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Optimal sizing and location of SPV (solar photovoltaic) based MLDG (multiple location distributed generator) in distribution system for loss reduction, voltage profile improvement with economical benefits

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  • Jamil, Majid
  • Anees, Ahmed Sharique

Abstract

In this paper an analytical approach is used for optimal size and location of SPV (solar photovoltaic) based MLDG (multiple location distributed generator) in primary distribution system. The main objective of this research includes power loss reduction and voltage profile improvement along with economic benefits. DGs (Distributed Generators) are placed at single location to improve the performance of the system with respect to the power loss reduction and voltage profile improvement. For further reduction of power loss and enhancement of voltage profile, the estimated optimal size of a DG at single location serve as a constraint in locating the SPV based MLDG in the primary distribution system. The proposed approach are tested exhaustively on an IEEE 33 and IEEE 69 bus systems and it is found that the power loss reduction and voltage profile improvement is 57% and 0.943908 to 0.977294 pu respectively for IEEE 33 bus system where as it is 29% and 0.94882 to 0.95727 for IEEE 69 bus system as compared to the single DG placement. Obtained results are compared with the base value and found better as compared to the other techniques. From this research, it is revealed that the placements of MLDG are more significant and economical as compared to single DG placement.

Suggested Citation

  • Jamil, Majid & Anees, Ahmed Sharique, 2016. "Optimal sizing and location of SPV (solar photovoltaic) based MLDG (multiple location distributed generator) in distribution system for loss reduction, voltage profile improvement with economical bene," Energy, Elsevier, vol. 103(C), pages 231-239.
    • Handle: RePEc:eee:energy:v:103:y:2016:i:c:p:231-239
    DOI: 10.1016/j.energy.2016.02.095
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    Cited by:

    1. Wu, Yunna & Xu, Chuanbo & Ke, Yiming & Chen, Kaifeng & Sun, Xiaokun, 2018. "An intuitionistic fuzzy multi-criteria framework for large-scale rooftop PV project portfolio selection: Case study in Zhejiang, China," Energy, Elsevier, vol. 143(C), pages 295-309.
    2. Walter Gil-González & Oscar Danilo Montoya & Luis Fernando Grisales-Noreña & Alberto-Jesus Perea-Moreno & Quetzalcoatl Hernandez-Escobedo, 2020. "Optimal Placement and Sizing of Wind Generators in AC Grids Considering Reactive Power Capability and Wind Speed Curves," Sustainability, MDPI, vol. 12(7), pages 1-20, April.
    3. da Silva Benedito, Ricardo & Zilles, Roberto & Pinho, João Tavares, 2021. "Overcoming the power factor apparent degradation of loads fed by photovoltaic distributed generators," Renewable Energy, Elsevier, vol. 164(C), pages 1364-1375.
    4. Ahmed M. Agwa & Attia A. El-Fergany, 2023. "Protective Relaying Coordination in Power Systems Comprising Renewable Sources: Challenges and Future Insights," Sustainability, MDPI, vol. 15(9), pages 1-25, April.
    5. Akintunde S. Alayande & O. D. Owoicho & Tobiloba Emmanuel Somefun & Joseph Olowoleni & Ignatius K. Okakwu & Ademola Abdulkareem, 2021. "Power Quality Considerations for Distributed Generation Integration in the Nigerian Distribution Network Using NEPLAN Software," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 331-342.
    6. Parizad, Ali & Hatziadoniu, Konstadinos, 2020. "Security/stability-based Pareto optimal solution for distribution networks planning implementing NSGAII/FDMT," Energy, Elsevier, vol. 192(C).
    7. Das, Bikash & Mukherjee, V. & Das, Debapriya, 2019. "Optimum DG placement for known power injection from utility/substation by a novel zero bus load flow approach," Energy, Elsevier, vol. 175(C), pages 228-249.
    8. Fugui Dong & Wen Zhang, 2017. "Evaluation and comparison of power network plans including distributed photovoltaic generations," Operational Research, Springer, vol. 17(3), pages 885-900, October.
    9. Gao, Dian-ce & Sun, Yongjun & Zhang, Xingxing & Huang, Pei & Yelin Zhang,, 2022. "A GA-based NZEB-cluster planning and design optimization method for mitigating grid overvoltage risk," Energy, Elsevier, vol. 243(C).
    10. Senthil Kumar, J. & Charles Raja, S. & Jeslin Drusila Nesamalar, J. & Venkatesh, P., 2018. "Optimizing renewable based generations in AC/DC microgrid system using hybrid Nelder-Mead – Cuckoo Search algorithm," Energy, Elsevier, vol. 158(C), pages 204-215.
    11. Zhang, Yelin & Zhang, Xingxing & Huang, Pei & Sun, Yongjun, 2020. "Global sensitivity analysis for key parameters identification of net-zero energy buildings for grid interaction optimization," Applied Energy, Elsevier, vol. 279(C).
    12. Huy, Phung Dang & Ramachandaramurthy, Vigna K. & Yong, Jia Ying & Tan, Kang Miao & Ekanayake, Janaka B., 2020. "Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage," Energy, Elsevier, vol. 195(C).
    13. Amro M Elshurafa & Abdel Rahman Muhsen, 2019. "The Upper Limit of Distributed Solar PV Capacity in Riyadh: A GIS-Assisted Study," Sustainability, MDPI, vol. 11(16), pages 1-20, August.
    14. Novoa, Laura & Neal, Russ & Samuelsen, Scott & Brouwer, Jack, 2020. "Fuel cell transmission integrated grid energy resources to support generation-constrained power systems," Applied Energy, Elsevier, vol. 276(C).

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