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A Solution Based on Bluetooth Low Energy for Smart Home Energy Management

Author

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  • Mario Collotta

    (Faculty of Engineering and Architecture, Kore University of Enna, Cittadella Universitaria, Enna 94100, Italy)

  • Giovanni Pau

    (Faculty of Engineering and Architecture, Kore University of Enna, Cittadella Universitaria, Enna 94100, Italy)

Abstract

The research and the implementation of home automation are getting more popular because the Internet of Things holds promise for making homes smarter through wireless technologies. The installation of systems based on wireless networks can play a key role also in the extension of the smart grid towards smart homes, that can be deemed as one of the most important components of smart grids. This paper proposes a fuzzy-based solution for smart energy management in a home automation wireless network. The approach, by using Bluetooth Low Energy (BLE), introduces a Fuzzy Logic Controller (FLC) in order to improve a Home Energy Management (HEM) scheme, addressing the power load of standby appliances and their loads in different hours of the day. Since the consumer is involved in the choice of switching on/off of home appliances, the approach introduced in this work proposes a fuzzy-based solution in order to manage the consumer feedbacks. Simulation results show that the proposed solution is efficient in terms of reducing peak load demand, electricity consumption charges with an increase comfort level of consumers. The performance of the proposed BLE-based wireless network scenario are validated in terms of packet delivery ratio, delay, and jitter and are compared to IEEE 802.15.4 technology.

Suggested Citation

  • Mario Collotta & Giovanni Pau, 2015. "A Solution Based on Bluetooth Low Energy for Smart Home Energy Management," Energies, MDPI, vol. 8(10), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:10:p:11916-11938:d:57493
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    References listed on IDEAS

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    1. Tiago D. P. Mendes & Radu Godina & Eduardo M. G. Rodrigues & João C. O. Matias & João P. S. Catalão, 2015. "Smart Home Communication Technologies and Applications: Wireless Protocol Assessment for Home Area Network Resources," Energies, MDPI, vol. 8(7), pages 1-33, July.
    2. Mohamed A. Ahmed & Yong Cheol Kang & Young-Chon Kim, 2015. "Communication Network Architectures for Smart-House with Renewable Energy Resources," Energies, MDPI, vol. 8(8), pages 1-20, August.
    3. Antimo Barbato & Antonio Capone, 2014. "Optimization Models and Methods for Demand-Side Management of Residential Users: A Survey," Energies, MDPI, vol. 7(9), pages 1-38, September.
    4. Mario Collotta & Antonio Messineo & Giuseppina Nicolosi & Giovanni Pau, 2014. "A Dynamic Fuzzy Controller to Meet Thermal Comfort by Using Neural Network Forecasted Parameters as the Input," Energies, MDPI, vol. 7(8), pages 1-30, July.
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    1. Apolinar González-Potes & Walter A. Mata-López & Alberto M. Ochoa-Brust & Carlos Escobar-del Pozo, 2016. "Smart Control of Multiple Evaporator Systems with Wireless Sensor and Actuator Networks," Energies, MDPI, vol. 9(3), pages 1-24, February.
    2. Hosna Khajeh & Hannu Laaksonen & Amin Shokri Gazafroudi & Miadreza Shafie-khah, 2019. "Towards Flexibility Trading at TSO-DSO-Customer Levels: A Review," Energies, MDPI, vol. 13(1), pages 1-19, December.
    3. Daniel Chioran & Honoriu Valean, 2021. "Design and Performance Evaluation of a Home Energy Management System for Power Saving," Energies, MDPI, vol. 14(6), pages 1-19, March.
    4. Naser Hossein Motlagh & Mahsa Mohammadrezaei & Julian Hunt & Behnam Zakeri, 2020. "Internet of Things (IoT) and the Energy Sector," Energies, MDPI, vol. 13(2), pages 1-27, January.
    5. 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.
    6. Bhati, Abhishek & Hansen, Michael & Chan, Ching Man, 2017. "Energy conservation through smart homes in a smart city: A lesson for Singapore households," Energy Policy, Elsevier, vol. 104(C), pages 230-239.
    7. Ronggang Zhang & Sathishkumar V E & R. Dinesh Jackson Samuel, 2020. "Fuzzy Efficient Energy Smart Home Management System for Renewable Energy Resources," Sustainability, MDPI, vol. 12(8), pages 1-14, April.
    8. Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Amir Mansouri, Seyed & Jurado, Francisco, 2022. "Day-ahead scheduling of 100% isolated communities under uncertainties through a novel stochastic-robust model," Applied Energy, Elsevier, vol. 328(C).
    9. Mingfu Li & Guan-Yi Li & Hou-Ren Chen & Cheng-Wei Jiang, 2018. "QoE-Aware Smart Home Energy Management Considering Renewables and Electric Vehicles," Energies, MDPI, vol. 11(9), pages 1-16, September.
    10. Giovanni Pau & Mario Collotta & Vincenzo Maniscalco, 2017. "Bluetooth 5 Energy Management through a Fuzzy-PSO Solution for Mobile Devices of Internet of Things," Energies, MDPI, vol. 10(7), pages 1-22, July.
    11. Giovanni Pau & Mario Collotta & Antonio Ruano & Jiahu Qin, 2017. "Smart Home Energy Management," Energies, MDPI, vol. 10(3), pages 1-5, March.
    12. Augustine Ikpehai & Bamidele Adebisi & Khaled M. Rabie & Russell Haggar & Mike Baker, 2016. "Experimental Study of 6LoPLC for Home Energy Management Systems," Energies, MDPI, vol. 9(12), pages 1-19, December.
    13. Andrzej Ożadowicz, 2017. "A New Concept of Active Demand Side Management for Energy Efficient Prosumer Microgrids with Smart Building Technologies," Energies, MDPI, vol. 10(11), pages 1-22, November.
    14. Danish Mahmood & Nadeem Javaid & Nabil Alrajeh & Zahoor Ali Khan & Umar Qasim & Imran Ahmed & Manzoor Ilahi, 2016. "Realistic Scheduling Mechanism for Smart Homes," Energies, MDPI, vol. 9(3), pages 1-28, March.

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