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Soft Computing in Smart Grid with Decentralized Generation and Renewable Energy Storage System Planning

Author

Listed:
  • Rasheed Abdulkader

    (Electrical Engineering Department, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11564, Saudi Arabia)

  • Hayder M. A. Ghanimi

    (Biomedical Engineering Department, College of Engineering, University of Warith Al-Anbiyaa, Karbala 56001, Iraq)

  • Pankaj Dadheech

    (Department of Computer Science & Engineering, Swami Keshvan and Institute of Technology, Management & Gramothan (SKIT), Jaipur 302017, Rajasthan, India)

  • Meshal Alharbi

    (Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Alkharj 11942, Saudi Arabia)

  • Walid El-Shafai

    (Security Engineering Lab, Computer Science Department, Prince Sultan University, Riyadh 11586, Saudi Arabia
    Department of Electronics and Electrical Communications Engineering, Faculty of Electronic Engineering, Menoufia University, Menouf 32952, Egypt)

  • Mostafa M. Fouda

    (Department of Electrical and Computer Engineering, College of Science and Engineering, Idaho State University, Pocatello, ID 83209, USA)

  • Moustafa H. Aly

    (Electronics and Communications Engineering Department, College of Engineering and Technology, Arab Academy for Science, Technology and Maritime Transport, Alexandria 21500, Egypt)

  • Dhivya Swaminathan

    (School of Electrical Engineering, Vellore Institute of Technology, Chennai 600127, Tamil Nadu, India)

  • Sudhakar Sengan

    (Department of Computer Science and Engineering, PSN College of Engineering and Technology, Tirunelveli 627152, Tamil Nadu, India)

Abstract

Distributed Power Generation and Energy Storage Systems (DPG-ESSs) are crucial to securing a local energy source. Both entities could enhance the operation of Smart Grids (SGs) by reducing Power Loss (PL), maintaining the voltage profile, and increasing Renewable Energy (RE) as a clean alternative to fossil fuel. However, determining the optimum size and location of different methodologies of DPG-ESS in the SG is essential to obtaining the most benefits and avoiding any negative impacts such as Quality of Power (QoP) and voltage fluctuation issues. This paper’s goal is to conduct comprehensive empirical studies and evaluate the best size and location for DPG-ESS in order to find out what problems it causes for SG modernization. Therefore, this paper presents explicit knowledge of decentralized power generation in SG based on integrating the DPG-ESS in terms of size and location with the help of Metaheuristic Optimization Algorithms (MOAs). This research also reviews rationalized cost-benefit considerations such as reliability, sensitivity, and security studies for Distribution Network (DN) planning. In order to determine results, various proposed works with algorithms and objectives are discussed. Other soft computing methods are also defined, and a comparison is drawn between many approaches adopted in DN planning.

Suggested Citation

  • Rasheed Abdulkader & Hayder M. A. Ghanimi & Pankaj Dadheech & Meshal Alharbi & Walid El-Shafai & Mostafa M. Fouda & Moustafa H. Aly & Dhivya Swaminathan & Sudhakar Sengan, 2023. "Soft Computing in Smart Grid with Decentralized Generation and Renewable Energy Storage System Planning," Energies, MDPI, vol. 16(6), pages 1-24, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2655-:d:1094716
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    References listed on IDEAS

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    2. Łukasz Mazur & Sławomir Cieślik & Stanislaw Czapp, 2023. "Trends in Locally Balanced Energy Systems without the Use of Fossil Fuels: A Review," Energies, MDPI, vol. 16(12), pages 1-31, June.
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    4. Gao, Jinling & Maalla, Allam & Li, Xuetao & Zhou, Xiao & Lian, Kong, 2024. "Comprehensive model for efficient microgrid operation: Addressing uncertainties and economic considerations," Energy, Elsevier, vol. 306(C).

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