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Real-time energy optimization and scheduling of buildings integrated with renewable microgrid

Author

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  • Alzahrani, Ahmad
  • Sajjad, Khizar
  • Hafeez, Ghulam
  • Murawwat, Sadia
  • Khan, Sheraz
  • Khan, Farrukh Aslam

Abstract

Real-time energy optimization is essential for effective load scheduling, cost reduction, maintaining demand and supply balance, and ensuring reliable power system operations. However, real-time energy optimization is challenging due to the unpredictable nature of renewable energy sources (RES) and the behavior of electric loads. On this note, a rigid model is required that can deal with this dilemma. Thus, the Lyapunov optimization technique (LOT) emerged as a solution for the real-time energy optimization problem. This work investigates a smart home equipped with inflexible loads (TV, computer, light, etc.), flexible loads (EVs, HVAC, water heaters, etc.), and RES (photovoltaic and wind energy) in a grid-connected mode that ensures energy trading (purchasing and selling of energy). The aim is to optimize total cost, thermal discomfort cost, and batteries and EVs charging/discharging using LOT by real-time energy optimization, which does not require any system parameters to be anticipated. The proposed algorithm employs LOT for four queues to solve the real-time energy optimization problem. Simulations are conducted for different scenarios and varying weather conditions to endorse the effectiveness of the developed real-time energy optimization solution in various aspects of the performance metrics.

Suggested Citation

  • Alzahrani, Ahmad & Sajjad, Khizar & Hafeez, Ghulam & Murawwat, Sadia & Khan, Sheraz & Khan, Farrukh Aslam, 2023. "Real-time energy optimization and scheduling of buildings integrated with renewable microgrid," Applied Energy, Elsevier, vol. 335(C).
    • Handle: RePEc:eee:appene:v:335:y:2023:i:c:s0306261923000041
    DOI: 10.1016/j.apenergy.2023.120640
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    References listed on IDEAS

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    Cited by:

    1. Qiang Wang & Dong Yu & Jinyu Zhou & Chaowu Jin, 2023. "Data Storage Optimization Model Based on Improved Simulated Annealing Algorithm," Sustainability, MDPI, vol. 15(9), pages 1-18, April.
    2. Sulman Shahzad & Muhammad Abbas Abbasi & Hassan Ali & Muhammad Iqbal & Rania Munir & Heybet Kilic, 2023. "Possibilities, Challenges, and Future Opportunities of Microgrids: A Review," Sustainability, MDPI, vol. 15(8), pages 1-28, April.
    3. Muhammad Irfan & Sara Deilami & Shujuan Huang & Binesh Puthen Veettil, 2023. "Rooftop Solar and Electric Vehicle Integration for Smart, Sustainable Homes: A Comprehensive Review," Energies, MDPI, vol. 16(21), pages 1-29, October.
    4. Ahmad Alzahrani & Ghulam Hafeez & Sajjad Ali & Sadia Murawwat & Muhammad Iftikhar Khan & Khalid Rehman & Azher M. Abed, 2023. "Multi-Objective Energy Optimization with Load and Distributed Energy Source Scheduling in the Smart Power Grid," Sustainability, MDPI, vol. 15(13), pages 1-21, June.

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