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Optimization-Based Energy Disaggregation: A Constrained Multi-Objective Approach

Author

Listed:
  • Jeewon Park

    (Department of Artificial Intelligence, Kyungpook National University, Daegu 37224, Republic of Korea)

  • Oladayo S. Ajani

    (Department of Artificial Intelligence, Kyungpook National University, Daegu 37224, Republic of Korea)

  • Rammohan Mallipeddi

    (Department of Artificial Intelligence, Kyungpook National University, Daegu 37224, Republic of Korea)

Abstract

Recently, optimization-based energy disaggregation (ED) algorithms have been gaining significance due to their capability to perform disaggregation with minimal information compared to the pattern-based ED algorithms, which demand large amounts of data for training. However, the performances of optimization-based ED algorithms depend on the problem formulation that includes an objective function(s) and/or constraints. In the literature, ED has been formulated as a constrained single-objective problem or an unconstrained multi-objective problem considering disaggregation error, sparsity of state switching, on/off switching, etc. In this work, the ED problem is formulated as a constrained multi-objective problem (CMOP), where the constraints related to the operational characteristics of the devices are included. In addition, the formulated CMOP is solved using a constrained multi-objective evolutionary algorithm (CMOEA). The performance of the proposed formulation is compared with those of three high-performing ED formulations in the literature based on the appliance-level and overall indicators. The results show that the proposed formulation improves both appliance-level and overall ED results.

Suggested Citation

  • Jeewon Park & Oladayo S. Ajani & Rammohan Mallipeddi, 2023. "Optimization-Based Energy Disaggregation: A Constrained Multi-Objective Approach," Mathematics, MDPI, vol. 11(3), pages 1-13, January.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:3:p:563-:d:1042981
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    References listed on IDEAS

    as
    1. Oladayo S. Ajani & Abhishek Kumar & Rammohan Mallipeddi & Swagatam Das & Ponnuthurai Nagaratnam Suganthan, 2022. "Benchmarking Optimization-Based Energy Disaggregation Algorithms," Energies, MDPI, vol. 15(5), pages 1-19, February.
    2. Tsai, Men-Shen & Lin, Yu-Hsiu, 2012. "Modern development of an Adaptive Non-Intrusive Appliance Load Monitoring system in electricity energy conservation," Applied Energy, Elsevier, vol. 96(C), pages 55-73.
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