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Optimal allocation and sizing for profitability and voltage enhancement of PV systems on feeders

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  • Hernández, J.C.
  • Medina, A.
  • Jurado, F.

Abstract

This paper presents a systematic algorithm to determine the optimal allocation and sizing of Photovoltaic Grid-connected Systems (PVGCSs) in feeders that provides the best overall impact onto the feeder. The optimal solution is reached by multi-objective optimization approach. Both technical and economical objective functions are taken into account in the optimization procedure. The technical objective is related with the improvement of the distribution feeder voltage conditions. The economical objective is associated with the profitability both PV generation and potential loss reduction on the feeder. This procedure aims at finding the PV solution that yields the best compromise for the two considered objectives between various potential candidates of PVGCSs well known. The results obtained with the proposed methodology for feeders found in the literature demonstrate its applicability.

Suggested Citation

  • Hernández, J.C. & Medina, A. & Jurado, F., 2007. "Optimal allocation and sizing for profitability and voltage enhancement of PV systems on feeders," Renewable Energy, Elsevier, vol. 32(10), pages 1768-1789.
    • Handle: RePEc:eee:renene:v:32:y:2007:i:10:p:1768-1789
    DOI: 10.1016/j.renene.2006.11.003
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    Citations

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    Cited by:

    1. Mellit, A. & Kalogirou, S.A. & Hontoria, L. & Shaari, S., 2009. "Artificial intelligence techniques for sizing photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(2), pages 406-419, February.
    2. Xie, Xiangmin & Peng, Fei & Zhang, Yan, 2022. "A data-driven probabilistic harmonic power flow approach in power distribution systems with PV generations," Applied Energy, Elsevier, vol. 321(C).
    3. Cagnano, A. & Torelli, F. & Alfonzetti, F. & De Tuglie, E., 2011. "Can PV plants provide a reactive power ancillary service? A treat offered by an on-line controller," Renewable Energy, Elsevier, vol. 36(3), pages 1047-1052.
    4. Hernández, J.C. & Ruiz-Rodriguez, F.J. & Jurado, F., 2017. "Modelling and assessment of the combined technical impact of electric vehicles and photovoltaic generation in radial distribution systems," Energy, Elsevier, vol. 141(C), pages 316-332.
    5. Rajesh, K. & Bhuvanesh, A. & Kannan, S. & Thangaraj, C., 2016. "Least cost generation expansion planning with solar power plant using Differential Evolution algorithm," Renewable Energy, Elsevier, vol. 85(C), pages 677-686.
    6. Kanato Tamashiro & Talal Alharbi & Alexey Mikhaylov & Ashraf M. Hemeida & Narayanan Krishnan & Mohammed Elsayed Lotfy & Tomonobu Senjyu, 2021. "Investigation of Home Energy Management with Advanced Direct Load Control and Optimal Scheduling of Controllable Loads," Energies, MDPI, vol. 14(21), pages 1-14, November.
    7. José Agüero-Rubio & Javier López-Martínez & José Ignacio Rojas-Sola & Ángel Jesús Callejón-Ferre, 2016. "A Design Alternative to Improve the Interconnection Capability of New Distributed-Generation Installations into Existing Griddle," Energies, MDPI, vol. 9(6), pages 1-11, May.
    8. Qi Wang & Ping Chang & Runqing Bai & Wenfei Liu & Jianfeng Dai & Yi Tang, 2019. "Mitigation Strategy for Duck Curve in High Photovoltaic Penetration Power System Using Concentrating Solar Power Station," Energies, MDPI, vol. 12(18), pages 1-16, September.
    9. Rajesh, K. & Karthikeyan, K. & Kannan, S. & Thangaraj, C., 2016. "Generation expansion planning based on solar plants with storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 953-964.
    10. Sharifzadeh, Mahdi & Lubiano-Walochik, Helena & Shah, Nilay, 2017. "Integrated renewable electricity generation considering uncertainties: The UK roadmap to 50% power generation from wind and solar energies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 385-398.
    11. Parida, Bhubaneswari & Iniyan, S. & Goic, Ranko, 2011. "A review of solar photovoltaic technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(3), pages 1625-1636, April.
    12. Pesaran H.A, Mahmoud & Huy, Phung Dang & Ramachandaramurthy, Vigna K., 2017. "A review of the optimal allocation of distributed generation: Objectives, constraints, methods, and algorithms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 293-312.

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