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An Optimized and Decentralized Energy Provision System for Smart Cities

Author

Listed:
  • Ayusee Swain

    (Department of Railroad and Electrical Engineering, Woosong University, Daejeon 34606, Korea)

  • Surender Reddy Salkuti

    (Department of Railroad and Electrical Engineering, Woosong University, Daejeon 34606, Korea)

  • Kaliprasanna Swain

    (Department of Electronics and Communication Engineering, Gandhi Institute of Technological Advancement, Bhubaneswar 752054, India)

Abstract

Energy efficiency and data security of smart grids are one of the major concerns in the context of implementing modern approaches in smart cities. For the intelligent management of energy systems, wireless sensor networks and advanced metering infrastructures have played an essential role in the transformation of traditional cities into smart communities. In this paper, a smart city energy model is proposed in which prosumer communities were built by interconnecting energy self-sufficient households to generate, consume and share clean energy on a decentralized trading platform by integrating blockchain technology with a smart microgrid. The efficiency and stability of the grid network were improved by using several wireless sensor nodes that manage a massive amount of data in the network. However, long communication distances between sensor nodes and the base station can greatly consume the energy of sensors and decrease the network lifespan. Therefore, bio-inspired algorithm approaches were proposed to improve routing by obtaining the shortest path for traversing the entire network and increasing the system performance in terms of the efficient selection of cluster heads, reduced energy consumption, and extended network lifetime. This was carried out by studying the properties and mechanisms of biological systems and applying them in the communication systems in order to obtain the best results for a specific problem. In this comprehensive model, particle swarm optimization and a genetic algorithm are used to search for the optimal solution in any problem space in less processing time.

Suggested Citation

  • Ayusee Swain & Surender Reddy Salkuti & Kaliprasanna Swain, 2021. "An Optimized and Decentralized Energy Provision System for Smart Cities," Energies, MDPI, vol. 14(5), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:5:p:1451-:d:512156
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Abhirup Khanna & Anushree Sah & Vadim Bolshev & Michal Jasinski & Alexander Vinogradov & Zbigniew Leonowicz & Marek Jasiński, 2021. "Blockchain: Future of e-Governance in Smart Cities," Sustainability, MDPI, vol. 13(21), pages 1-21, October.
    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.
    3. Mohammad Hossein Fouladfar & Nagham Saeed & Mousa Marzband & Giuseppe Franchini, 2021. "Home-Microgrid Energy Management Strategy Considering EV’s Participation in DR," Energies, MDPI, vol. 14(18), pages 1-12, September.
    4. Tatiana Tucunduva Philippi Cortese & Jairo Filho Sousa de Almeida & Giseli Quirino Batista & José Eduardo Storopoli & Aaron Liu & Tan Yigitcanlar, 2022. "Understanding Sustainable Energy in the Context of Smart Cities: A PRISMA Review," Energies, MDPI, vol. 15(7), pages 1-38, March.
    5. Salil Madhav Dubey & Hari Mohan Dubey & Manjaree Pandit & Surender Reddy Salkuti, 2021. "Multiobjective Scheduling of Hybrid Renewable Energy System Using Equilibrium Optimization," Energies, MDPI, vol. 14(19), pages 1-20, October.
    6. Liang Zhong & Shizhong Zhang & Yidu Zhang & Guang Chen & Yong Liu, 2021. "Joint Acquisition Time Design and Sensor Association for Wireless Sensor Networks in Microgrids," Energies, MDPI, vol. 14(22), pages 1-18, November.
    7. Surender Reddy Salkuti, 2022. "Emerging and Advanced Green Energy Technologies for Sustainable and Resilient Future Grid," Energies, MDPI, vol. 15(18), pages 1-7, September.

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