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Solar PV integration cost variation due to array orientation and geographic location in the Electric Reliability Council of Texas

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  • Deetjen, Thomas A.
  • Garrison, Jared B.
  • Rhodes, Joshua D.
  • Webber, Michael E.

Abstract

Adding large solar photovoltaic (PV) resources into an electric grid influences the flexibility characteristics of its net load profile. The dispatch of the existing generation fleet changes as it adjusts to accommodate the new net load. This study categorizes and defines these flexibility characteristics. It utilizes a unit commitment and dispatch (UC&D) model to simulate large solar generation assets with different geographic locations and orientations. The simulations show the sensitivity of the wholesale energy price, reserve market prices, total dispatch cost, fuel mix, emissions, and water use to changes in net load flexibility requirements. The results show that generating 22,500GWh of solar energy in a 2011 simulation of the Electric Reliability Council of Texas (ERCOT) reduces total dispatch cost by approximately $900million (a 10.3% decrease) while increasing ancillary services costs by approximately $10million (a 3% increase). The results also show that PV reduces water consumption and water withdrawals as well as CO2, NOx, and SOx emissions. It also reduces peak load by 4% but increases net load volatility by 40–79% and ramping by 11–33%. In addition, west-located, west-oriented solar resources reduce total dispatch cost more than the other simulated solar scenarios. The west-located, west-oriented solar simulation required greater system flexibility, but utilized more low-cost generators and fewer high-cost generators for energy production than other simulated scenarios. These results suggest that the mix of energy provided by different generation technologies influences the dispatch cost more than the net load flexibility requirements.

Suggested Citation

  • Deetjen, Thomas A. & Garrison, Jared B. & Rhodes, Joshua D. & Webber, Michael E., 2016. "Solar PV integration cost variation due to array orientation and geographic location in the Electric Reliability Council of Texas," Applied Energy, Elsevier, vol. 180(C), pages 607-616.
  • Handle: RePEc:eee:appene:v:180:y:2016:i:c:p:607-616
    DOI: 10.1016/j.apenergy.2016.08.012
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    Cited by:

    1. Nemet, Gregory F. & O’Shaughnessy, Eric & Wiser, Ryan & Darghouth, Naïm & Barbose, Galen & Gillingham, Ken & Rai, Varun, 2017. "Characteristics of low-priced solar PV systems in the U.S," Applied Energy, Elsevier, vol. 187(C), pages 501-513.
    2. Olukunle O. Owolabi & Toryn L. J. Schafer & Georgia E. Smits & Sanhita Sengupta & Sean E. Ryan & Lan Wang & David S. Matteson & Mila Getmansky Sherman & Deborah A. Sunter, 2021. "Role of Variable Renewable Energy Penetration on Electricity Price and its Volatility Across Independent System Operators in the United States," Papers 2112.11338, arXiv.org, revised Nov 2022.
    3. Deetjen, Thomas A. & Vitter, J. Scott & Reimers, Andrew S. & Webber, Michael E., 2018. "Optimal dispatch and equipment sizing of a residential central utility plant for improving rooftop solar integration," Energy, Elsevier, vol. 147(C), pages 1044-1059.
    4. Freitas, S. & Brito, M.C., 2019. "Non-cumulative only solar photovoltaics for electricity load-matching," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 271-283.
    5. Philip Tafarte & Marcus Eichhorn & Daniela Thrän, 2019. "Capacity Expansion Pathways for a Wind and Solar Based Power Supply and the Impact of Advanced Technology—A Case Study for Germany," Energies, MDPI, vol. 12(2), pages 1-23, January.
    6. Mills, Andrew D. & Levin, Todd & Wiser, Ryan & Seel, Joachim & Botterud, Audun, 2020. "Impacts of variable renewable energy on wholesale markets and generating assets in the United States: A review of expectations and evidence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    7. Deetjen, Thomas A. & Martin, Henry & Rhodes, Joshua D. & Webber, Michael E., 2018. "Modeling the optimal mix and location of wind and solar with transmission and carbon pricing considerations," Renewable Energy, Elsevier, vol. 120(C), pages 35-50.
    8. Deetjen, Thomas A. & Rhodes, Joshua D. & Webber, Michael E., 2017. "The impacts of wind and solar on grid flexibility requirements in the Electric Reliability Council of Texas," Energy, Elsevier, vol. 123(C), pages 637-654.
    9. Liu, Jingkun & Zhang, Ning & Kang, Chongqing & Kirschen, Daniel & Xia, Qing, 2017. "Cloud energy storage for residential and small commercial consumers: A business case study," Applied Energy, Elsevier, vol. 188(C), pages 226-236.
    10. Maaike Braat & Odysseas Tsafarakis & Ioannis Lampropoulos & Joris Besseling & Wilfried G. J. H. M. van Sark, 2021. "Cost-Effective Increase of Photovoltaic Electricity Feed-In on Congested Transmission Lines: A Case Study of The Netherlands," Energies, MDPI, vol. 14(10), pages 1-21, May.
    11. Mallapragada, Dharik S. & Papageorgiou, Dimitri J. & Venkatesh, Aranya & Lara, Cristiana L. & Grossmann, Ignacio E., 2018. "Impact of model resolution on scenario outcomes for electricity sector system expansion," Energy, Elsevier, vol. 163(C), pages 1231-1244.
    12. Spiller, Elisheba & Sopher, Peter & Martin, Nicholas & Mirzatuny, Marita & Zhang, Xinxing, 2017. "The environmental impacts of green technologies in TX," Energy Economics, Elsevier, vol. 68(C), pages 199-214.
    13. Sascha Samadi, 2017. "The Social Costs of Electricity Generation—Categorising Different Types of Costs and Evaluating Their Respective Relevance," Energies, MDPI, vol. 10(3), pages 1-37, March.
    14. Wang, Rong & Hasanefendic, Sandra & Von Hauff, Elizabeth & Bossink, Bart, 2022. "The cost of photovoltaics: Re-evaluating grid parity for PV systems in China," Renewable Energy, Elsevier, vol. 194(C), pages 469-481.

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