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Optimization of the investment cost of solar based grid

Author

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  • Siali, M.
  • Flazi, S.
  • Stambouli, A. Boudghene
  • Fergani, S.

Abstract

A new optimization method of the investment cost of a distribution grid supplied by photovoltaic (PV) sources. This method consists of determining the optimal grid cables cross sections and the optimal grid supply point (GSP) position, such that the sum of the joule losses and the cables investment costs are optimized. The determination of these parameters are performed by the programming of analytical equations using Matlab software, taking into account the influence of technical and economical requirements on the choice of the cables cross sections and the possibility of using several photovoltaic generators (PVG) with separated grids for spaced loads from a long distance, by optimizing the grouping loads combination. The obtained results show that: for a lowest global investment cost, the optimal GSP is referred to the minimum cost center (MCC), for the grid joule losses minimization, it can be in the minimum joule losses cost center (MJLCC); or in the center of the minimum investment cost of cables (CMICC) in the case of the cables investment cost minimization. The adoption of the optimal cross sections, the optimal PVGs (GSPs) number and their optimal positions achieve significant economic gains in terms of the investment cost.

Suggested Citation

  • Siali, M. & Flazi, S. & Stambouli, A. Boudghene & Fergani, S., 2016. "Optimization of the investment cost of solar based grid," Renewable Energy, Elsevier, vol. 97(C), pages 169-176.
    • Handle: RePEc:eee:renene:v:97:y:2016:i:c:p:169-176
    DOI: 10.1016/j.renene.2016.05.077
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    References listed on IDEAS

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    1. Nottrott, A. & Kleissl, J. & Washom, B., 2013. "Energy dispatch schedule optimization and cost benefit analysis for grid-connected, photovoltaic-battery storage systems," Renewable Energy, Elsevier, vol. 55(C), pages 230-240.
    2. Xiangang Peng & Lixiang Lin & Weiqin Zheng & Yi Liu, 2015. "Crisscross Optimization Algorithm and Monte Carlo Simulation for Solving Optimal Distributed Generation Allocation Problem," Energies, MDPI, vol. 8(12), pages 1-19, December.
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    Cited by:

    1. Padmanathan K. & Uma Govindarajan & Vigna K. Ramachandaramurthy & Sudar Oli Selvi T., 2017. "Multiple Criteria Decision Making (MCDM) Based Economic Analysis of Solar PV System with Respect to Performance Investigation for Indian Market," Sustainability, MDPI, vol. 9(5), pages 1-19, May.
    2. Joshua Sunday Riti & Deyong Song & Yang Shu & Miriam Kamah & Agya Adi Atabani, 2018. "Does renewable energy ensure environmental quality in favour of economic growth? Empirical evidence from China’s renewable development," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(5), pages 2007-2030, September.

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