Chance-constrained programming model for reference network with wind power integration

With the large-scale integration of volatile wind power generations, power system operation and planning face the problem of increasing injection fluctuations and uncertainties. In this paper, chance constraint expressions are used to characterize the wind power uncertainty, and then a new chance-constrained programming model for reference network with wind power integration is proposed to ensure the expected wind power utilization. In the proposed model, the objective function is minimizing total power generation cost and transmission investment cost, and the constraints are the safety operation technical requirements under intact operation state and the preconceived contingency operation state. The sample average approximation (SAA) method is used to develop a deterministic approach for the proposed model. Numerical analysis shows the potential benefit of the proposed model.