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Smart Energy Management System of Environmentally Friendly Microgrid Based on Grasshopper Optimization Technique

Author

Listed:
  • Yehia Gad

    (Department of Electrical Energy Engineering, Arab Academy for Science, Technology and Maritime Transport, Cairo 12577, Egypt)

  • Hatem Diab

    (Department of Electrical Energy Engineering, Arab Academy for Science, Technology and Maritime Transport, Cairo 12577, Egypt)

  • Mahmoud Abdelsalam

    (Department of Electrical Energy Engineering, Arab Academy for Science, Technology and Maritime Transport, Cairo 12577, Egypt)

  • Yasser Galal

    (Department of Electrical and Control Engineering, Arab Academy for Science, Technology and Maritime Transport, Cairo 11799, Egypt)

Abstract

A microgrid is a group of distributed energy resources and interconnected loads that may be operated either in isolated mode or connected mode with the main utility within electrical boundaries. Microgrids may consist of different types of renewable energy resources such as photovoltaic panels, wind turbines, fuel cells, micro turbines, and storage units. It is highly recommended to manage the dependency on these resources by implementing an energy management unit to optimize the energy exchange so that the minimum cost is achieved. In this paper, an energy management system based on the grasshopper optimization algorithm (GOA) is proposed to determine the optimal power generated by the distributed generators in the microgrid which is required to minimize the total generation cost. The proposed unit is applied to a microgrid that consists of five generating units feeding residential, commercial, and industrial loads, and results are compared to other available research in literature to validate the proposed algorithm.

Suggested Citation

  • Yehia Gad & Hatem Diab & Mahmoud Abdelsalam & Yasser Galal, 2020. "Smart Energy Management System of Environmentally Friendly Microgrid Based on Grasshopper Optimization Technique," Energies, MDPI, vol. 13(19), pages 1-22, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5000-:d:418054
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    References listed on IDEAS

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    Cited by:

    1. Arul Rajagopalan & Karthik Nagarajan & Oscar Danilo Montoya & Seshathiri Dhanasekaran & Inayathullah Abdul Kareem & Angalaeswari Sendraya Perumal & Natrayan Lakshmaiya & Prabhu Paramasivam, 2022. "Multi-Objective Optimal Scheduling of a Microgrid Using Oppositional Gradient-Based Grey Wolf Optimizer," Energies, MDPI, vol. 15(23), pages 1-24, November.
    2. Naser Hossein Motlagh & Ali Khatibi & Alireza Aslani, 2020. "Toward Sustainable Energy-Independent Buildings Using Internet of Things," Energies, MDPI, vol. 13(22), pages 1-17, November.
    3. Hatem Diab & Mahmoud Abdelsalam & Alaa Abdelbary, 2021. "A Multi-Objective Optimal Power Flow Control of Electrical Transmission Networks Using Intelligent Meta-Heuristic Optimization Techniques," Sustainability, MDPI, vol. 13(9), pages 1-25, April.
    4. Mahmoud M. Gamil & Soichirou Ueda & Akito Nakadomari & Keifa Vamba Konneh & Tomonobu Senjyu & Ashraf M. Hemeida & Mohammed Elsayed Lotfy, 2022. "Optimal Multi-Objective Power Scheduling of a Residential Microgrid Considering Renewable Sources and Demand Response Technique," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    5. Dariusz Tarnapowicz & Sergey German-Galkin & Arkadiusz Nerc & Marek Jaskiewicz, 2023. "Improving the Energy Efficiency of a Ship’s Power Plant by Using an Autonomous Hybrid System with a PMSG," Energies, MDPI, vol. 16(7), pages 1-19, March.

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