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Optimal Operation of Stand-Alone Microgrid Considering Emission Issues and Demand Response Program Using Whale Optimization Algorithm

Author

Listed:
  • Mehrdad Tahmasebi

    (Department of Electrical Engineering, Ilam Branch, Islamic Azad University, Ilam, Iran)

  • Jagadeesh Pasupuleti

    (Institute of Sustainable Energy, Universiti Tenaga Nasional (The National Energy University), Jalan IKRAM-UNITEN, Kajang 43000, Malaysia)

  • Fatemeh Mohamadian

    (Electronic Instructor, Technical and Vocational Training Organization, Tehran 1345653868, Iran)

  • Mohammad Shakeri

    (Institute of Sustainable Energy, Universiti Tenaga Nasional (The National Energy University), Jalan IKRAM-UNITEN, Kajang 43000, Malaysia)

  • Josep M. Guerrero

    (Center for Research on Microgrids (CROM), Department of Energy Technology, Aalborg University, 9220 Aalborg East, Denmark)

  • M. Reyasudin Basir Khan

    (School of Engineering, Manipal International University, No. 1, Persiaran MIU, Nilai 71800, Malaysia)

  • Muhammad Shahzad Nazir

    (Faculty of Automation, Huaiyin Institute of Technology, Huai’an 223003, China)

  • Amir Safari

    (Faculty of Technology & Natural Sciences, University of South-Eastern Norway, USN, 3616 Kongsberg, Norway)

  • Najmeh Bazmohammadi

    (Center for Research on Microgrids (CROM), Department of Energy Technology, Aalborg University, 9220 Aalborg East, Denmark)

Abstract

Microgrids are new technologies for integrating renewable energies into power systems. Optimal operation of renewable energy sources in standalone micro-grids is an intensive task due to the continuous variation of their output powers and intermittant nature. This work addresses the optimum operation of an independent microgrid considering the demand response program (DRP). An energy management model with two different scenarios has been proposed to minimize the costs of operation and emissions. Interruptible/curtailable loads are considered in DRPs. Besides, due to the growing concern of the developing efficient optimization methods and algorithms in line with the increasing needs of microgrids, the focus of this study is on using the whale meta-heuristic algorithm for operation management of microgrids. The findings indicate that the whale optimization algorithm outperforms the other known algorithms such as imperialist competitive and genetic algorithms, as well as particle swarm optimization. Furthermore, the results show that the use of DRPS has a significant impact on the costs of operation and emissions.

Suggested Citation

  • Mehrdad Tahmasebi & Jagadeesh Pasupuleti & Fatemeh Mohamadian & Mohammad Shakeri & Josep M. Guerrero & M. Reyasudin Basir Khan & Muhammad Shahzad Nazir & Amir Safari & Najmeh Bazmohammadi, 2021. "Optimal Operation of Stand-Alone Microgrid Considering Emission Issues and Demand Response Program Using Whale Optimization Algorithm," Sustainability, MDPI, vol. 13(14), pages 1-22, July.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:14:p:7710-:d:591777
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    References listed on IDEAS

    as
    1. 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.
    2. Tabar, Vahid Sohrabi & Ghassemzadeh, Saeid & Tohidi, Sajjad, 2019. "Energy management in hybrid microgrid with considering multiple power market and real time demand response," Energy, Elsevier, vol. 174(C), pages 10-23.
    3. Nikmehr, Nima & Najafi-Ravadanegh, Sajad & Khodaei, Amin, 2017. "Probabilistic optimal scheduling of networked microgrids considering time-based demand response programs under uncertainty," Applied Energy, Elsevier, vol. 198(C), pages 267-279.
    4. Lorestani, Alireza & Gharehpetian, G.B. & Nazari, Mohammad Hassan, 2019. "Optimal sizing and techno-economic analysis of energy- and cost-efficient standalone multi-carrier microgrid," Energy, Elsevier, vol. 178(C), pages 751-764.
    5. Karimi, Hamid & Jadid, Shahram, 2019. "Optimal microgrid operation scheduling by a novel hybrid multi-objective and multi-attribute decision-making framework," Energy, Elsevier, vol. 186(C).
    6. Aghajani, G.R. & Shayanfar, H.A. & Shayeghi, H., 2017. "Demand side management in a smart micro-grid in the presence of renewable generation and demand response," Energy, Elsevier, vol. 126(C), pages 622-637.
    7. Ghadi, M. Jabbari & Ghavidel, Sahand & Rajabi, Amin & Azizivahed, Ali & Li, Li & Zhang, Jiangfeng, 2019. "A review on economic and technical operation of active distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 38-53.
    8. 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.
    9. McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
    10. Adefarati, T. & Bansal, R.C., 2019. "Reliability, economic and environmental analysis of a microgrid system in the presence of renewable energy resources," Applied Energy, Elsevier, vol. 236(C), pages 1089-1114.
    11. Fatin Ishraque, Md. & Shezan, Sk. A. & Ali, M.M. & Rashid, M.M., 2021. "Optimization of load dispatch strategies for an islanded microgrid connected with renewable energy sources," Applied Energy, Elsevier, vol. 292(C).
    12. Rabiee, Abdorreza & Sadeghi, Mohammad & Aghaeic, Jamshid & Heidari, Alireza, 2016. "Optimal operation of microgrids through simultaneous scheduling of electrical vehicles and responsive loads considering wind and PV units uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 721-739.
    13. Kwon, Kyung-bin & Kim, Dam, 2020. "Enhanced method for considering energy storage systems as ancillary service resources in stochastic unit commitment," Energy, Elsevier, vol. 213(C).
    14. Mohamed El-Hendawi & Hossam A. Gabbar & Gaber El-Saady & El-Nobi A. Ibrahim, 2018. "Control and EMS of a Grid-Connected Microgrid with Economical Analysis," Energies, MDPI, vol. 11(1), pages 1-20, January.
    15. Roslan, M.F. & Hannan, M.A. & Jern Ker, Pin & Begum, R.A. & Indra Mahlia, TM & Dong, Z.Y., 2021. "Scheduling controller for microgrids energy management system using optimization algorithm in achieving cost saving and emission reduction," Applied Energy, Elsevier, vol. 292(C).
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    1. Mostafa Darvishi & Mehrdad Tahmasebi & Ehsan Shokouhmand & Jagadeesh Pasupuleti & Pitshou Bokoro & Jwan Satei Raafat, 2023. "Optimal Operation of Sustainable Virtual Power Plant Considering the Amount of Emission in the Presence of Renewable Energy Sources and Demand Response," Sustainability, MDPI, vol. 15(14), pages 1-25, July.
    2. Muhammad Shahzad Nazir & Ahmed N. Abdalla & Ahmed Sayed M. Metwally & Muhammad Imran & Patrizia Bocchetta & Muhammad Sufyan Javed, 2022. "Cryogenic-Energy-Storage-Based Optimized Green Growth of an Integrated and Sustainable Energy System," Sustainability, MDPI, vol. 14(9), pages 1-18, April.

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