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

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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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    1. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Kendall, Alissa & Træholt, Chresten, 2018. "Optimization of a biomass-integrated renewable energy microgrid with demand side management under uncertainty," Applied Energy, Elsevier, vol. 230(C), pages 836-844.
    2. Anvari-Moghaddam, Amjad & Rahimi-Kian, Ashkan & Mirian, Maryam S. & Guerrero, Josep M., 2017. "A multi-agent based energy management solution for integrated buildings and microgrid system," Applied Energy, Elsevier, vol. 203(C), pages 41-56.
    3. Wei Fan & Nian Liu & Jianhua Zhang, 2016. "An Event-Triggered Online Energy Management Algorithm of Smart Home: Lyapunov Optimization Approach," Energies, MDPI, vol. 9(5), pages 1-24, May.
    4. Fahad R. Albogamy & Sajjad Ali Khan & Ghulam Hafeez & Sadia Murawwat & Sheraz Khan & Syed Irtaza Haider & Abdul Basit & Klaus-Dieter Thoben, 2022. "Real-Time Energy Management and Load Scheduling with Renewable Energy Integration in Smart Grid," Sustainability, MDPI, vol. 14(3), pages 1-28, February.
    5. Ullah, Kalim & Hafeez, Ghulam & Khan, Imran & Jan, Sadaqat & Javaid, Nadeem, 2021. "A multi-objective energy optimization in smart grid with high penetration of renewable energy sources," Applied Energy, Elsevier, vol. 299(C).
    6. Bhatti, Abdul Rauf & Salam, Zainal, 2018. "A rule-based energy management scheme for uninterrupted electric vehicles charging at constant price using photovoltaic-grid system," Renewable Energy, Elsevier, vol. 125(C), pages 384-400.
    7. Jianwei Gao & Yu Yang & Fangjie Gao & Haoyu Wu, 2022. "Two-Stage Robust Economic Dispatch of Regional Integrated Energy System Considering Source-Load Uncertainty Based on Carbon Neutral Vision," Energies, MDPI, vol. 15(4), pages 1-16, February.
    8. Hu, Jie & Liu, Di & Du, Changqing & Yan, Fuwu & Lv, Chen, 2020. "Intelligent energy management strategy of hybrid energy storage system for electric vehicle based on driving pattern recognition," Energy, Elsevier, vol. 198(C).
    9. Ma, Tao & Yang, Hongxing & Lu, Lin, 2014. "A feasibility study of a stand-alone hybrid solar–wind–battery system for a remote island," Applied Energy, Elsevier, vol. 121(C), pages 149-158.
    10. Xia, Yuanxing & Xu, Qingshan & Tao, Siyu & Du, Pengwei & Ding, Yixing & Fang, Jicheng, 2022. "Preserving operation privacy of peer-to-peer energy transaction based on Enhanced Benders Decomposition considering uncertainty of renewable energy generations," Energy, Elsevier, vol. 250(C).
    11. Ahmad, Ashfaq & Khan, Jamil Yusuf, 2020. "Real-Time Load Scheduling, Energy Storage Control and Comfort Management for Grid-Connected Solar Integrated Smart Buildings," Applied Energy, Elsevier, vol. 259(C).
    12. Delgarm, N. & Sajadi, B. & Kowsary, F. & Delgarm, S., 2016. "Multi-objective optimization of the building energy performance: A simulation-based approach by means of particle swarm optimization (PSO)," Applied Energy, Elsevier, vol. 170(C), pages 293-303.
    13. Guo, Chenyu & Wang, Xin & Zheng, Yihui & Zhang, Feng, 2022. "Real-time optimal energy management of microgrid with uncertainties based on deep reinforcement learning," Energy, Elsevier, vol. 238(PC).
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    Cited by:

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    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. Dong, Fuxiang & Wang, Jiangjiang & Xu, Hangwei & Zhang, Xutao, 2024. "A robust real-time energy scheduling strategy of integrated energy system based on multi-step interval prediction of uncertainties," Energy, Elsevier, vol. 300(C).
    4. 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.
    5. Yilin Xu & Zeping Hu, 2024. "Source-Grid-Load Cross-Area Coordinated Optimization Model Based on IGDT and Wind-Photovoltaic-Photothermal System," Sustainability, MDPI, vol. 16(5), pages 1-15, March.
    6. Abdellatif Soussi & Enrico Zero & Alessandro Bozzi & Roberto Sacile, 2024. "Enhancing Energy Systems and Rural Communities through a System of Systems Approach: A Comprehensive Review," Energies, MDPI, vol. 17(19), pages 1-43, October.
    7. 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.
    8. Diego Peña & Paul Arevalo & Yadyra Ortiz & Franciso Jurado, 2024. "Survey of Optimization Techniques for Microgrids Using High-Efficiency Converters," Energies, MDPI, vol. 17(15), pages 1-24, July.

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