Chance constrained unit commitment approximation under stochastic wind energy

With the increasing integration of renewable energy into power networks, scheduling and operation systems become more challenging, in particular because intermittency wind speed. Thus, appropriate optimization tools are needed to efficiently manage modern systems. This paper considers unit commitment problem under high penetration. To mitigate potential negative effects inaccurate forecast, a chance constrained model is employed guarantee that supply demand for be balanced at each time period over finite planning horizon. As joint constraint known difficult handle analytically, two approximation approaches, namely quantile- p-efficiency-based, proposed benchmarked against well-known scenario-based approximation. The results indicate schemes provide feasible solutions tight lower bounds true cost within much shorter frame than counterpart.