Scenario Creation and Power-Conditioning Strategies for Operating Power Grids with Two-Stage Stochastic Economic Dispatch: Preprint
Conference
·
OSTI ID:1735620
A significant difficultly associated with the use of stochastic programming to solve optimal power flow problems on a 5-minute timescale is the quality of renewable energy scenarios input by the user. This is especially true when considering power systems with high penetrations of renewable energy, e.g. wind power. This paper introduces the use of stochastic programming to solve the DCOPF problem with scenarios drawn directly from high-fidelity data sets. Hence, the proposed method avoids the problem of lost physics by finding high-fidelity analogs that can describe future states of the system. Furthermore, this method can be simply extended to output multi-period scenarios to the stochastic program. We demonstrate the effectiveness of this technique on simulated dispatch operations of the RTS-GMLC over a week.
- Research Organization:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Grid Modernization Lab Consortium (GMLC); USDOE Exascale Computing Project (ECP)
- DOE Contract Number:
- AC36-08GO28308;
- OSTI ID:
- 1735620
- Report Number(s):
- NREL/CP-2C00-75363; MainId:6726; UUID:a5865b8f-2c00-ea11-9c29-ac162d87dfe5; MainAdminID:18655
- Conference Information:
- Presented at the 2020 IEEE Power and Energy Society General Meeting (IEEE PES GM), 3-6 August 2020
- Country of Publication:
- United States
- Language:
- English
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