Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: A comparative study

Hao Quan, Dipti Srinivasan and Abbas Khosravi

Energy, 2016, vol. 103, issue C, 735-745

Abstract: The uncertainties of renewable energy have brought great challenges to power system commitment, dispatches and reserve requirement. This paper presents a comparative study on integration of renewable generation uncertainties into SCUC (stochastic security-constrained unit commitment) considering reserve and risk. Renewable forecast uncertainties are captured by a list of PIs (prediction intervals). A new scenario generation method is proposed to generate scenarios from these PIs. Different system uncertainties are considered as scenarios in the stochastic SCUC problem formulation. Two comparative simulations with single (E1: wind only) and multiple sources of uncertainty (E2: load, wind, solar and generation outages) are investigated. Five deterministic and four stochastic case studies are performed. Different generation costs, reserve strategies and associated risks are compared under various scenarios. Demonstrated results indicate the overall costs of E2 is lower than E1 due to penetration of solar power and the associated risk in deterministic cases of E2 is higher than E1. It implies the superimposed effect of uncertainties during uncertainty integration. The results also demonstrate that power systems run a higher level of risk during peak load hours, and that stochastic models are more robust than deterministic ones.

Keywords: Scenario generation; Uncertainty; Renewable generation; Unit commitment; Genetic algorithm; Risk assessment (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (20)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:103:y:2016:i:c:p:735-745

DOI: 10.1016/j.energy.2016.03.007

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