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Operational Scheduling of Household Appliances by Using Triple-Objective Optimization Algorithm Integrated with Multi-Criteria Decision Making

Author

Listed:
  • Dhiaa Halboot Muhsen

    (Department of Computer Engineering, Mustansiriyah University, Baghdad 14022, Iraq)

  • Haider Tarish Haider

    (Department of Computer Engineering, Mustansiriyah University, Baghdad 14022, Iraq)

  • Yaarob Al-Nidawi

    (Department of Computer Engineering, Mustansiriyah University, Baghdad 14022, Iraq)

  • Ghadeer Ghazi Shayea

    (College of Information Technology, Imam Ja’afar Al-Sadiq University, Baghdad 10001, Iraq)

Abstract

Load scheduling is a key factor in demand side management (DSM), which manages available generation capacity with regard to the required demand. In this paper, a triple-objective load scheduling optimization problem (LSOP) is formulated for achieving optimal cost and peak demand as well as minimum customer inconvenience. A Henry gas solubility optimization (HGSO) algorithm that is based on multi-objective is used for solving LSOP. The proposed HGSO offers a set of compromise solutions that represent the tradeoff between the three objectives of the formulated problem. A set of all compromise solutions from the dominant Pareto front is achieved first, and then ranked by using MCDM so as to optimally sort these solutions. An entropy weighting method (EWM) is then used for computing the weights of various criteria that dominate the LSOP and is provided as a technique for ordering preferences by similarity to achieve the ideal solution (TOPSIS) so as to rank the sorted solutions. Two types of end-users are considered so as to show the effectiveness of the proposed LSOP: non-cooperative and cooperative users. The results of the proposed load scheduling method show the significance of the proposed method for both the cooperative and non-cooperative end-users. The proposed method achieves a cost of energy of R50.62 as a total cost of energy consumed by four non-cooperative end-users. The cost of energy for the cooperative end-users is found to be R47.39. Thus, saving in the energy cost unit is found to be around 5.5% by using the proposed method; moreover, the peak demand value is reduced by 9.7% when non-cooperative end-users becomes cooperative.

Suggested Citation

  • Dhiaa Halboot Muhsen & Haider Tarish Haider & Yaarob Al-Nidawi & Ghadeer Ghazi Shayea, 2023. "Operational Scheduling of Household Appliances by Using Triple-Objective Optimization Algorithm Integrated with Multi-Criteria Decision Making," Sustainability, MDPI, vol. 15(24), pages 1-24, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:24:p:16589-:d:1294990
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    References listed on IDEAS

    as
    1. Rasheed, Muhammad Babar & R-Moreno, María D., 2022. "Minimizing pricing policies based on user load profiles and residential demand responses in smart grids," Applied Energy, Elsevier, vol. 310(C).
    2. Xinhui Lu & Kaile Zhou & Felix T. S. Chan & Shanlin Yang, 2017. "Optimal scheduling of household appliances for smart home energy management considering demand response," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1639-1653, September.
    Full references (including those not matched with items on IDEAS)

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