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Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing

Author

Listed:
  • Muhammad Babar Rasheed

    (COMSATS Institute of Information Technology, Islamabad 44000, Pakistan)

  • Nadeem Javaid

    (COMSATS Institute of Information Technology, Islamabad 44000, Pakistan)

  • Ashfaq Ahmad

    (COMSATS Institute of Information Technology, Islamabad 44000, Pakistan)

  • Mohsin Jamil

    (School of Mechanical & Manufacturing Engineering, National University of Science and Technology, Islamabad 44000, Pakistan)

  • Zahoor Ali Khan

    (Internetworking Program, Faculty of Engineering, Dalhousie University, Halifax, NS B3J 4R2, Canada)

  • Umar Qasim

    (Cameron Library, University of Alberta, Edmonton, AB T6G 2J8, Canada)

  • Nabil Alrajeh

    (Department of Biomedical Technology, College of Applied Medical Sciences, King Saud University, Riyadh 11633, Saudi Arabia)

Abstract

In this paper, we present an energy optimization technique to schedule three types of household appliances (user dependent, interactive schedulable and unschedulable) in response to the dynamic behaviours of customers, electricity prices and weather conditions. Our optimization technique schedules household appliances in real time to optimally control their energy consumption, such that the electricity bills of end users are reduced while not compromising on user comfort. More specifically, we use the binary multiple knapsack problem formulation technique to design an objective function, which is solved via the constraint optimization technique. Simulation results show that average aggregated energy savings with and without considering the human presence control system are 11.77% and 5.91%, respectively.

Suggested Citation

  • Muhammad Babar Rasheed & Nadeem Javaid & Ashfaq Ahmad & Mohsin Jamil & Zahoor Ali Khan & Umar Qasim & Nabil Alrajeh, 2016. "Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing," Energies, MDPI, vol. 9(8), pages 1-25, July.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:8:p:593-:d:74817
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    References listed on IDEAS

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    1. Widén, Joakim & Wäckelgård, Ewa, 2010. "A high-resolution stochastic model of domestic activity patterns and electricity demand," Applied Energy, Elsevier, vol. 87(6), pages 1880-1892, June.
    2. 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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    Cited by:

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    2. Zafar Iqbal & Nadeem Javaid & Syed Muhammad Mohsin & Syed Muhammad Abrar Akber & Muhammad Khalil Afzal & Farruh Ishmanov, 2018. "Performance Analysis of Hybridization of Heuristic Techniques for Residential Load Scheduling," Energies, MDPI, vol. 11(10), pages 1-31, October.
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    4. Ihsan Ullah & Muhammad Babar Rasheed & Thamer Alquthami & Shahzadi Tayyaba, 2019. "A Residential Load Scheduling with the Integration of On-Site PV and Energy Storage Systems in Micro-Grid," Sustainability, MDPI, vol. 12(1), pages 1-36, December.
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    6. Emmanuel Guillen-Garcia & Angel L. Zorita-Lamadrid & Oscar Duque-Perez & Luis Morales-Velazquez & Roque Alfredo Osornio-Rios & Rene De Jesus Romero-Troncoso, 2017. "Power Consumption Analysis of Electrical Installations at Healthcare Facility," Energies, MDPI, vol. 10(1), pages 1-14, January.
    7. Tuomela, Sanna & de Castro Tomé, Mauricio & Iivari, Netta & Svento, Rauli, 2021. "Impacts of home energy management systems on electricity consumption," Applied Energy, Elsevier, vol. 299(C).
    8. Thamer Alquthami & Ahmad H. Milyani & Muhammad Awais & Muhammad B. Rasheed, 2021. "An Incentive Based Dynamic Pricing in Smart Grid: A Customer’s Perspective," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    9. Martina Arosio & Davide Falabretti, 2023. "DER Participation in Ancillary Services Market: An Analysis of Current Trends and Future Opportunities," Energies, MDPI, vol. 16(5), pages 1-21, March.
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    12. Mariko Almeida Carneiro & Diogo Da Fonseca-Soares & Lucian Hendyo Max Pereira & Angel Firmín Ramos-Ridao, 2022. "An Approach for Water and Energy Savings in Public Buildings: A Case Study of Brazilian Rail Company," Sustainability, MDPI, vol. 14(23), pages 1-13, November.
    13. Bishnu P. Bhattarai & Kurt S. Myers & Birgitte Bak-Jensen & Sumit Paudyal, 2017. "Multi-Time Scale Control of Demand Flexibility in Smart Distribution Networks," Energies, MDPI, vol. 10(1), pages 1-18, January.
    14. Sana Iqbal & Mohammad Sarfraz & Mohammad Ayyub & Mohd Tariq & Ripon K. Chakrabortty & Michael J. Ryan & Basem Alamri, 2021. "A Comprehensive Review on Residential Demand Side Management Strategies in Smart Grid Environment," Sustainability, MDPI, vol. 13(13), pages 1-23, June.
    15. Piotr Bórawski & Aneta Bełdycka-Bórawska & Lisa Holden & Tomasz Rokicki, 2022. "The Role of Renewable Energy Sources in Electricity Production in Poland and the Background of Energy Policy of the European Union at the Beginning of the COVID-19 Crisis," Energies, MDPI, vol. 15(22), pages 1-17, November.
    16. Makhadmeh, Sharif Naser & Khader, Ahamad Tajudin & Al-Betar, Mohammed Azmi & Naim, Syibrah & Abasi, Ammar Kamal & Alyasseri, Zaid Abdi Alkareem, 2019. "Optimization methods for power scheduling problems in smart home: Survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    17. Ritu Kandari & Neeraj Neeraj & Alexander Micallef, 2022. "Review on Recent Strategies for Integrating Energy Storage Systems in Microgrids," Energies, MDPI, vol. 16(1), pages 1-24, December.
    18. Su, Yongxin & Zhou, Yao & Tan, Mao, 2020. "An interval optimization strategy of household multi-energy system considering tolerance degree and integrated demand response," Applied Energy, Elsevier, vol. 260(C).
    19. Yonggang Zhang & Yongwei Zhong & Yingda Gong & Lirong Zheng, 2018. "The Optimization of Visual Comfort and Energy Consumption Induced by Natural Light Based on PSO," Sustainability, MDPI, vol. 11(1), pages 1-11, December.

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