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Optimal Distributed Energy Resources Accommodation with Techno-Economic Benefits Using Cheetah Optimizer
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  • Muhammad Shaarif,
  • Muhammad Yousif,
  • Muhammad Numan,
  • Muhammad Zubair Iftikhar,
  • Izhar Us Salam,
  • Thamer A. H. Alghamdi
Muhammad Shaarif
National University of Sciences and Technology
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Muhammad Yousif
National University of Sciences and Technology

Corresponding Author:[email protected]

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Muhammad Numan
National University of Sciences and Technology
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Muhammad Zubair Iftikhar
National University of Sciences and Technology
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Izhar Us Salam
National University of Sciences and Technology
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Thamer A. H. Alghamdi
Cardiff University
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Abstract

The planning and operation of radial distribution networks (RDN) face increasing challenges such as active power losses and voltage instability, prompting a focus on integrating renewable energy resources (RER) to mitigate these issues. This study presents a techno-economic optimization framework leveraging the Cheetah optimizer (CO), a recently introduced metaheuristic technique, to optimize the accommodation of distributed energy resource (DER) units within the IEEE 33-bus radial distribution networks (RDN) utilizing MATLAB environment. Both single and multi-objective perspectives are explored, demonstrating significant reductions in active power losses, minimized voltage deviation, improved stability, and maximized economic benefits. The Cheetah optimizer (CO) efficacy is showcased through notable achievements, including a 94.20% reduction in active power losses and annual savings of up to $77,933 for optimal power factor (OPF) mode in multi-objective optimization, surpassing existing literature. Additionally, reliability analysis conducted with ETAP software underscores the effectiveness of DER integration, particularly with wind turbine systems, in enhancing network reliability.
Submitted to IET Generation, Transmission & Distribution
28 Apr 2024Submission Checks Completed
28 Apr 2024Assigned to Editor
28 Apr 2024Review(s) Completed, Editorial Evaluation Pending
05 Jun 2024Reviewer(s) Assigned
17 Jul 2024Editorial Decision: Revise Major
30 Jul 20241st Revision Received
31 Jul 2024Assigned to Editor
31 Jul 2024Submission Checks Completed
31 Jul 2024Review(s) Completed, Editorial Evaluation Pending
31 Jul 2024Reviewer(s) Assigned