Importance Sampling with Analog Scenarios for Stochastic Economic Dispatch
Conference
·
OSTI ID:1483233
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Increasing penetrations of renewable energy sources such as wind into power grids motivates the investigation of new approaches to 5-minute economic dispatch computation. In this poster, we investigate the application of importance sampling in the two-stage stochastic economic dispatch problem while using historical data to characterize uncertainty. In our numerical experiments, we observe that importance sampling performs better than the standard Monte Carlo sampling approach in preventing loss-of-load. While first-stage costs are comparable for both sampling methods, the second-stage costs are significantly reduced when the importance sampling method is employed.
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21), Scientific Discovery through Advanced Computing (SciDAC)
- DOE Contract Number:
- AC36-08GO28308;
- OSTI ID:
- 1483233
- Report Number(s):
- NREL/PO-2C00-72784
- Conference Information:
- Presented at the Energy Systems and Optimization Workshop 2018, 15-16 November 2018, Atlanta, Georgia
- Country of Publication:
- United States
- Language:
- English
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