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Penetration of solar power without storage

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  • Stodola, Nathan
  • Modi, Vijay

Abstract

If solar power is to provide substantial portions of our electricity needs, it will first become cost effective when it provides peak power in the daytime, without the need for storing the energy. Indeed since human electricity consumption is frequently small at night and larger when the sun is shining, there is already a natural correlation. Existing power systems are currently geared to provide this variable demand, with baseload plants cheaply providing a constant level of power, and dispatchable plants dynamically (and more expensively) supplying the rest. This leads to the frequent suggestion that one can exploit the correlation between sunlight and electricity by using energy from solar panels during the day to offset some of the load previously generated by dispatchable plants. This paper addresses the question of how much of the load can be substituted by the solar electricity, without leaving the solar power plant substantially idle or requiring the solar power to be stored. It uses historical sunlight and electrical load data from 32 regions of the United States to determine the photovoltaic (PV) power generation capacity that could be installed such that "almost all" of its energy output would occur at times of high demand. Specifically, what is the maximum deployment that permits 95% of the annual output from PV to be utilized without reducing the output of the baseload plants? Our results for these 32 regions are that 7.8% of the total annual electricity demand could be met by installing 59Â GW of PV panels. This represents about a fourth of the present electrical energy supplied by dispatchable plants. If solar power were equally effective in the rest of the United States, nearly 200Â GW of PV capacity could be put to use without any energy storage. Thus, in the near term, there is enormous room for expanding the roughly 1Â GW installed base of PV power without investing in night-time energy storage. The paper also provides insight into how year-to-year variability of sunlight and demand impact the results.

Suggested Citation

  • Stodola, Nathan & Modi, Vijay, 2009. "Penetration of solar power without storage," Energy Policy, Elsevier, vol. 37(11), pages 4730-4736, November.
  • Handle: RePEc:eee:enepol:v:37:y:2009:i:11:p:4730-4736
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    1. Kocaman, Ayse Selin & Ozyoruk, Emin & Taneja, Shantanu & Modi, Vijay, 2020. "A stochastic framework to evaluate the impact of agricultural load flexibility on the sizing of renewable energy systems," Renewable Energy, Elsevier, vol. 152(C), pages 1067-1078.
    2. Yu, Dayang & Zhang, Bo & Liang, Jun & Han, Xueshan, 2011. "The influence of generation mix on the wind integrating capability of North China power grids: A modeling interpretation and potential solutions," Energy Policy, Elsevier, vol. 39(11), pages 7455-7463.
    3. Orioli, Aldo & Di Gangi, Alessandra, 2016. "Five-years-long effects of the Italian policies for photovoltaics on the energy demand coverage of grid-connected PV systems installed in urban contexts," Energy, Elsevier, vol. 113(C), pages 444-460.
    4. Orioli, Aldo & Di Gangi, Alessandra, 2013. "Load mismatch of grid-connected photovoltaic systems: Review of the effects and analysis in an urban context," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 13-28.
    5. Solomon, A.A. & Faiman, D. & Meron, G., 2010. "Grid matching of large-scale wind energy conversion systems, alone and in tandem with large-scale photovoltaic systems: An Israeli case study," Energy Policy, Elsevier, vol. 38(11), pages 7070-7081, November.
    6. Solomon, A.A. & Faiman, D. & Meron, G., 2010. "An energy-based evaluation of the matching possibilities of very large photovoltaic plants to the electricity grid: Israel as a case study," Energy Policy, Elsevier, vol. 38(10), pages 5457-5468, October.
    7. Orioli, Aldo & Di Gangi, Alessandra, 2014. "Review of the energy and economic parameters involved in the effectiveness of grid-connected PV systems installed in multi-storey buildings," Applied Energy, Elsevier, vol. 113(C), pages 955-969.
    8. Aldo Orioli & Vincenzo Franzitta & Alessandra Di Gangi & Ferdinando Foresta, 2016. "The Recent Change in the Italian Policies for Photovoltaics: Effects on the Energy Demand Coverage of Grid-Connected PV Systems Installed in Urban Contexts," Energies, MDPI, vol. 9(11), pages 1-31, November.
    9. Orioli, Aldo & Di Gangi, Alessandra, 2015. "The recent change in the Italian policies for photovoltaics: Effects on the payback period and levelized cost of electricity of grid-connected photovoltaic systems installed in urban contexts," Energy, Elsevier, vol. 93(P2), pages 1989-2005.
    10. Lloyd, Bob & Forest, Andrew S., 2010. "The transition to renewables: Can PV provide an answer to the peak oil and climate change challenges?," Energy Policy, Elsevier, vol. 38(11), pages 7378-7394, November.
    11. Hernández-Moro, J. & Martínez-Duart, J.M., 2013. "Analytical model for solar PV and CSP electricity costs: Present LCOE values and their future evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 119-132.

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    Keywords

    Solar Energy storage Electricity;

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