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Technoeconomic parametric analysis of PV-battery systems

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  • Khalilpour, Kaveh Rajab
  • Vassallo, Anthony

Abstract

Application of integrated PV-battery systems for off-grid locations has a history exceeding four decades. With the observed fast reduction of PV and battery system prices in recent years, however, interest in the use of PV-battery systems has notably increased even at on-grid locations. The aim of this paper is to assess the impact of various technoeconomic parameters, such as geographic location, weather condition, electricity price, feed-in tariff, PV/battery system cost, and PV/battery specifications on the economic feasibility of grid-connected PV-battery systems. For this, we have used our inhouse decision support tool for investment decision making, optimal sizing, and operation scheduling of grid-connected PV/battery system with respect to these parameters. The results show that decision on the selection of the right PV-battery system is significantly sensitive to each and every one of these parameters. Within various price scenarios that we carried out, battery shows positive impact on NPV only at low installation costs (e.g. ≤750 $/kWh). Neither the sales electricity tariff nor the feed-in tariff has alone a direct impact on the feasibility of installing a battery system. Rather, the magnitude of the difference between electricity price and feed-in tariff is the detrimental element in battery attractiveness. A case-study for Sydney, Australia, showed that at current sales/feed-in electricity tariffs, PV systems with prices of 2700 $/kW, or less, not only reach parity with the grid electricity price but also reach parity with feed-in tariff. This implies the viability of installing large PV systems merely for selling the generated electricity to the grid.

Suggested Citation

  • Khalilpour, Kaveh Rajab & Vassallo, Anthony, 2016. "Technoeconomic parametric analysis of PV-battery systems," Renewable Energy, Elsevier, vol. 97(C), pages 757-768.
    • Handle: RePEc:eee:renene:v:97:y:2016:i:c:p:757-768
    DOI: 10.1016/j.renene.2016.06.010
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    References listed on IDEAS

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    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. Stadler, M. & Groissböck, M. & Cardoso, G. & Marnay, C., 2014. "Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel," Applied Energy, Elsevier, vol. 132(C), pages 557-567.
    3. Fragaki, A. & Markvart, T., 2008. "Stand-alone PV system design: Results using a new sizing approach," Renewable Energy, Elsevier, vol. 33(1), pages 162-167.
    4. Khalilpour, Rajab & Vassallo, Anthony, 2016. "Planning and operation scheduling of PV-battery systems: A novel methodology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 194-208.
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