title: A three-stage birandom program for unit commitment with wind power uncertainty.
abstract: The integration of large-scale wind power adds a significant uncertainty to power system planning and operating. The wind forecast error is decreased with the forecast horizon, particularly when it is from one day to several hours ahead. Integrating intraday unit commitment (UC) adjustment process based on updated ultra-short term wind forecast information is one way to improve the dispatching results. A novel three-stage UC decision method, in which the day-ahead UC decisions are determined in the first stage, the intraday UC adjustment decisions of subfast start units are determined in the second stage, and the UC decisions of fast-start units and dispatching decisions are determined in the third stage is presented. Accordingly, a three-stage birandom UC model is presented, in which the intraday hours-ahead forecasted wind power is formulated as a birandom variable, and the intraday UC adjustment event is formulated as a birandom event. The equilibrium chance constraint is employed to ensure the reliability requirement. A birandom simulation based hybrid genetic algorithm is designed to solve the proposed model. Some computational results indicate that the proposed model provides UC decisions with lower expected total costs.
authors.affiliation: School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China.
authors.forename: Na
authors.initials: N
authors.lastname: Zhang
authors.affiliation: School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China.
authors.forename: Weidong
authors.initials: W
authors.lastname: Li
authors.affiliation: School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China.
authors.forename: Rao
authors.initials: R
authors.lastname: Liu
authors.affiliation: School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China.
authors.forename: Quan
authors.initials: Q
authors.lastname: Lv
authors.affiliation: State Grid Shenyang Electric Power Supply Company, Shenyang 110021, China.
authors.forename: Liang
authors.initials: L
authors.lastname: Sun
mesh_terms: D000465:Algorithms; D006801:Humans; D008962:Models, Theoretical