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Multi-Objective Optimization-Based Approach for Optimal Allocation of Distributed Generation Considering Techno-Economic and Environmental Indices

Author

Listed:
  • Muhammad Shahroz Sultan

    (US-Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), H-12, Islamabad 44000, Pakistan)

  • Syed Ali Abbas Kazmi

    (US-Pakistan Center for Advanced Studies in Energy (USPCAS-E), National University of Sciences and Technology (NUST), H-12, Islamabad 44000, Pakistan)

  • Abdullah Altamimi

    (Department of Electrical Engineering, College of Engineering, Majmaah University, Al-Majmaah 11952, Saudi Arabia
    Engineering and Applied Science Research Center, Majmaah University, Al-Majmaah 11952, Saudi Arabia)

  • Zafar A. Khan

    (Department of Electrical Engineering, Mirpur University of Science and Technology, Mirpur AK 10250, Pakistan
    School of Computing and Engineering, Institute for Innovation in Sustainable Engineering, University of Derby, Derby DE22 1GB, UK)

  • Dong Ryeol Shin

    (Department of Electrical and Computer Engineering, College of Information and Communication Engineering (CICE), Sungkyunkwan University (SKKU), Suwon 16419, Republic of Korea)

Abstract

Distribution networks have entered a new era with the broad adoption of the distributed generation (DG) allocation as a practical solution for addressing power losses, voltage variation, and voltage stability. The primary goal is to enhance techno-economic and environmental characteristics while meeting the limitations of the system. In order to allocate DGs in active distribution networks (ADNs) efficiently, this study demonstrates two optimization methods inspired by nature: ant lion optimization (ALO) and multiverse optimization (MVO). Various multi-criteria decision-making (MCDM) methods are used to find the best possible solution among the different alternatives. On the IEEE 33- and 69-bus active distribution networks, the proposed ALO was shown to be effective and produces the highest loss reduction in the IEEE 33- and 69-bus systems at 94.43% and 97.16%, respectively, and the maximum voltage stability index (VSI) was 0.9805 p.u and 0.9937 p.u, respectively; moreover, the minimum voltage deviation (V D ) and annual energy loss cost for the given test systems was 0.00019 p.u and 3353.3 PKR, which shows that the suggested method can produce higher quality results as compared to other methods presented in the literature. Therefore, the proposed ALO is a very efficient, effective, and appealing solution to the optimal allocation of the distributed generation (OADG) problem.

Suggested Citation

  • Muhammad Shahroz Sultan & Syed Ali Abbas Kazmi & Abdullah Altamimi & Zafar A. Khan & Dong Ryeol Shin, 2023. "Multi-Objective Optimization-Based Approach for Optimal Allocation of Distributed Generation Considering Techno-Economic and Environmental Indices," Sustainability, MDPI, vol. 15(5), pages 1-30, February.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:5:p:4306-:d:1083309
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    References listed on IDEAS

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    1. Tanwar, Surender Singh & Khatod, D.K., 2017. "Techno-economic and environmental approach for optimal placement and sizing of renewable DGs in distribution system," Energy, Elsevier, vol. 127(C), pages 52-67.
    2. Ali Selim & Salah Kamel & Amal A. Mohamed & Ehab E. Elattar, 2021. "Optimal Allocation of Multiple Types of Distributed Generations in Radial Distribution Systems Using a Hybrid Technique," Sustainability, MDPI, vol. 13(12), pages 1-31, June.
    3. Chenjun Sun & Zengqiang Mi & Hui Ren & Zhipeng Jing & Jinling Lu & David Watts, 2019. "Multi-Dimensional Indexes for the Sustainability Evaluation of an Active Distribution Network," Energies, MDPI, vol. 12(3), pages 1-24, January.
    4. Ehsan, Ali & Yang, Qiang, 2018. "Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques," Applied Energy, Elsevier, vol. 210(C), pages 44-59.
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