Abstract
AbstractTexas has seen a rapid decline in coal use in recent years, but still burns more coal and emits more carbon dioxide and sulfur dioxide than any other state. Coal’s share of power generation in the Electric Reliability Council of Texas (ERCOT) system that covers most of the state fell to 20 percent in 2019, while wind grew to 20 percent and solar to 2 percent. Here, we investigate the potential for new wind and solar projects already proposed in the ERCOT interconnection queue as of June 2020 to replace the coal power that remained in 2019. The Wind Integration National Data Set (WIND) Toolkit is used to simulate the output of each wind project, and the System Advisor Model to simulate solar output, for 3 years of meteorological conditions. Mixed integer cost-optimization modeling finds that a portfolio of just 72 of the 108 wind projects and 42 of the 262 solar projects in the queue would be sufficient to replace most coal generation in ERCOT, leaving 10 percent of coal output uncovered and generating larger surpluses at other times. The complementary timing of solar and wind in Texas, with sunshine peaking midday and winds peaking overnight in the west and on summer evenings near the coast, enables these high levels of displacement to be achieved. In fact, the wind and solar portfolio would outproduce retired coal on summer afternoons when demand peaks, leaving small gaps in evenings and shoulder seasons when demand is lower.
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Software
Reference49 articles.
1. Andrade, J., & Baldick, R. (2017). Estimation of Transmission Costs for New Generation. University of Texas at Austin Energy Institute. https://energy.utexas.edu/sites/default/files/UTAustin_FCe_TransmissionCosts_2017.pdf
2. Blair, N. J., DiOrio, N. A., Freeman, J. M., Gilman, P., Janzou, S., Neises, T. W., & Wagner, M. J. (2018). System Advisor Model (SAM) General Description (Version 2017.9.5) (NREL/TP--6A20–70414, 1440404; p. NREL/TP--6A20–70414, 1440404). https://doi.org/10.2172/1440404
3. Bolinger, M., Seel, J., & Robson, D. (2019). Utility-scale solar: Empirical Trends in Project Technology, Cost, Performance, and PPA Pricing in the United States – 2019 Edition. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). https://emp.lbl.gov/sites/default/files/lbnl_utility_scale_solar_2019_edition_final.pdf
4. Bolinger, M., Seel, J., Robson, D., & Warner, C. (2020). Utility-Scale Solar Data Update: 2020 Edition (p. 57). Lawrence Berkeley National Laboratory. https://emp.lbl.gov/sites/default/files/2020_utility-scale_solar_data_update.pdf
5. Deetjen, T. A., Garrison, J. B., Rhodes, J. D., & Webber, M. E. (2016). Solar PV integration cost variation due to array orientation and geographic location in the Electric Reliability Council of Texas. Applied Energy, 180, 607–616. https://doi.org/10.1016/j.apenergy.2016.08.012
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