Load Restoration Flexible Optimization in Wind Power Integrated System Based on Conditional Value at Risk

In order to better accommodate the uncertainty induced from a high penetration of wind power during load recovery, method restoration flexible optimization is developed in this paper. First, idea adopting operational constraints when optimizing schemes presented so as not be too conservative application output restoration. Further, conditional value at risk (CVaR) employed define an constraint slacking factor (OCSF) through analyzing extent exceeding prescribed limits speed taking outside its confidence interval. Adopting OCSF, mixed integer linear programming (MILP) model restoration, constructed based on primary by substituting adjustable for rigid constraints, which can solved with CPLEX. Finally, New England 10-unit 39-bus system used demonstrate proposed method, and results explicitly indicate that amount picked up effectively increased security guaranteed well.