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On Employing a Constrained Nonlinear Optimizer to Constrained Economic Dispatch Problems

Author

Listed:
  • Ghulam Abbas

    (Department of Electrical Engineering, The University of Lahore, Lahore 54000, Pakistan)

  • Irfan Ahmad Khan

    (Clean and Resilient Energy Systems (CARES) Lab, Electrical and Computer Engineering Department, Texas A & M University, Galveston, TX 77553, USA)

  • Naveed Ashraf

    (Department of Electrical Engineering, The University of Lahore, Lahore 54000, Pakistan)

  • Muhammad Taskeen Raza

    (Department of Electrical Engineering, Lahore College for Women University, Lahore 54000, Pakistan)

  • Muhammad Rashad

    (Department of Electrical Engineering, The University of Lahore, Lahore 54000, Pakistan)

  • Raheel Muzzammel

    (Department of Electrical Engineering, The University of Lahore, Lahore 54000, Pakistan)

Abstract

Recently, different metaheuristic techniques, their variants, and hybrid forms have been extensively used to solve economic load dispatch (ELD) problems with and without valve point loading (VPL) effects. Due to the randomization involved in these metaheuristic techniques, one has to perform extensive runs for each experiment to get an optimal solution. The process may sometimes become laborious and time-consuming to converge to an optimal solution. On the other hand, advanced calculus-based techniques, being deterministic, perform iteration systematically and come up with the same solution on each run of the experiment. Since ELD problems are constrained optimization problems, we are proposing the constrained (deterministic) optimization algorithm for their solutions. Various 13-unit, 38-unit, and 40-unit thermal test systems are considered. Valve point loading (VPL) effects are also considered in some cases. Computer-based numerical results depict that the constrained optimization algorithm shows evidence of being almost as competitive in a total fuel cost as the metaheuristic optimization techniques, especially for the less-constrained ELD problems but with far reduced computation time. This finding validates the application of the constrained optimization technique to solve the economic dispatch problem.

Suggested Citation

  • Ghulam Abbas & Irfan Ahmad Khan & Naveed Ashraf & Muhammad Taskeen Raza & Muhammad Rashad & Raheel Muzzammel, 2023. "On Employing a Constrained Nonlinear Optimizer to Constrained Economic Dispatch Problems," Sustainability, MDPI, vol. 15(13), pages 1-23, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:13:p:9924-:d:1176458
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    References listed on IDEAS

    as
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    3. Xiong, Guojiang & Shi, Dongyuan & Duan, Xianzhong, 2013. "Multi-strategy ensemble biogeography-based optimization for economic dispatch problems," Applied Energy, Elsevier, vol. 111(C), pages 801-811.
    4. Muhammad Ahmad Iqbal & Muhammad Salman Fakhar & Noor Ul Ain & Ahsen Tahir & Irfan Ahmad Khan & Ghulam Abbas & Syed Abdul Rahman Kashif, 2023. "A New Fast Deterministic Economic Dispatch Method and Statistical Performance Evaluation for the Cascaded Short-Term Hydrothermal Scheduling Problem," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
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    6. Loau Al-Bahrani & Mehdi Seyedmahmoudian & Ben Horan & Alex Stojcevski, 2021. "Solving the Real Power Limitations in the Dynamic Economic Dispatch of Large-Scale Thermal Power Units under the Effects of Valve-Point Loading and Ramp-Rate Limitations," Sustainability, MDPI, vol. 13(3), pages 1-26, January.
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