Investigation of Stochastic Unit Commitment to Enable Advanced Flexibility Measures for High Shares of Solar PV
Journal Article
·
· Applied Energy
As the share of solar photovoltaics (PV) in the power system increases, there is a growing need for flexibility from multiple, possibly interdependent sources to adjust to PV's variability, uncertainty, and diurnal dependence. This paper investigates how stochastic unit commitment leveraging probabilistic solar forecasts can support other flexibility measures under high solar shares. We consider two flexibility measures relevant to day-ahead scheduling: battery energy time-shifting and solar ancillary service provision. Unit commitment and economic dispatch simulations are conducted on a realistic test system based on Texas using day-ahead solar trajectories. The benefits of the two flexibility measures are pronounced when the instantaneous solar share is high, offering cost savings of 10%-20% in the spring. For a Texas-sized system, this translates to hundreds of millions of dollars in cost savings once the installed PV capacity enables instantaneous solar shares regularly exceeding 40%. Using probabilistic forecasts also greatly increases the reliability of upward reserve provision from solar PV, reducing unserved reserves by 50%-100%. Both day-ahead forecast resolution and errors can impact system reliability at high solar shares, but the stochastic formulation has significant value, mitigating reliability impacts on over-forecast days.
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1874464
- Report Number(s):
- NREL/JA-5C00-80513; MainId:43715; UUID:b04fe172-dcc7-4e61-9dc0-c77483544457; MainAdminID:64772
- Journal Information:
- Applied Energy, Journal Name: Applied Energy Vol. 321
- Country of Publication:
- United States
- Language:
- English
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