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Design and Development of Optimal and Deep-Learning-Based Demand Response Technologies for Residential Hybrid Renewable Energy Management System

Author

Listed:
  • Murugaperumal Krishnamoorthy

    (Department of EEE, Vardhaman College of Engineering, Hyderabad 501218, India)

  • P. Ajay-D-Vimal Raj

    (Department of EEE, Puducherry Technological University, Puducherry 605014, India)

  • N. P. Subramaniam

    (Department of EEE, Puducherry Technological University, Puducherry 605014, India)

  • M. Sudhakaran

    (Department of EEE, Puducherry Technological University, Puducherry 605014, India)

  • Arulselvi Ramasamy

    (Department of CSE, Vardhaman College of Engineering, Hyderabad 501218, India)

Abstract

The principal goal of this study is to conduct a techno-economic analysis of hybrid energy generation designs for residential-form houses in urban areas. Various possibilities for a form house electrification system are created and simulated in order to determine an optimum ideal configuration for meeting residential load demand with an increase in energy capacity and minimal investment. Using NREL’s HOMER optimization tool, a case-study-based virtual HRE model is developed. Pre-assessment data and relevant operation constraints are used to build the system’s objective functions. The instantaneous energy balance algorithm technique is used to solve the multi-objective function. The overall optimization procedure is sandwiched between two supporting advanced approaches, pre- and post-operations. The development of an optimal techno-economic hybrid energy generation system for the smooth fulfillment of urban load demand is aided by novel deep belief network (NDBN)-based pre-stage load demand predictions and an analysis of the necessary demand side management (DSM)practicing code for utility efficiency improvements in post-stage simulations.

Suggested Citation

  • Murugaperumal Krishnamoorthy & P. Ajay-D-Vimal Raj & N. P. Subramaniam & M. Sudhakaran & Arulselvi Ramasamy, 2023. "Design and Development of Optimal and Deep-Learning-Based Demand Response Technologies for Residential Hybrid Renewable Energy Management System," Sustainability, MDPI, vol. 15(18), pages 1-26, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13773-:d:1240684
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    References listed on IDEAS

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    1. Cuesta, M.A. & Castillo-Calzadilla, T. & Borges, C.E., 2020. "A critical analysis on hybrid renewable energy modeling tools: An emerging opportunity to include social indicators to optimise systems in small communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 122(C).
    2. Javed, Muhammad Shahzad & Zhong, Dan & Ma, Tao & Song, Aotian & Ahmed, Salman, 2020. "Hybrid pumped hydro and battery storage for renewable energy based power supply system," Applied Energy, Elsevier, vol. 257(C).
    3. Tiwari, Ramji & Babu, N. Ramesh, 2016. "Recent developments of control strategies for wind energy conversion system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 268-285.
    4. Ramirez Camargo, Luis & Valdes, Javier & Masip Macia, Yunesky & Dorner, Wolfgang, 2019. "Assessment of on-site steady electricity generation from hybrid renewable energy systems in Chile," Applied Energy, Elsevier, vol. 250(C), pages 1548-1558.
    5. Ceran, Bartosz, 2019. "The concept of use of PV/WT/FC hybrid power generation system for smoothing the energy profile of the consumer," Energy, Elsevier, vol. 167(C), pages 853-865.
    6. Kosai, Shoki & Cravioto, Jordi, 2020. "Resilience of standalone hybrid renewable energy systems: The role of storage capacity," Energy, Elsevier, vol. 196(C).
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    Cited by:

    1. Marwan Mahmoud & Sami Ben Slama, 2024. "Deep Learning-Based Home Energy Management Incorporating Vehicle-to-Home and Home-to-Vehicle Technologies for Renewable Integration," Energies, MDPI, vol. 18(1), pages 1-24, December.

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