A Multi-Stage Stochastic Risk Assessment With Markovian Representation of Renewable Power
Journal Article
·
· IEEE Transactions on Sustainable Energy
Probabilistic forecasts provide a distribution of possible outputs and so can capture the uncertainty and variability of Variable Renewable Energy (VRE). However, taking advantage of uncertainty information has practical challenges that make it difficult to integrate probabilistic forecasting into control room decision-making. This paper proposes a novel use-case for probabilistic forecasts by incorporating them into the hour-ahead operations for situational awareness via a risk-averse multi-stage stochastic program. We employ a Markovian representation of the probabilistic forecasts that enables the formulation of the multi-stage problem and avoids a scenario generation phase. We test the model on a realistically sized system to assess risk and showcase the capability of using probabilistic renewable forecast as input to produce probabilistic output forecasts of future system states. The results show that the model can capture time consistency in the reserves and Area Control Error (ACE) forecast. The solution times are adequate for risk profiling in hour-ahead timescales.
- 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:
- 1866771
- Report Number(s):
- NREL/JA-6A40-82849; MainId:83622; UUID:e4a518a0-cda4-41db-be06-ba0e218528f5; MainAdminID:64462
- Journal Information:
- IEEE Transactions on Sustainable Energy, Journal Name: IEEE Transactions on Sustainable Energy Journal Issue: 1 Vol. 13
- Country of Publication:
- United States
- Language:
- English
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