Two-Stage Robust Security-Constrained Unit Commitment Model Considering Time Autocorrelation of Wind/Load Prediction Error and Outage Contingency Probability of Units

• Published in: IEEE access Vol. 7; pp. 25398 - 25408
• Main Authors: Zhang, Zhi, Chen, Yanbo, Liu, Xinyuan, Wang, Weiru
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Benders decomposition; Constraints; Contingency; Correlation; Correlation analysis; Economic dispatch; Load modeling; Numerical models; Optimization; Power systems; Predictive models; robust optimization; Robustness (mathematics); Security; Time correlation functions; Uncertainty; uncertainty set; Unit commitment; unit outage contingency; Wind power; Wind power generation; wind/load uncertainty
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2019.2900254

The conservativeness of unit commitment models-based robust optimization (RO) depends on the modeling of uncertainty sets. This paper proposes a new two-stage robust security-constrained unit commitment (SCUC) model, which aims at minimizing the operating cost in the base scenario while guaranteeing that the robust solution can be adaptively and safely adjusted according to the uncertainties of wind power, load, and <inline-formula> <tex-math notation="LaTeX">N </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula> fault. This new model has the following characteristics: 1) the temporal correlation of continuous uncertainties (i.e., wind power output and load) are studied and a time-correlation constraint is established to reduce the conservativeness of uncertainty sets in the proposed robust SCUC model; 2) the discrete characteristics of the uncertain set is used to describe the uncertainty of discrete <inline-formula> <tex-math notation="LaTeX">N </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula> fault; 3) the outage probability of units with different capacity is also considered with a proposed probability criterion; and 4) the constraint approximation is simplified to a linear constraint that can be applied to RO. The proposed model is solved by the Benders decomposition and dual theory. The simulation results on modified IEEE-RTS-96 system show that the proposed method can effectively reduce the conservativeness of uncertain sets and ensure the economic and security of the optimization results.