hybrid microgrid in the presence of battery storage system," Energy, Elsevier, vol. 147(C), pages 226-238.
    3. Niknam, Taher & Golestaneh, Faranak & Malekpour, Ahmadreza, 2012. "Probabilistic energy and operation management of a microgrid containing wind/photovoltaic/fuel cell generation and energy storage devices based on point estimate method and self-adaptive gravitational," Energy, Elsevier, vol. 43(1), pages 427-437.
    4. 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.
    5. Jiyang Wang & Yuyang Gao & Xuejun Chen, 2018. "A Novel Hybrid Interval Prediction Approach Based on Modified Lower Upper Bound Estimation in Combination with Multi-Objective Salp Swarm Algorithm for Short-Term Load Forecasting," Energies, MDPI, vol. 11(6), pages 1-30, June.
    6. Mellouk, Lamyae & Ghazi, M. & Aaroud, A. & Boulmalf, M. & Benhaddou, D. & Zine-Dine, K., 2019. "Design and energy management optimization for hybrid renewable energy system- case study: Laayoune region," Renewable Energy, Elsevier, vol. 139(C), pages 621-634.
    7. Elattar, Ehab E., 2019. "Environmental economic dispatch with heat optimization in the presence of renewable energy based on modified shuffle frog leaping algorithm," Energy, Elsevier, vol. 171(C), pages 256-269.
    8. Jafari, Mohammad & Malekjamshidi, Zahra, 2020. "Optimal energy management of a residential-based hybrid renewable energy system using rule-based real-time control and 2D dynamic programming optimization method," Renewable Energy, Elsevier, vol. 146(C), pages 254-266.
    9. El-Fergany, Attia A., 2018. "Extracting optimal parameters of PEM fuel cells using Salp Swarm Optimizer," Renewable Energy, Elsevier, vol. 119(C), pages 641-648.
    10. Mohammadi, Sirus & Mozafari, Babak & Solimani, Soodabeh & Niknam, Taher, 2013. "An Adaptive Modified Firefly Optimisation Algorithm based on Hong's Point Estimate Method to optimal operation management in a microgrid with consideration of uncertainties," Energy, Elsevier, vol. 51(C), pages 339-348.
    11. 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.
    12. Elattar, Ehab E. & ElSayed, Salah K., 2019. "Modified JAYA algorithm for optimal power flow incorporating renewable energy sources considering the cost, emission, power loss and voltage profile improvement," Energy, Elsevier, vol. 178(C), pages 598-609.
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    3. Lin, Xing-Min & Kireeva, Natalia & Timoshin, A.V. & Naderipour, Amirreza & Abdul-Malek, Zulkurnain & Kamyab, Hesam, 2021. "A multi-criteria framework for designing of stand-alone and grid-connected photovoltaic, wind, battery clean energy system considering reliability and economic assessment," Energy, Elsevier, vol. 224(C).
    4. Salah K. ElSayed & Ehab E. Elattar, 2021. "Slime Mold Algorithm for Optimal Reactive Power Dispatch Combining with Renewable Energy Sources," Sustainability, MDPI, vol. 13(11), pages 1-25, 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.
    6. Phani Raghav, L. & Seshu Kumar, R. & Koteswara Raju, D. & Singh, Arvind R., 2022. "Analytic Hierarchy Process (AHP) – Swarm intelligence based flexible demand response management of grid-connected microgrid," Applied Energy, Elsevier, vol. 306(PB).

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