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Optimal Scheduling of Hybrid Energy Resources for a Smart Home

Author

Listed:
  • Muhammad Kashif Rafique

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea)

  • Zunaib Maqsood Haider

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea)

  • Khawaja Khalid Mehmood

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea)

  • Muhammad Saeed Uz Zaman

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea)

  • Muhammad Irfan

    (Department of Electrical Engineering, Khwaja Fareed University of Engineering and Information Technology (KFUEIT), Rahim Yar Khan 64200, Pakistan)

  • Saad Ullah Khan

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea)

  • Chul-Hwan Kim

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea)

Abstract

The present environmental and economic conditions call for the increased use of hybrid energy resources and, concurrently, recent developments in combined heat and power (CHP) systems enable their use at a domestic level. In this work, the optimal scheduling of electric and gas energy resources is achieved for a smart home (SH) which is equipped with a fuel cell-based micro-CHP system. The SH energy system has thermal and electrical loops that contain an auxiliary boiler, a battery energy storage system, and an electrical vehicle besides other typical loads. The optimal operational cost of the SH is achieved using the real coded genetic algorithm (RCGA) under various scenarios of utility tariff and availability of hybrid energy resources. The results compare different scenarios and point-out the conditions for economic operation of micro-CHP and hybrid energy systems for an SH.

Suggested Citation

  • Muhammad Kashif Rafique & Zunaib Maqsood Haider & Khawaja Khalid Mehmood & Muhammad Saeed Uz Zaman & Muhammad Irfan & Saad Ullah Khan & Chul-Hwan Kim, 2018. "Optimal Scheduling of Hybrid Energy Resources for a Smart Home," Energies, MDPI, vol. 11(11), pages 1-19, November.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3201-:d:183714
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    References listed on IDEAS

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    Cited by:

    1. Pavić, Ivan & Čović, Nikolina & Pandžić, Hrvoje, 2022. "PV–battery-hydrogen plant: Cutting green hydrogen costs through multi-market positioning," Applied Energy, Elsevier, vol. 328(C).
    2. Lucrezia Manservigi & Mattia Cattozzo & Pier Ruggero Spina & Mauro Venturini & Hilal Bahlawan, 2020. "Optimal Management of the Energy Flows of Interconnected Residential Users," Energies, MDPI, vol. 13(6), pages 1-21, March.
    3. Isaías Gomes & Karol Bot & Maria Graça Ruano & António Ruano, 2022. "Recent Techniques Used in Home Energy Management Systems: A Review," Energies, MDPI, vol. 15(8), pages 1-41, April.
    4. Ghayour, Sepideh Saravani & Barforoushi, Taghi, 2022. "Optimal scheduling of electrical and thermal resources and appliances in a smart home under uncertainty," Energy, Elsevier, vol. 261(PA).
    5. Muhammad Faisal Shehzad & Mainak Dan & Valerio Mariani & Seshadhri Srinivasan & Davide Liuzza & Carmine Mongiello & Roberto Saraceno & Luigi Glielmo, 2021. "A Heuristic Algorithm for Combined Heat and Power System Operation Management," Energies, MDPI, vol. 14(6), pages 1-22, March.
    6. Nicu Bizon & Mihai Oproescu, 2018. "Experimental Comparison of Three Real-Time Optimization Strategies Applied to Renewable/FC-Based Hybrid Power Systems Based on Load-Following Control," Energies, MDPI, vol. 11(12), pages 1-32, December.
    7. Nicu Bizon & Valentin Alexandru Stan & Angel Ciprian Cormos, 2019. "Optimization of the Fuel Cell Renewable Hybrid Power System Using the Control Mode of the Required Load Power on the DC Bus," Energies, MDPI, vol. 12(10), pages 1-15, May.

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