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Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities

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  • Bhagya Nathali Silva

    (School of Computer Science and Engineering, Kyungpook National University, Daegu 41566, Korea)

  • Murad Khan

    (School of Computer Science and Engineering, Kyungpook National University, Daegu 41566, Korea)

  • Kijun Han

    (School of Computer Science and Engineering, Kyungpook National University, Daegu 41566, Korea)

Abstract

The emergence of the Internet of Things (IoT) notion pioneered the implementation of various smart environments. Smart environments intelligibly accommodate inhabitants’ requirements. With rapid resource shrinkage, energy management has recently become an essential concern for all smart environments. Energy management aims to assure ecosystem sustainability, while benefiting both consumers and utility providers. Although energy management emerged as a solution that addresses challenges that arise with increasing energy demand and resource deterioration, further evolution and expansion are hindered due to technological, economical, and social barriers. This review aggregates energy management approaches in smart environments and extensively reviews a variety of recent literature reports on peak load shaving and demand response. Significant benefits and challenges of these energy management strategies were identified through the literature survey. Finally, a critical discussion summarizing trends and opportunities is given as a thread for future research.

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  • Bhagya Nathali Silva & Murad Khan & Kijun Han, 2020. "Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities," Sustainability, MDPI, vol. 12(14), pages 1-23, July.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:14:p:5561-:d:382719
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    4. Lei Zhang & Ying Yang, 2023. "Towards Sustainable Energy Systems Considering Unexpected Sports Event Management: Integrating Machine Learning and Optimization Algorithms," Sustainability, MDPI, vol. 15(9), pages 1-16, April.
    5. Harsh Wardhan Pandey & Ramesh Kumar & Rajib Kumar Mandal, 2023. "Ranking of mitigation strategies for duck curve in Indian active distribution network using MCDM," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(4), pages 1255-1275, August.
    6. Sousa, Joana & Soares, Isabel, 2023. "Benefits and barriers concerning demand response stakeholder value chain: A systematic literature review," Energy, Elsevier, vol. 280(C).
    7. Prina, Matteo Giacomo & Groppi, Daniele & Nastasi, Benedetto & Garcia, Davide Astiaso, 2021. "Bottom-up energy system models applied to sustainable islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    8. Ruben Barreto & Calvin Gonçalves & Luis Gomes & Pedro Faria & Zita Vale, 2022. "Evaluation Metrics to Assess the Most Suitable Energy Community End-Users to Participate in Demand Response," Energies, MDPI, vol. 15(7), pages 1-18, March.
    9. Jelena Končar & Aleksandar Grubor & Radenko Marić & Sonja Vučenović & Goran Vukmirović, 2020. "Setbacks to IoT Implementation in the Function of FMCG Supply Chain Sustainability during COVID-19 Pandemic," Sustainability, MDPI, vol. 12(18), pages 1-21, September.
    10. Aguilar, J. & Garces-Jimenez, A. & R-Moreno, M.D. & García, Rodrigo, 2021. "A systematic literature review on the use of artificial intelligence in energy self-management in smart buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    11. Yasir Basheer & Asad Waqar & Saeed Mian Qaisar & Toqeer Ahmed & Nasim Ullah & Sattam Alotaibi, 2022. "Analyzing the Prospect of Hybrid Energy in the Cement Industry of Pakistan, Using HOMER Pro," Sustainability, MDPI, vol. 14(19), pages 1-24, September.
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