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Investigation and Field Measurements for Demand Side Management Control Technique of Smart Air Conditioners located at Residential, Commercial, and Industrial Sites

Author

Listed:
  • Bilal Masood

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Song Guobing

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Jamel Nebhen

    (College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia)

  • Ateeq Ur Rehman

    (Department of Electrical Engineering Government College University, Lahore 54000, Pakistan)

  • Muhammad Naveed Iqbal

    (Department of Electrical Engineering Government College University, Lahore 54000, Pakistan
    Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia)

  • Iftikhar Rasheed

    (Department of Information & Communication Engineering, The Islamia University of Bahawalpur, Bahawalpur 63100, Pakistan)

  • Mohit Bajaj

    (Department of Electrical and Electronics Engineering, National Institute of Technology, Delhi 110040, India)

  • Muhammad Shafiq

    (Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea)

  • Habib Hamam

    (Faculty of Engineering, Uni de Moncton, Moncton, NB E1A3E9, Canada
    International Institute of Technology and Management, Libreville BP1989, Gabon
    Spectrum of Knowledge Production & Skills Development, Sfax 3027, Tunisia
    School of Electrical Engineering, Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa)

Abstract

This paper investigates the response and characteristics of the narrowband power line communication (NB-PLC) technique for the effective control of electric appliances such as smart air conditioners (SACs) for demand side management (DSM) services. The expression for temperature sensitivity by examining the influence of atmospheric temperature variations on power consumption profile of all possible types of loads, i.e., residential, commercial, and industrial loads is derived and analyzed. Comprehensive field measurements on these power consumers are carried out in Lahore, Pakistan. The responses of low voltage channels, medium voltage channels, and transformer bridge for a 3–500 kHz NB-PLC frequency range are presented for DSM services. The master control room transmits control commands for the thermostat settings of SACs over power lines, crossing the transformer bridge to reach the SACs of power consumers by using communication protocol smart energy profile 1.0. The comparison of hourly and daily power consumption profiles under evaluation loads, by analyzing typical and variable frequency air conditioners on setting thermostat temperature at 25 °C and 27 °C conventionally and then by using DSM control technique, is analyzed. A prominent reduction in power consumption is found with the implementation of the DSM control technique.

Suggested Citation

  • Bilal Masood & Song Guobing & Jamel Nebhen & Ateeq Ur Rehman & Muhammad Naveed Iqbal & Iftikhar Rasheed & Mohit Bajaj & Muhammad Shafiq & Habib Hamam, 2022. "Investigation and Field Measurements for Demand Side Management Control Technique of Smart Air Conditioners located at Residential, Commercial, and Industrial Sites," Energies, MDPI, vol. 15(7), pages 1-23, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2482-:d:781365
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    References listed on IDEAS

    as
    1. Bilal Masood & M. Arif Khan & Sobia Baig & Guobing Song & Ateeq Ur Rehman & Saif Ur Rehman & Rao M. Asif & Muhammad Babar Rasheed, 2020. "Investigation of Deterministic, Statistical and Parametric NB-PLC Channel Modeling Techniques for Advanced Metering Infrastructure," Energies, MDPI, vol. 13(12), pages 1-20, June.
    2. Matthias Pilz & Luluwah Al-Fagih, 2020. "A Dynamic Game Approach for Demand-Side Management: Scheduling Energy Storage with Forecasting Errors," Dynamic Games and Applications, Springer, vol. 10(4), pages 897-929, December.
    3. Adnan Yousaf & Rao Muhammad Asif & Mustafa Shakir & Ateeq Ur Rehman & Fawaz Alassery & Habib Hamam & Omar Cheikhrouhou, 2021. "A Novel Machine Learning-Based Price Forecasting for Energy Management Systems," Sustainability, MDPI, vol. 13(22), pages 1-26, November.
    4. Masood, Bilal & Baig, Sobia, 2016. "Standardization and deployment scenario of next generation NB-PLC technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1033-1047.
    5. Kamran Daniel & Lauri Kütt & Muhammad Naveed Iqbal & Noman Shabbir & Ateeq Ur Rehman & Muhammad Shafiq & Habib Hamam, 2022. "Current Harmonic Aggregation Cases for Contemporary Loads," Energies, MDPI, vol. 15(2), pages 1-15, January.
    6. Adnan Khalid & Mujtaba Hussain Jaffery & Muhammad Yaqoob Javed & Adnan Yousaf & Jehangir Arshad & Ateeq Ur Rehman & Aun Haider & Maha M. Althobaiti & Muhammad Shafiq & Habib Hamam, 2021. "Performance Analysis of Mars-Powered Descent-Based Landing in a Constrained Optimization Control Framework," Energies, MDPI, vol. 14(24), pages 1-14, December.
    7. Harpreet Sharma & Sachin Mishra & Javed Dhillon & Naveen Kumar Sharma & Mohit Bajaj & Rizwan Tariq & Ateeq Ur Rehman & Muhammad Shafiq & Habib Hamam, 2022. "Feasibility of Solar Grid-Based Industrial Virtual Power Plant for Optimal Energy Scheduling: A Case of Indian Power Sector," Energies, MDPI, vol. 15(3), pages 1-21, January.
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    2. Hasan M. Salman & Jagadeesh Pasupuleti & Ahmad H. Sabry, 2023. "Review on Causes of Power Outages and Their Occurrence: Mitigation Strategies," Sustainability, MDPI, vol. 15(20), pages 1-34, October.

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