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Balancing comfort and conservation: dynamic programming algorithm for appliance scheduling in residential demand-side management

Authors

  • Maria Ashraf

    Dept. of Electronics and Power Engineering, National University of Science and Technology, Karachi, Sindh, Pakistan
    Author

  • Maryam Arshad

    Dept. of Electronics and Power Engineering, National University of Science and Technology, Karachi, Sindh, Pakistan
    Author

  • Sajjad Haider Zaidi

    Dept. of Electronics and Power Engineering, National University of Science and Technology, Karachi, Sindh, Pakistan
    Author

  • Kiran Shaukat

    Dept. of Electronics and Power Engineering, National University of Science and Technology, Karachi, Sindh, Pakistan
    Author

DOI:

https://doi.org/10.22581/muet1982.0051

Keywords:

Demand Response Home Energy Management Energy Efficiency Optimization Algorithms Appliance Scheduling Dynamic Programming Algorithm Peak average ratio (PAR)

Abstract

With the exponential upward thrust in residential energy consumption, effective Demand-Side Management (DSM) has come to be vital to ensure grid balance and user satisfaction. This paper proposes a holistic and customer-centric method for DSM via the improvement of the Automated Load Scheduling (ALS) algorithm. Unlike conventional strategies that neglect user preferences, ALS permits dynamic equipment categorization, priority-based scheduling, and real-time consumption comments, ensuring active consumer participation. The ALS set of rules employs dynamic programming to evenly distribute appliance hundreds across a 24-hour cycle, minimizing Peak-to-Average Ratio (PAR), electricity cost, and consumer inconvenience. A flexible power level selection mechanism, quadratic pricing version, and iterative optimization framework further enhance adaptability to numerous household patterns. Empirical results from weekday and weekend situations exhibit huge reductions in PAR—over 32% on weekdays and 46% on weekends—along with improved energy efficiency and cost savings. The proposed ALS framework offers a sturdy, scalable solution for smart home strength control systems in smart grid environments.

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References

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Published

2025-07-01

Issue

Vol. 44 No. 3 (2025): July Issue

Section

Articles

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Copyright (c) 2025 Mehran University Research Journal of Engineering and Technology

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How to Cite

Balancing comfort and conservation: dynamic programming algorithm for appliance scheduling in residential demand-side management. (2025). Mehran University Research Journal of Engineering and Technology, 44(3), 10-18. https://doi.org/10.22581/muet1982.0051

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