Abstract :
With large scale wind integration into power grid, the monthly unit commitment scheduling and the consumption of wind have great challenges due to the randomness and correlation of wind power. In view of the randomness of wind power, reserve and security constraints are addressed in the probability form, further the chance-constrained model of monthly unit commitment is derived. Then, the correlation between the wind farms is considered, and the combined probability distribution of various wind farms is described and established by dependent probabilistic sequence operation theory. Accordingly, the chance-constrained stochastic formulation is converted into a deterministic programming problem, which can avoid the tedious process of simulation, and a mixed integer linear programming method is utilized to solve the monthly scheduling problem. Numerical cases are performed with a modified IEEE 118-bus system. The results show the viability of the proposed formulation.
