Interval optimization combined with point estimate method for stochastic security-constrained unit commitment

To the stochastic nature of unit commitment problem induced by wind power fluctuation, an interval optimization combined with point estimation method (IO-PEM) is proposed to model and solve stochastic security constrained unit commitment (SCUC) problem. Considering reasonable fluctuation range of wind power, an interval optimization model is established which takes two worst-case scenarios to replace all scenarios in the interval. This model accelerates the solution speed on the premise that the scheduling result meets security constraints. At the same time, in order to accurately evaluate corrective dispatching cost caused by wind power fluctuations and make the scheduling scheme more economic, two kinds of point estimation method: 2M and 2M + 1 schemes, are introduced to improve the accuracy of the interval optimization approach. Comparison studies are done with the proposed method over three conventional methods: Monte Carlo method, the scenario reduction method and the interval optimization method, on the six-bus system and the modified IEEE 118-bus system, the simulation results show that the proposed method has the merits in computation speed and accuracy, in the meanwhile keeping security and economy of the dispatching scheme.